Annotation of imach/src/imach.c, revision 1.332
1.332 ! brouard 1: /* $Id: imach.c,v 1.331 2022/08/07 05:40:09 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.332 ! brouard 4: Revision 1.331 2022/08/07 05:40:09 brouard
! 5: *** empty log message ***
! 6:
1.331 brouard 7: Revision 1.330 2022/08/06 07:18:25 brouard
8: Summary: last 0.99r31
9:
10: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
11:
1.330 brouard 12: Revision 1.329 2022/08/03 17:29:54 brouard
13: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
14:
1.329 brouard 15: Revision 1.328 2022/07/27 17:40:48 brouard
16: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
17:
1.328 brouard 18: Revision 1.327 2022/07/27 14:47:35 brouard
19: Summary: Still a problem for one-step probabilities in case of quantitative variables
20:
1.327 brouard 21: Revision 1.326 2022/07/26 17:33:55 brouard
22: Summary: some test with nres=1
23:
1.326 brouard 24: Revision 1.325 2022/07/25 14:27:23 brouard
25: Summary: r30
26:
27: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
28: coredumped, revealed by Feiuno, thank you.
29:
1.325 brouard 30: Revision 1.324 2022/07/23 17:44:26 brouard
31: *** empty log message ***
32:
1.324 brouard 33: Revision 1.323 2022/07/22 12:30:08 brouard
34: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
35:
1.323 brouard 36: Revision 1.322 2022/07/22 12:27:48 brouard
37: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
38:
1.322 brouard 39: Revision 1.321 2022/07/22 12:04:24 brouard
40: Summary: r28
41:
42: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
43:
1.321 brouard 44: Revision 1.320 2022/06/02 05:10:11 brouard
45: *** empty log message ***
46:
1.320 brouard 47: Revision 1.319 2022/06/02 04:45:11 brouard
48: * imach.c (Module): Adding the Wald tests from the log to the main
49: htm for better display of the maximum likelihood estimators.
50:
1.319 brouard 51: Revision 1.318 2022/05/24 08:10:59 brouard
52: * imach.c (Module): Some attempts to find a bug of wrong estimates
53: of confidencce intervals with product in the equation modelC
54:
1.318 brouard 55: Revision 1.317 2022/05/15 15:06:23 brouard
56: * imach.c (Module): Some minor improvements
57:
1.317 brouard 58: Revision 1.316 2022/05/11 15:11:31 brouard
59: Summary: r27
60:
1.316 brouard 61: Revision 1.315 2022/05/11 15:06:32 brouard
62: *** empty log message ***
63:
1.315 brouard 64: Revision 1.314 2022/04/13 17:43:09 brouard
65: * imach.c (Module): Adding link to text data files
66:
1.314 brouard 67: Revision 1.313 2022/04/11 15:57:42 brouard
68: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
69:
1.313 brouard 70: Revision 1.312 2022/04/05 21:24:39 brouard
71: *** empty log message ***
72:
1.312 brouard 73: Revision 1.311 2022/04/05 21:03:51 brouard
74: Summary: Fixed quantitative covariates
75:
76: Fixed covariates (dummy or quantitative)
77: with missing values have never been allowed but are ERRORS and
78: program quits. Standard deviations of fixed covariates were
79: wrongly computed. Mean and standard deviations of time varying
80: covariates are still not computed.
81:
1.311 brouard 82: Revision 1.310 2022/03/17 08:45:53 brouard
83: Summary: 99r25
84:
85: Improving detection of errors: result lines should be compatible with
86: the model.
87:
1.310 brouard 88: Revision 1.309 2021/05/20 12:39:14 brouard
89: Summary: Version 0.99r24
90:
1.309 brouard 91: Revision 1.308 2021/03/31 13:11:57 brouard
92: Summary: Version 0.99r23
93:
94:
95: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
96:
1.308 brouard 97: Revision 1.307 2021/03/08 18:11:32 brouard
98: Summary: 0.99r22 fixed bug on result:
99:
1.307 brouard 100: Revision 1.306 2021/02/20 15:44:02 brouard
101: Summary: Version 0.99r21
102:
103: * imach.c (Module): Fix bug on quitting after result lines!
104: (Module): Version 0.99r21
105:
1.306 brouard 106: Revision 1.305 2021/02/20 15:28:30 brouard
107: * imach.c (Module): Fix bug on quitting after result lines!
108:
1.305 brouard 109: Revision 1.304 2021/02/12 11:34:20 brouard
110: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
111:
1.304 brouard 112: Revision 1.303 2021/02/11 19:50:15 brouard
113: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
114:
1.303 brouard 115: Revision 1.302 2020/02/22 21:00:05 brouard
116: * (Module): imach.c Update mle=-3 (for computing Life expectancy
117: and life table from the data without any state)
118:
1.302 brouard 119: Revision 1.301 2019/06/04 13:51:20 brouard
120: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
121:
1.301 brouard 122: Revision 1.300 2019/05/22 19:09:45 brouard
123: Summary: version 0.99r19 of May 2019
124:
1.300 brouard 125: Revision 1.299 2019/05/22 18:37:08 brouard
126: Summary: Cleaned 0.99r19
127:
1.299 brouard 128: Revision 1.298 2019/05/22 18:19:56 brouard
129: *** empty log message ***
130:
1.298 brouard 131: Revision 1.297 2019/05/22 17:56:10 brouard
132: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
133:
1.297 brouard 134: Revision 1.296 2019/05/20 13:03:18 brouard
135: Summary: Projection syntax simplified
136:
137:
138: We can now start projections, forward or backward, from the mean date
139: of inteviews up to or down to a number of years of projection:
140: prevforecast=1 yearsfproj=15.3 mobil_average=0
141: or
142: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
143: or
144: prevbackcast=1 yearsbproj=12.3 mobil_average=1
145: or
146: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
147:
1.296 brouard 148: Revision 1.295 2019/05/18 09:52:50 brouard
149: Summary: doxygen tex bug
150:
1.295 brouard 151: Revision 1.294 2019/05/16 14:54:33 brouard
152: Summary: There was some wrong lines added
153:
1.294 brouard 154: Revision 1.293 2019/05/09 15:17:34 brouard
155: *** empty log message ***
156:
1.293 brouard 157: Revision 1.292 2019/05/09 14:17:20 brouard
158: Summary: Some updates
159:
1.292 brouard 160: Revision 1.291 2019/05/09 13:44:18 brouard
161: Summary: Before ncovmax
162:
1.291 brouard 163: Revision 1.290 2019/05/09 13:39:37 brouard
164: Summary: 0.99r18 unlimited number of individuals
165:
166: 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.
167:
1.290 brouard 168: Revision 1.289 2018/12/13 09:16:26 brouard
169: Summary: Bug for young ages (<-30) will be in r17
170:
1.289 brouard 171: Revision 1.288 2018/05/02 20:58:27 brouard
172: Summary: Some bugs fixed
173:
1.288 brouard 174: Revision 1.287 2018/05/01 17:57:25 brouard
175: Summary: Bug fixed by providing frequencies only for non missing covariates
176:
1.287 brouard 177: Revision 1.286 2018/04/27 14:27:04 brouard
178: Summary: some minor bugs
179:
1.286 brouard 180: Revision 1.285 2018/04/21 21:02:16 brouard
181: Summary: Some bugs fixed, valgrind tested
182:
1.285 brouard 183: Revision 1.284 2018/04/20 05:22:13 brouard
184: Summary: Computing mean and stdeviation of fixed quantitative variables
185:
1.284 brouard 186: Revision 1.283 2018/04/19 14:49:16 brouard
187: Summary: Some minor bugs fixed
188:
1.283 brouard 189: Revision 1.282 2018/02/27 22:50:02 brouard
190: *** empty log message ***
191:
1.282 brouard 192: Revision 1.281 2018/02/27 19:25:23 brouard
193: Summary: Adding second argument for quitting
194:
1.281 brouard 195: Revision 1.280 2018/02/21 07:58:13 brouard
196: Summary: 0.99r15
197:
198: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
199:
1.280 brouard 200: Revision 1.279 2017/07/20 13:35:01 brouard
201: Summary: temporary working
202:
1.279 brouard 203: Revision 1.278 2017/07/19 14:09:02 brouard
204: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
205:
1.278 brouard 206: Revision 1.277 2017/07/17 08:53:49 brouard
207: Summary: BOM files can be read now
208:
1.277 brouard 209: Revision 1.276 2017/06/30 15:48:31 brouard
210: Summary: Graphs improvements
211:
1.276 brouard 212: Revision 1.275 2017/06/30 13:39:33 brouard
213: Summary: Saito's color
214:
1.275 brouard 215: Revision 1.274 2017/06/29 09:47:08 brouard
216: Summary: Version 0.99r14
217:
1.274 brouard 218: Revision 1.273 2017/06/27 11:06:02 brouard
219: Summary: More documentation on projections
220:
1.273 brouard 221: Revision 1.272 2017/06/27 10:22:40 brouard
222: Summary: Color of backprojection changed from 6 to 5(yellow)
223:
1.272 brouard 224: Revision 1.271 2017/06/27 10:17:50 brouard
225: Summary: Some bug with rint
226:
1.271 brouard 227: Revision 1.270 2017/05/24 05:45:29 brouard
228: *** empty log message ***
229:
1.270 brouard 230: Revision 1.269 2017/05/23 08:39:25 brouard
231: Summary: Code into subroutine, cleanings
232:
1.269 brouard 233: Revision 1.268 2017/05/18 20:09:32 brouard
234: Summary: backprojection and confidence intervals of backprevalence
235:
1.268 brouard 236: Revision 1.267 2017/05/13 10:25:05 brouard
237: Summary: temporary save for backprojection
238:
1.267 brouard 239: Revision 1.266 2017/05/13 07:26:12 brouard
240: Summary: Version 0.99r13 (improvements and bugs fixed)
241:
1.266 brouard 242: Revision 1.265 2017/04/26 16:22:11 brouard
243: Summary: imach 0.99r13 Some bugs fixed
244:
1.265 brouard 245: Revision 1.264 2017/04/26 06:01:29 brouard
246: Summary: Labels in graphs
247:
1.264 brouard 248: Revision 1.263 2017/04/24 15:23:15 brouard
249: Summary: to save
250:
1.263 brouard 251: Revision 1.262 2017/04/18 16:48:12 brouard
252: *** empty log message ***
253:
1.262 brouard 254: Revision 1.261 2017/04/05 10:14:09 brouard
255: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
256:
1.261 brouard 257: Revision 1.260 2017/04/04 17:46:59 brouard
258: Summary: Gnuplot indexations fixed (humm)
259:
1.260 brouard 260: Revision 1.259 2017/04/04 13:01:16 brouard
261: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
262:
1.259 brouard 263: Revision 1.258 2017/04/03 10:17:47 brouard
264: Summary: Version 0.99r12
265:
266: Some cleanings, conformed with updated documentation.
267:
1.258 brouard 268: Revision 1.257 2017/03/29 16:53:30 brouard
269: Summary: Temp
270:
1.257 brouard 271: Revision 1.256 2017/03/27 05:50:23 brouard
272: Summary: Temporary
273:
1.256 brouard 274: Revision 1.255 2017/03/08 16:02:28 brouard
275: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
276:
1.255 brouard 277: Revision 1.254 2017/03/08 07:13:00 brouard
278: Summary: Fixing data parameter line
279:
1.254 brouard 280: Revision 1.253 2016/12/15 11:59:41 brouard
281: Summary: 0.99 in progress
282:
1.253 brouard 283: Revision 1.252 2016/09/15 21:15:37 brouard
284: *** empty log message ***
285:
1.252 brouard 286: Revision 1.251 2016/09/15 15:01:13 brouard
287: Summary: not working
288:
1.251 brouard 289: Revision 1.250 2016/09/08 16:07:27 brouard
290: Summary: continue
291:
1.250 brouard 292: Revision 1.249 2016/09/07 17:14:18 brouard
293: Summary: Starting values from frequencies
294:
1.249 brouard 295: Revision 1.248 2016/09/07 14:10:18 brouard
296: *** empty log message ***
297:
1.248 brouard 298: Revision 1.247 2016/09/02 11:11:21 brouard
299: *** empty log message ***
300:
1.247 brouard 301: Revision 1.246 2016/09/02 08:49:22 brouard
302: *** empty log message ***
303:
1.246 brouard 304: Revision 1.245 2016/09/02 07:25:01 brouard
305: *** empty log message ***
306:
1.245 brouard 307: Revision 1.244 2016/09/02 07:17:34 brouard
308: *** empty log message ***
309:
1.244 brouard 310: Revision 1.243 2016/09/02 06:45:35 brouard
311: *** empty log message ***
312:
1.243 brouard 313: Revision 1.242 2016/08/30 15:01:20 brouard
314: Summary: Fixing a lots
315:
1.242 brouard 316: Revision 1.241 2016/08/29 17:17:25 brouard
317: Summary: gnuplot problem in Back projection to fix
318:
1.241 brouard 319: Revision 1.240 2016/08/29 07:53:18 brouard
320: Summary: Better
321:
1.240 brouard 322: Revision 1.239 2016/08/26 15:51:03 brouard
323: Summary: Improvement in Powell output in order to copy and paste
324:
325: Author:
326:
1.239 brouard 327: Revision 1.238 2016/08/26 14:23:35 brouard
328: Summary: Starting tests of 0.99
329:
1.238 brouard 330: Revision 1.237 2016/08/26 09:20:19 brouard
331: Summary: to valgrind
332:
1.237 brouard 333: Revision 1.236 2016/08/25 10:50:18 brouard
334: *** empty log message ***
335:
1.236 brouard 336: Revision 1.235 2016/08/25 06:59:23 brouard
337: *** empty log message ***
338:
1.235 brouard 339: Revision 1.234 2016/08/23 16:51:20 brouard
340: *** empty log message ***
341:
1.234 brouard 342: Revision 1.233 2016/08/23 07:40:50 brouard
343: Summary: not working
344:
1.233 brouard 345: Revision 1.232 2016/08/22 14:20:21 brouard
346: Summary: not working
347:
1.232 brouard 348: Revision 1.231 2016/08/22 07:17:15 brouard
349: Summary: not working
350:
1.231 brouard 351: Revision 1.230 2016/08/22 06:55:53 brouard
352: Summary: Not working
353:
1.230 brouard 354: Revision 1.229 2016/07/23 09:45:53 brouard
355: Summary: Completing for func too
356:
1.229 brouard 357: Revision 1.228 2016/07/22 17:45:30 brouard
358: Summary: Fixing some arrays, still debugging
359:
1.227 brouard 360: Revision 1.226 2016/07/12 18:42:34 brouard
361: Summary: temp
362:
1.226 brouard 363: Revision 1.225 2016/07/12 08:40:03 brouard
364: Summary: saving but not running
365:
1.225 brouard 366: Revision 1.224 2016/07/01 13:16:01 brouard
367: Summary: Fixes
368:
1.224 brouard 369: Revision 1.223 2016/02/19 09:23:35 brouard
370: Summary: temporary
371:
1.223 brouard 372: Revision 1.222 2016/02/17 08:14:50 brouard
373: Summary: Probably last 0.98 stable version 0.98r6
374:
1.222 brouard 375: Revision 1.221 2016/02/15 23:35:36 brouard
376: Summary: minor bug
377:
1.220 brouard 378: Revision 1.219 2016/02/15 00:48:12 brouard
379: *** empty log message ***
380:
1.219 brouard 381: Revision 1.218 2016/02/12 11:29:23 brouard
382: Summary: 0.99 Back projections
383:
1.218 brouard 384: Revision 1.217 2015/12/23 17:18:31 brouard
385: Summary: Experimental backcast
386:
1.217 brouard 387: Revision 1.216 2015/12/18 17:32:11 brouard
388: Summary: 0.98r4 Warning and status=-2
389:
390: Version 0.98r4 is now:
391: - displaying an error when status is -1, date of interview unknown and date of death known;
392: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
393: Older changes concerning s=-2, dating from 2005 have been supersed.
394:
1.216 brouard 395: Revision 1.215 2015/12/16 08:52:24 brouard
396: Summary: 0.98r4 working
397:
1.215 brouard 398: Revision 1.214 2015/12/16 06:57:54 brouard
399: Summary: temporary not working
400:
1.214 brouard 401: Revision 1.213 2015/12/11 18:22:17 brouard
402: Summary: 0.98r4
403:
1.213 brouard 404: Revision 1.212 2015/11/21 12:47:24 brouard
405: Summary: minor typo
406:
1.212 brouard 407: Revision 1.211 2015/11/21 12:41:11 brouard
408: Summary: 0.98r3 with some graph of projected cross-sectional
409:
410: Author: Nicolas Brouard
411:
1.211 brouard 412: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 413: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 414: Summary: Adding ftolpl parameter
415: Author: N Brouard
416:
417: We had difficulties to get smoothed confidence intervals. It was due
418: to the period prevalence which wasn't computed accurately. The inner
419: parameter ftolpl is now an outer parameter of the .imach parameter
420: file after estepm. If ftolpl is small 1.e-4 and estepm too,
421: computation are long.
422:
1.209 brouard 423: Revision 1.208 2015/11/17 14:31:57 brouard
424: Summary: temporary
425:
1.208 brouard 426: Revision 1.207 2015/10/27 17:36:57 brouard
427: *** empty log message ***
428:
1.207 brouard 429: Revision 1.206 2015/10/24 07:14:11 brouard
430: *** empty log message ***
431:
1.206 brouard 432: Revision 1.205 2015/10/23 15:50:53 brouard
433: Summary: 0.98r3 some clarification for graphs on likelihood contributions
434:
1.205 brouard 435: Revision 1.204 2015/10/01 16:20:26 brouard
436: Summary: Some new graphs of contribution to likelihood
437:
1.204 brouard 438: Revision 1.203 2015/09/30 17:45:14 brouard
439: Summary: looking at better estimation of the hessian
440:
441: Also a better criteria for convergence to the period prevalence And
442: therefore adding the number of years needed to converge. (The
443: prevalence in any alive state shold sum to one
444:
1.203 brouard 445: Revision 1.202 2015/09/22 19:45:16 brouard
446: Summary: Adding some overall graph on contribution to likelihood. Might change
447:
1.202 brouard 448: Revision 1.201 2015/09/15 17:34:58 brouard
449: Summary: 0.98r0
450:
451: - Some new graphs like suvival functions
452: - Some bugs fixed like model=1+age+V2.
453:
1.201 brouard 454: Revision 1.200 2015/09/09 16:53:55 brouard
455: Summary: Big bug thanks to Flavia
456:
457: Even model=1+age+V2. did not work anymore
458:
1.200 brouard 459: Revision 1.199 2015/09/07 14:09:23 brouard
460: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
461:
1.199 brouard 462: Revision 1.198 2015/09/03 07:14:39 brouard
463: Summary: 0.98q5 Flavia
464:
1.198 brouard 465: Revision 1.197 2015/09/01 18:24:39 brouard
466: *** empty log message ***
467:
1.197 brouard 468: Revision 1.196 2015/08/18 23:17:52 brouard
469: Summary: 0.98q5
470:
1.196 brouard 471: Revision 1.195 2015/08/18 16:28:39 brouard
472: Summary: Adding a hack for testing purpose
473:
474: After reading the title, ftol and model lines, if the comment line has
475: a q, starting with #q, the answer at the end of the run is quit. It
476: permits to run test files in batch with ctest. The former workaround was
477: $ echo q | imach foo.imach
478:
1.195 brouard 479: Revision 1.194 2015/08/18 13:32:00 brouard
480: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
481:
1.194 brouard 482: Revision 1.193 2015/08/04 07:17:42 brouard
483: Summary: 0.98q4
484:
1.193 brouard 485: Revision 1.192 2015/07/16 16:49:02 brouard
486: Summary: Fixing some outputs
487:
1.192 brouard 488: Revision 1.191 2015/07/14 10:00:33 brouard
489: Summary: Some fixes
490:
1.191 brouard 491: Revision 1.190 2015/05/05 08:51:13 brouard
492: Summary: Adding digits in output parameters (7 digits instead of 6)
493:
494: Fix 1+age+.
495:
1.190 brouard 496: Revision 1.189 2015/04/30 14:45:16 brouard
497: Summary: 0.98q2
498:
1.189 brouard 499: Revision 1.188 2015/04/30 08:27:53 brouard
500: *** empty log message ***
501:
1.188 brouard 502: Revision 1.187 2015/04/29 09:11:15 brouard
503: *** empty log message ***
504:
1.187 brouard 505: Revision 1.186 2015/04/23 12:01:52 brouard
506: Summary: V1*age is working now, version 0.98q1
507:
508: Some codes had been disabled in order to simplify and Vn*age was
509: working in the optimization phase, ie, giving correct MLE parameters,
510: but, as usual, outputs were not correct and program core dumped.
511:
1.186 brouard 512: Revision 1.185 2015/03/11 13:26:42 brouard
513: Summary: Inclusion of compile and links command line for Intel Compiler
514:
1.185 brouard 515: Revision 1.184 2015/03/11 11:52:39 brouard
516: Summary: Back from Windows 8. Intel Compiler
517:
1.184 brouard 518: Revision 1.183 2015/03/10 20:34:32 brouard
519: Summary: 0.98q0, trying with directest, mnbrak fixed
520:
521: We use directest instead of original Powell test; probably no
522: incidence on the results, but better justifications;
523: We fixed Numerical Recipes mnbrak routine which was wrong and gave
524: wrong results.
525:
1.183 brouard 526: Revision 1.182 2015/02/12 08:19:57 brouard
527: Summary: Trying to keep directest which seems simpler and more general
528: Author: Nicolas Brouard
529:
1.182 brouard 530: Revision 1.181 2015/02/11 23:22:24 brouard
531: Summary: Comments on Powell added
532:
533: Author:
534:
1.181 brouard 535: Revision 1.180 2015/02/11 17:33:45 brouard
536: Summary: Finishing move from main to function (hpijx and prevalence_limit)
537:
1.180 brouard 538: Revision 1.179 2015/01/04 09:57:06 brouard
539: Summary: back to OS/X
540:
1.179 brouard 541: Revision 1.178 2015/01/04 09:35:48 brouard
542: *** empty log message ***
543:
1.178 brouard 544: Revision 1.177 2015/01/03 18:40:56 brouard
545: Summary: Still testing ilc32 on OSX
546:
1.177 brouard 547: Revision 1.176 2015/01/03 16:45:04 brouard
548: *** empty log message ***
549:
1.176 brouard 550: Revision 1.175 2015/01/03 16:33:42 brouard
551: *** empty log message ***
552:
1.175 brouard 553: Revision 1.174 2015/01/03 16:15:49 brouard
554: Summary: Still in cross-compilation
555:
1.174 brouard 556: Revision 1.173 2015/01/03 12:06:26 brouard
557: Summary: trying to detect cross-compilation
558:
1.173 brouard 559: Revision 1.172 2014/12/27 12:07:47 brouard
560: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
561:
1.172 brouard 562: Revision 1.171 2014/12/23 13:26:59 brouard
563: Summary: Back from Visual C
564:
565: Still problem with utsname.h on Windows
566:
1.171 brouard 567: Revision 1.170 2014/12/23 11:17:12 brouard
568: Summary: Cleaning some \%% back to %%
569:
570: The escape was mandatory for a specific compiler (which one?), but too many warnings.
571:
1.170 brouard 572: Revision 1.169 2014/12/22 23:08:31 brouard
573: Summary: 0.98p
574:
575: Outputs some informations on compiler used, OS etc. Testing on different platforms.
576:
1.169 brouard 577: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 578: Summary: update
1.169 brouard 579:
1.168 brouard 580: Revision 1.167 2014/12/22 13:50:56 brouard
581: Summary: Testing uname and compiler version and if compiled 32 or 64
582:
583: Testing on Linux 64
584:
1.167 brouard 585: Revision 1.166 2014/12/22 11:40:47 brouard
586: *** empty log message ***
587:
1.166 brouard 588: Revision 1.165 2014/12/16 11:20:36 brouard
589: Summary: After compiling on Visual C
590:
591: * imach.c (Module): Merging 1.61 to 1.162
592:
1.165 brouard 593: Revision 1.164 2014/12/16 10:52:11 brouard
594: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
595:
596: * imach.c (Module): Merging 1.61 to 1.162
597:
1.164 brouard 598: Revision 1.163 2014/12/16 10:30:11 brouard
599: * imach.c (Module): Merging 1.61 to 1.162
600:
1.163 brouard 601: Revision 1.162 2014/09/25 11:43:39 brouard
602: Summary: temporary backup 0.99!
603:
1.162 brouard 604: Revision 1.1 2014/09/16 11:06:58 brouard
605: Summary: With some code (wrong) for nlopt
606:
607: Author:
608:
609: Revision 1.161 2014/09/15 20:41:41 brouard
610: Summary: Problem with macro SQR on Intel compiler
611:
1.161 brouard 612: Revision 1.160 2014/09/02 09:24:05 brouard
613: *** empty log message ***
614:
1.160 brouard 615: Revision 1.159 2014/09/01 10:34:10 brouard
616: Summary: WIN32
617: Author: Brouard
618:
1.159 brouard 619: Revision 1.158 2014/08/27 17:11:51 brouard
620: *** empty log message ***
621:
1.158 brouard 622: Revision 1.157 2014/08/27 16:26:55 brouard
623: Summary: Preparing windows Visual studio version
624: Author: Brouard
625:
626: In order to compile on Visual studio, time.h is now correct and time_t
627: and tm struct should be used. difftime should be used but sometimes I
628: just make the differences in raw time format (time(&now).
629: Trying to suppress #ifdef LINUX
630: Add xdg-open for __linux in order to open default browser.
631:
1.157 brouard 632: Revision 1.156 2014/08/25 20:10:10 brouard
633: *** empty log message ***
634:
1.156 brouard 635: Revision 1.155 2014/08/25 18:32:34 brouard
636: Summary: New compile, minor changes
637: Author: Brouard
638:
1.155 brouard 639: Revision 1.154 2014/06/20 17:32:08 brouard
640: Summary: Outputs now all graphs of convergence to period prevalence
641:
1.154 brouard 642: Revision 1.153 2014/06/20 16:45:46 brouard
643: Summary: If 3 live state, convergence to period prevalence on same graph
644: Author: Brouard
645:
1.153 brouard 646: Revision 1.152 2014/06/18 17:54:09 brouard
647: Summary: open browser, use gnuplot on same dir than imach if not found in the path
648:
1.152 brouard 649: Revision 1.151 2014/06/18 16:43:30 brouard
650: *** empty log message ***
651:
1.151 brouard 652: Revision 1.150 2014/06/18 16:42:35 brouard
653: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
654: Author: brouard
655:
1.150 brouard 656: Revision 1.149 2014/06/18 15:51:14 brouard
657: Summary: Some fixes in parameter files errors
658: Author: Nicolas Brouard
659:
1.149 brouard 660: Revision 1.148 2014/06/17 17:38:48 brouard
661: Summary: Nothing new
662: Author: Brouard
663:
664: Just a new packaging for OS/X version 0.98nS
665:
1.148 brouard 666: Revision 1.147 2014/06/16 10:33:11 brouard
667: *** empty log message ***
668:
1.147 brouard 669: Revision 1.146 2014/06/16 10:20:28 brouard
670: Summary: Merge
671: Author: Brouard
672:
673: Merge, before building revised version.
674:
1.146 brouard 675: Revision 1.145 2014/06/10 21:23:15 brouard
676: Summary: Debugging with valgrind
677: Author: Nicolas Brouard
678:
679: Lot of changes in order to output the results with some covariates
680: After the Edimburgh REVES conference 2014, it seems mandatory to
681: improve the code.
682: No more memory valgrind error but a lot has to be done in order to
683: continue the work of splitting the code into subroutines.
684: Also, decodemodel has been improved. Tricode is still not
685: optimal. nbcode should be improved. Documentation has been added in
686: the source code.
687:
1.144 brouard 688: Revision 1.143 2014/01/26 09:45:38 brouard
689: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
690:
691: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
692: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
693:
1.143 brouard 694: Revision 1.142 2014/01/26 03:57:36 brouard
695: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
696:
697: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
698:
1.142 brouard 699: Revision 1.141 2014/01/26 02:42:01 brouard
700: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
701:
1.141 brouard 702: Revision 1.140 2011/09/02 10:37:54 brouard
703: Summary: times.h is ok with mingw32 now.
704:
1.140 brouard 705: Revision 1.139 2010/06/14 07:50:17 brouard
706: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
707: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
708:
1.139 brouard 709: Revision 1.138 2010/04/30 18:19:40 brouard
710: *** empty log message ***
711:
1.138 brouard 712: Revision 1.137 2010/04/29 18:11:38 brouard
713: (Module): Checking covariates for more complex models
714: than V1+V2. A lot of change to be done. Unstable.
715:
1.137 brouard 716: Revision 1.136 2010/04/26 20:30:53 brouard
717: (Module): merging some libgsl code. Fixing computation
718: of likelione (using inter/intrapolation if mle = 0) in order to
719: get same likelihood as if mle=1.
720: Some cleaning of code and comments added.
721:
1.136 brouard 722: Revision 1.135 2009/10/29 15:33:14 brouard
723: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
724:
1.135 brouard 725: Revision 1.134 2009/10/29 13:18:53 brouard
726: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
727:
1.134 brouard 728: Revision 1.133 2009/07/06 10:21:25 brouard
729: just nforces
730:
1.133 brouard 731: Revision 1.132 2009/07/06 08:22:05 brouard
732: Many tings
733:
1.132 brouard 734: Revision 1.131 2009/06/20 16:22:47 brouard
735: Some dimensions resccaled
736:
1.131 brouard 737: Revision 1.130 2009/05/26 06:44:34 brouard
738: (Module): Max Covariate is now set to 20 instead of 8. A
739: lot of cleaning with variables initialized to 0. Trying to make
740: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
741:
1.130 brouard 742: Revision 1.129 2007/08/31 13:49:27 lievre
743: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
744:
1.129 lievre 745: Revision 1.128 2006/06/30 13:02:05 brouard
746: (Module): Clarifications on computing e.j
747:
1.128 brouard 748: Revision 1.127 2006/04/28 18:11:50 brouard
749: (Module): Yes the sum of survivors was wrong since
750: imach-114 because nhstepm was no more computed in the age
751: loop. Now we define nhstepma in the age loop.
752: (Module): In order to speed up (in case of numerous covariates) we
753: compute health expectancies (without variances) in a first step
754: and then all the health expectancies with variances or standard
755: deviation (needs data from the Hessian matrices) which slows the
756: computation.
757: In the future we should be able to stop the program is only health
758: expectancies and graph are needed without standard deviations.
759:
1.127 brouard 760: Revision 1.126 2006/04/28 17:23:28 brouard
761: (Module): Yes the sum of survivors was wrong since
762: imach-114 because nhstepm was no more computed in the age
763: loop. Now we define nhstepma in the age loop.
764: Version 0.98h
765:
1.126 brouard 766: Revision 1.125 2006/04/04 15:20:31 lievre
767: Errors in calculation of health expectancies. Age was not initialized.
768: Forecasting file added.
769:
770: Revision 1.124 2006/03/22 17:13:53 lievre
771: Parameters are printed with %lf instead of %f (more numbers after the comma).
772: The log-likelihood is printed in the log file
773:
774: Revision 1.123 2006/03/20 10:52:43 brouard
775: * imach.c (Module): <title> changed, corresponds to .htm file
776: name. <head> headers where missing.
777:
778: * imach.c (Module): Weights can have a decimal point as for
779: English (a comma might work with a correct LC_NUMERIC environment,
780: otherwise the weight is truncated).
781: Modification of warning when the covariates values are not 0 or
782: 1.
783: Version 0.98g
784:
785: Revision 1.122 2006/03/20 09:45:41 brouard
786: (Module): Weights can have a decimal point as for
787: English (a comma might work with a correct LC_NUMERIC environment,
788: otherwise the weight is truncated).
789: Modification of warning when the covariates values are not 0 or
790: 1.
791: Version 0.98g
792:
793: Revision 1.121 2006/03/16 17:45:01 lievre
794: * imach.c (Module): Comments concerning covariates added
795:
796: * imach.c (Module): refinements in the computation of lli if
797: status=-2 in order to have more reliable computation if stepm is
798: not 1 month. Version 0.98f
799:
800: Revision 1.120 2006/03/16 15:10:38 lievre
801: (Module): refinements in the computation of lli if
802: status=-2 in order to have more reliable computation if stepm is
803: not 1 month. Version 0.98f
804:
805: Revision 1.119 2006/03/15 17:42:26 brouard
806: (Module): Bug if status = -2, the loglikelihood was
807: computed as likelihood omitting the logarithm. Version O.98e
808:
809: Revision 1.118 2006/03/14 18:20:07 brouard
810: (Module): varevsij Comments added explaining the second
811: table of variances if popbased=1 .
812: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
813: (Module): Function pstamp added
814: (Module): Version 0.98d
815:
816: Revision 1.117 2006/03/14 17:16:22 brouard
817: (Module): varevsij Comments added explaining the second
818: table of variances if popbased=1 .
819: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
820: (Module): Function pstamp added
821: (Module): Version 0.98d
822:
823: Revision 1.116 2006/03/06 10:29:27 brouard
824: (Module): Variance-covariance wrong links and
825: varian-covariance of ej. is needed (Saito).
826:
827: Revision 1.115 2006/02/27 12:17:45 brouard
828: (Module): One freematrix added in mlikeli! 0.98c
829:
830: Revision 1.114 2006/02/26 12:57:58 brouard
831: (Module): Some improvements in processing parameter
832: filename with strsep.
833:
834: Revision 1.113 2006/02/24 14:20:24 brouard
835: (Module): Memory leaks checks with valgrind and:
836: datafile was not closed, some imatrix were not freed and on matrix
837: allocation too.
838:
839: Revision 1.112 2006/01/30 09:55:26 brouard
840: (Module): Back to gnuplot.exe instead of wgnuplot.exe
841:
842: Revision 1.111 2006/01/25 20:38:18 brouard
843: (Module): Lots of cleaning and bugs added (Gompertz)
844: (Module): Comments can be added in data file. Missing date values
845: can be a simple dot '.'.
846:
847: Revision 1.110 2006/01/25 00:51:50 brouard
848: (Module): Lots of cleaning and bugs added (Gompertz)
849:
850: Revision 1.109 2006/01/24 19:37:15 brouard
851: (Module): Comments (lines starting with a #) are allowed in data.
852:
853: Revision 1.108 2006/01/19 18:05:42 lievre
854: Gnuplot problem appeared...
855: To be fixed
856:
857: Revision 1.107 2006/01/19 16:20:37 brouard
858: Test existence of gnuplot in imach path
859:
860: Revision 1.106 2006/01/19 13:24:36 brouard
861: Some cleaning and links added in html output
862:
863: Revision 1.105 2006/01/05 20:23:19 lievre
864: *** empty log message ***
865:
866: Revision 1.104 2005/09/30 16:11:43 lievre
867: (Module): sump fixed, loop imx fixed, and simplifications.
868: (Module): If the status is missing at the last wave but we know
869: that the person is alive, then we can code his/her status as -2
870: (instead of missing=-1 in earlier versions) and his/her
871: contributions to the likelihood is 1 - Prob of dying from last
872: health status (= 1-p13= p11+p12 in the easiest case of somebody in
873: the healthy state at last known wave). Version is 0.98
874:
875: Revision 1.103 2005/09/30 15:54:49 lievre
876: (Module): sump fixed, loop imx fixed, and simplifications.
877:
878: Revision 1.102 2004/09/15 17:31:30 brouard
879: Add the possibility to read data file including tab characters.
880:
881: Revision 1.101 2004/09/15 10:38:38 brouard
882: Fix on curr_time
883:
884: Revision 1.100 2004/07/12 18:29:06 brouard
885: Add version for Mac OS X. Just define UNIX in Makefile
886:
887: Revision 1.99 2004/06/05 08:57:40 brouard
888: *** empty log message ***
889:
890: Revision 1.98 2004/05/16 15:05:56 brouard
891: New version 0.97 . First attempt to estimate force of mortality
892: directly from the data i.e. without the need of knowing the health
893: state at each age, but using a Gompertz model: log u =a + b*age .
894: This is the basic analysis of mortality and should be done before any
895: other analysis, in order to test if the mortality estimated from the
896: cross-longitudinal survey is different from the mortality estimated
897: from other sources like vital statistic data.
898:
899: The same imach parameter file can be used but the option for mle should be -3.
900:
1.324 brouard 901: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 902: former routines in order to include the new code within the former code.
903:
904: The output is very simple: only an estimate of the intercept and of
905: the slope with 95% confident intervals.
906:
907: Current limitations:
908: A) Even if you enter covariates, i.e. with the
909: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
910: B) There is no computation of Life Expectancy nor Life Table.
911:
912: Revision 1.97 2004/02/20 13:25:42 lievre
913: Version 0.96d. Population forecasting command line is (temporarily)
914: suppressed.
915:
916: Revision 1.96 2003/07/15 15:38:55 brouard
917: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
918: rewritten within the same printf. Workaround: many printfs.
919:
920: Revision 1.95 2003/07/08 07:54:34 brouard
921: * imach.c (Repository):
922: (Repository): Using imachwizard code to output a more meaningful covariance
923: matrix (cov(a12,c31) instead of numbers.
924:
925: Revision 1.94 2003/06/27 13:00:02 brouard
926: Just cleaning
927:
928: Revision 1.93 2003/06/25 16:33:55 brouard
929: (Module): On windows (cygwin) function asctime_r doesn't
930: exist so I changed back to asctime which exists.
931: (Module): Version 0.96b
932:
933: Revision 1.92 2003/06/25 16:30:45 brouard
934: (Module): On windows (cygwin) function asctime_r doesn't
935: exist so I changed back to asctime which exists.
936:
937: Revision 1.91 2003/06/25 15:30:29 brouard
938: * imach.c (Repository): Duplicated warning errors corrected.
939: (Repository): Elapsed time after each iteration is now output. It
940: helps to forecast when convergence will be reached. Elapsed time
941: is stamped in powell. We created a new html file for the graphs
942: concerning matrix of covariance. It has extension -cov.htm.
943:
944: Revision 1.90 2003/06/24 12:34:15 brouard
945: (Module): Some bugs corrected for windows. Also, when
946: mle=-1 a template is output in file "or"mypar.txt with the design
947: of the covariance matrix to be input.
948:
949: Revision 1.89 2003/06/24 12:30:52 brouard
950: (Module): Some bugs corrected for windows. Also, when
951: mle=-1 a template is output in file "or"mypar.txt with the design
952: of the covariance matrix to be input.
953:
954: Revision 1.88 2003/06/23 17:54:56 brouard
955: * 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.
956:
957: Revision 1.87 2003/06/18 12:26:01 brouard
958: Version 0.96
959:
960: Revision 1.86 2003/06/17 20:04:08 brouard
961: (Module): Change position of html and gnuplot routines and added
962: routine fileappend.
963:
964: Revision 1.85 2003/06/17 13:12:43 brouard
965: * imach.c (Repository): Check when date of death was earlier that
966: current date of interview. It may happen when the death was just
967: prior to the death. In this case, dh was negative and likelihood
968: was wrong (infinity). We still send an "Error" but patch by
969: assuming that the date of death was just one stepm after the
970: interview.
971: (Repository): Because some people have very long ID (first column)
972: we changed int to long in num[] and we added a new lvector for
973: memory allocation. But we also truncated to 8 characters (left
974: truncation)
975: (Repository): No more line truncation errors.
976:
977: Revision 1.84 2003/06/13 21:44:43 brouard
978: * imach.c (Repository): Replace "freqsummary" at a correct
979: place. It differs from routine "prevalence" which may be called
980: many times. Probs is memory consuming and must be used with
981: parcimony.
982: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
983:
984: Revision 1.83 2003/06/10 13:39:11 lievre
985: *** empty log message ***
986:
987: Revision 1.82 2003/06/05 15:57:20 brouard
988: Add log in imach.c and fullversion number is now printed.
989:
990: */
991: /*
992: Interpolated Markov Chain
993:
994: Short summary of the programme:
995:
1.227 brouard 996: This program computes Healthy Life Expectancies or State-specific
997: (if states aren't health statuses) Expectancies from
998: cross-longitudinal data. Cross-longitudinal data consist in:
999:
1000: -1- a first survey ("cross") where individuals from different ages
1001: are interviewed on their health status or degree of disability (in
1002: the case of a health survey which is our main interest)
1003:
1004: -2- at least a second wave of interviews ("longitudinal") which
1005: measure each change (if any) in individual health status. Health
1006: expectancies are computed from the time spent in each health state
1007: according to a model. More health states you consider, more time is
1008: necessary to reach the Maximum Likelihood of the parameters involved
1009: in the model. The simplest model is the multinomial logistic model
1010: where pij is the probability to be observed in state j at the second
1011: wave conditional to be observed in state i at the first
1012: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1013: etc , where 'age' is age and 'sex' is a covariate. If you want to
1014: have a more complex model than "constant and age", you should modify
1015: the program where the markup *Covariates have to be included here
1016: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1017: convergence.
1018:
1019: The advantage of this computer programme, compared to a simple
1020: multinomial logistic model, is clear when the delay between waves is not
1021: identical for each individual. Also, if a individual missed an
1022: intermediate interview, the information is lost, but taken into
1023: account using an interpolation or extrapolation.
1024:
1025: hPijx is the probability to be observed in state i at age x+h
1026: conditional to the observed state i at age x. The delay 'h' can be
1027: split into an exact number (nh*stepm) of unobserved intermediate
1028: states. This elementary transition (by month, quarter,
1029: semester or year) is modelled as a multinomial logistic. The hPx
1030: matrix is simply the matrix product of nh*stepm elementary matrices
1031: and the contribution of each individual to the likelihood is simply
1032: hPijx.
1033:
1034: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1035: of the life expectancies. It also computes the period (stable) prevalence.
1036:
1037: Back prevalence and projections:
1.227 brouard 1038:
1039: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1040: double agemaxpar, double ftolpl, int *ncvyearp, double
1041: dateprev1,double dateprev2, int firstpass, int lastpass, int
1042: mobilavproj)
1043:
1044: Computes the back prevalence limit for any combination of
1045: covariate values k at any age between ageminpar and agemaxpar and
1046: returns it in **bprlim. In the loops,
1047:
1048: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1049: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1050:
1051: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1052: Computes for any combination of covariates k and any age between bage and fage
1053: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1054: oldm=oldms;savm=savms;
1.227 brouard 1055:
1.267 brouard 1056: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1057: Computes the transition matrix starting at age 'age' over
1058: 'nhstepm*hstepm*stepm' months (i.e. until
1059: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1060: nhstepm*hstepm matrices.
1061:
1062: Returns p3mat[i][j][h] after calling
1063: p3mat[i][j][h]=matprod2(newm,
1064: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1065: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1066: oldm);
1.226 brouard 1067:
1068: Important routines
1069:
1070: - func (or funcone), computes logit (pij) distinguishing
1071: o fixed variables (single or product dummies or quantitative);
1072: o varying variables by:
1073: (1) wave (single, product dummies, quantitative),
1074: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1075: % fixed dummy (treated) or quantitative (not done because time-consuming);
1076: % varying dummy (not done) or quantitative (not done);
1077: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1078: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1079: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1080: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1081: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1082:
1.226 brouard 1083:
1084:
1.324 brouard 1085: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1086: Institut national d'études démographiques, Paris.
1.126 brouard 1087: This software have been partly granted by Euro-REVES, a concerted action
1088: from the European Union.
1089: It is copyrighted identically to a GNU software product, ie programme and
1090: software can be distributed freely for non commercial use. Latest version
1091: can be accessed at http://euroreves.ined.fr/imach .
1092:
1093: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1094: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1095:
1096: **********************************************************************/
1097: /*
1098: main
1099: read parameterfile
1100: read datafile
1101: concatwav
1102: freqsummary
1103: if (mle >= 1)
1104: mlikeli
1105: print results files
1106: if mle==1
1107: computes hessian
1108: read end of parameter file: agemin, agemax, bage, fage, estepm
1109: begin-prev-date,...
1110: open gnuplot file
1111: open html file
1.145 brouard 1112: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1113: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1114: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1115: freexexit2 possible for memory heap.
1116:
1117: h Pij x | pij_nom ficrestpij
1118: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1119: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1120: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1121:
1122: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1123: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1124: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1125: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1126: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1127:
1.126 brouard 1128: forecasting if prevfcast==1 prevforecast call prevalence()
1129: health expectancies
1130: Variance-covariance of DFLE
1131: prevalence()
1132: movingaverage()
1133: varevsij()
1134: if popbased==1 varevsij(,popbased)
1135: total life expectancies
1136: Variance of period (stable) prevalence
1137: end
1138: */
1139:
1.187 brouard 1140: /* #define DEBUG */
1141: /* #define DEBUGBRENT */
1.203 brouard 1142: /* #define DEBUGLINMIN */
1143: /* #define DEBUGHESS */
1144: #define DEBUGHESSIJ
1.224 brouard 1145: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1146: #define POWELL /* Instead of NLOPT */
1.224 brouard 1147: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1148: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1149: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1150: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1151:
1152: #include <math.h>
1153: #include <stdio.h>
1154: #include <stdlib.h>
1155: #include <string.h>
1.226 brouard 1156: #include <ctype.h>
1.159 brouard 1157:
1158: #ifdef _WIN32
1159: #include <io.h>
1.172 brouard 1160: #include <windows.h>
1161: #include <tchar.h>
1.159 brouard 1162: #else
1.126 brouard 1163: #include <unistd.h>
1.159 brouard 1164: #endif
1.126 brouard 1165:
1166: #include <limits.h>
1167: #include <sys/types.h>
1.171 brouard 1168:
1169: #if defined(__GNUC__)
1170: #include <sys/utsname.h> /* Doesn't work on Windows */
1171: #endif
1172:
1.126 brouard 1173: #include <sys/stat.h>
1174: #include <errno.h>
1.159 brouard 1175: /* extern int errno; */
1.126 brouard 1176:
1.157 brouard 1177: /* #ifdef LINUX */
1178: /* #include <time.h> */
1179: /* #include "timeval.h" */
1180: /* #else */
1181: /* #include <sys/time.h> */
1182: /* #endif */
1183:
1.126 brouard 1184: #include <time.h>
1185:
1.136 brouard 1186: #ifdef GSL
1187: #include <gsl/gsl_errno.h>
1188: #include <gsl/gsl_multimin.h>
1189: #endif
1190:
1.167 brouard 1191:
1.162 brouard 1192: #ifdef NLOPT
1193: #include <nlopt.h>
1194: typedef struct {
1195: double (* function)(double [] );
1196: } myfunc_data ;
1197: #endif
1198:
1.126 brouard 1199: /* #include <libintl.h> */
1200: /* #define _(String) gettext (String) */
1201:
1.251 brouard 1202: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1203:
1204: #define GNUPLOTPROGRAM "gnuplot"
1205: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1206: #define FILENAMELENGTH 256
1.126 brouard 1207:
1208: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1209: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1210:
1.144 brouard 1211: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1212: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1213:
1214: #define NINTERVMAX 8
1.144 brouard 1215: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1216: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1217: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1218: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1219: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1220: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1221: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1222: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1223: /* #define AGESUP 130 */
1.288 brouard 1224: /* #define AGESUP 150 */
1225: #define AGESUP 200
1.268 brouard 1226: #define AGEINF 0
1.218 brouard 1227: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1228: #define AGEBASE 40
1.194 brouard 1229: #define AGEOVERFLOW 1.e20
1.164 brouard 1230: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1231: #ifdef _WIN32
1232: #define DIRSEPARATOR '\\'
1233: #define CHARSEPARATOR "\\"
1234: #define ODIRSEPARATOR '/'
1235: #else
1.126 brouard 1236: #define DIRSEPARATOR '/'
1237: #define CHARSEPARATOR "/"
1238: #define ODIRSEPARATOR '\\'
1239: #endif
1240:
1.332 ! brouard 1241: /* $Id: imach.c,v 1.331 2022/08/07 05:40:09 brouard Exp $ */
1.126 brouard 1242: /* $State: Exp $ */
1.196 brouard 1243: #include "version.h"
1244: char version[]=__IMACH_VERSION__;
1.332 ! brouard 1245: char copyright[]="August 2022,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, Nihon University 2021-202, INED 2000-2022";
! 1246: char fullversion[]="$Revision: 1.331 $ $Date: 2022/08/07 05:40:09 $";
1.126 brouard 1247: char strstart[80];
1248: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1249: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1250: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1251: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1252: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1253: int cptcovn=0; /**< cptcovn decodemodel: number of covariates k of the models excluding age*products =6 and age*age */
1254: int cptcovt=0; /**< cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
1255: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1.225 brouard 1256: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1257: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1258: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.330 brouard 1259: int cptcoveff=0; /* Total number of covariates to vary for printing results (2**cptcoveff combinations of dummies)(computed in tricode as cptcov) */
1.233 brouard 1260: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1261: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1262: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1263: int nsd=0; /**< Total number of single dummy variables (output) */
1264: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1265: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1266: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1267: int ntveff=0; /**< ntveff number of effective time varying variables */
1268: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1269: int cptcov=0; /* Working variable */
1.290 brouard 1270: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1271: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1272: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1273: int nlstate=2; /* Number of live states */
1274: int ndeath=1; /* Number of dead states */
1.130 brouard 1275: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1276: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1277: int popbased=0;
1278:
1279: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1280: int maxwav=0; /* Maxim number of waves */
1281: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1282: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1283: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1284: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1285: int mle=1, weightopt=0;
1.126 brouard 1286: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1287: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1288: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1289: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1290: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1291: int selected(int kvar); /* Is covariate kvar selected for printing results */
1292:
1.130 brouard 1293: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1294: double **matprod2(); /* test */
1.126 brouard 1295: double **oldm, **newm, **savm; /* Working pointers to matrices */
1296: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1297: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1298:
1.136 brouard 1299: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1300: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1301: FILE *ficlog, *ficrespow;
1.130 brouard 1302: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1303: double fretone; /* Only one call to likelihood */
1.130 brouard 1304: long ipmx=0; /* Number of contributions */
1.126 brouard 1305: double sw; /* Sum of weights */
1306: char filerespow[FILENAMELENGTH];
1307: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1308: FILE *ficresilk;
1309: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1310: FILE *ficresprobmorprev;
1311: FILE *fichtm, *fichtmcov; /* Html File */
1312: FILE *ficreseij;
1313: char filerese[FILENAMELENGTH];
1314: FILE *ficresstdeij;
1315: char fileresstde[FILENAMELENGTH];
1316: FILE *ficrescveij;
1317: char filerescve[FILENAMELENGTH];
1318: FILE *ficresvij;
1319: char fileresv[FILENAMELENGTH];
1.269 brouard 1320:
1.126 brouard 1321: char title[MAXLINE];
1.234 brouard 1322: char model[MAXLINE]; /**< The model line */
1.217 brouard 1323: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1324: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1325: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1326: char command[FILENAMELENGTH];
1327: int outcmd=0;
1328:
1.217 brouard 1329: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1330: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1331: char filelog[FILENAMELENGTH]; /* Log file */
1332: char filerest[FILENAMELENGTH];
1333: char fileregp[FILENAMELENGTH];
1334: char popfile[FILENAMELENGTH];
1335:
1336: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1337:
1.157 brouard 1338: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1339: /* struct timezone tzp; */
1340: /* extern int gettimeofday(); */
1341: struct tm tml, *gmtime(), *localtime();
1342:
1343: extern time_t time();
1344:
1345: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1346: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1347: struct tm tm;
1348:
1.126 brouard 1349: char strcurr[80], strfor[80];
1350:
1351: char *endptr;
1352: long lval;
1353: double dval;
1354:
1355: #define NR_END 1
1356: #define FREE_ARG char*
1357: #define FTOL 1.0e-10
1358:
1359: #define NRANSI
1.240 brouard 1360: #define ITMAX 200
1361: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1362:
1363: #define TOL 2.0e-4
1364:
1365: #define CGOLD 0.3819660
1366: #define ZEPS 1.0e-10
1367: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1368:
1369: #define GOLD 1.618034
1370: #define GLIMIT 100.0
1371: #define TINY 1.0e-20
1372:
1373: static double maxarg1,maxarg2;
1374: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1375: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1376:
1377: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1378: #define rint(a) floor(a+0.5)
1.166 brouard 1379: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1380: #define mytinydouble 1.0e-16
1.166 brouard 1381: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1382: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1383: /* static double dsqrarg; */
1384: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1385: static double sqrarg;
1386: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1387: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1388: int agegomp= AGEGOMP;
1389:
1390: int imx;
1391: int stepm=1;
1392: /* Stepm, step in month: minimum step interpolation*/
1393:
1394: int estepm;
1395: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1396:
1397: int m,nb;
1398: long *num;
1.197 brouard 1399: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1400: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1401: covariate for which somebody answered excluding
1402: undefined. Usually 2: 0 and 1. */
1403: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1404: covariate for which somebody answered including
1405: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1406: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1407: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1408: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 ! brouard 1409: 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 1410: double *ageexmed,*agecens;
1411: double dateintmean=0;
1.296 brouard 1412: double anprojd, mprojd, jprojd; /* For eventual projections */
1413: double anprojf, mprojf, jprojf;
1.126 brouard 1414:
1.296 brouard 1415: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1416: double anbackf, mbackf, jbackf;
1417: double jintmean,mintmean,aintmean;
1.126 brouard 1418: double *weight;
1419: int **s; /* Status */
1.141 brouard 1420: double *agedc;
1.145 brouard 1421: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1422: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1423: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1424: double **coqvar; /* Fixed quantitative covariate nqv */
1425: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1426: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1427: double idx;
1428: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1429: /* Some documentation */
1430: /* Design original data
1431: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1432: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1433: * ntv=3 nqtv=1
1.330 brouard 1434: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1435: * For time varying covariate, quanti or dummies
1436: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1437: * cotvar[wav][ntv+iv][i]= [3+(1 to nqtv)][i]=(V12) quanti
1438: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1439: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 ! brouard 1440: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1441: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1442: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1443: * k= 1 2 3 4 5 6 7 8 9 10 11
1444: */
1445: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1446: /* 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
1447: # States 1=Coresidence, 2 Living alone, 3 Institution
1448: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1449: */
1.319 brouard 1450: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1451: /* k 1 2 3 4 5 6 7 8 9 */
1452: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 *//*0 for simple covariate (dummy, quantitative,*/
1453: /* fixed or varying), 1 for age product, 2 for*/
1454: /* product */
1455: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1456: /*(single or product without age), 2 dummy*/
1457: /* with age product, 3 quant with age product*/
1458: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1459: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1.330 brouard 1460: /*TnsdVar[Tvar] 1 2 3 */
1.319 brouard 1461: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1462: /*TvarsDind[k] 2 3 9 */ /* position K of single dummy cova */
1463: /* nsq 1 2 */ /* Counting single quantit tv */
1464: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1465: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1466: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1467: /* cptcovage 1 2 */ /* Counting cov*age in the model equation */
1468: /* Tage[cptcovage]=k 5 8 */ /* Position in the model of ith cov*age */
1469: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1470: /* 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 1471: /* 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 1472: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1473: /* Type */
1474: /* V 1 2 3 4 5 */
1475: /* F F V V V */
1476: /* D Q D D Q */
1477: /* */
1478: int *TvarsD;
1.330 brouard 1479: int *TnsdVar;
1.234 brouard 1480: int *TvarsDind;
1481: int *TvarsQ;
1482: int *TvarsQind;
1483:
1.318 brouard 1484: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1485: int nresult=0;
1.258 brouard 1486: int parameterline=0; /* # of the parameter (type) line */
1.318 brouard 1487: int TKresult[MAXRESULTLINESPONE];
1.330 brouard 1488: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
1.318 brouard 1489: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */
1.332 ! brouard 1490: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
! 1491: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.318 brouard 1492: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For dummy variable , variable # (output) */
1.332 ! brouard 1493: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1494: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 ! brouard 1495: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1496:
1497: /* 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
1498: # States 1=Coresidence, 2 Living alone, 3 Institution
1499: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1500: */
1.234 brouard 1501: /* 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 1502: 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 */
1503: 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 */
1504: 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 */
1505: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1506: 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 */
1507: 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 1508: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1509: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1510: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1511: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1512: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1513: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1514: 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 */
1515: 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 */
1516:
1.230 brouard 1517: int *Tvarsel; /**< Selected covariates for output */
1518: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1519: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1520: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1521: 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 1522: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1523: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1524: int *Tage;
1.227 brouard 1525: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1526: 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 1527: 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*/
1528: 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 1529: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1530: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1531: int **Tvard;
1.330 brouard 1532: int **Tvardk;
1.227 brouard 1533: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1534: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1535: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1536: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1537: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1538: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1539: double *lsurv, *lpop, *tpop;
1540:
1.231 brouard 1541: #define FD 1; /* Fixed dummy covariate */
1542: #define FQ 2; /* Fixed quantitative covariate */
1543: #define FP 3; /* Fixed product covariate */
1544: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1545: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1546: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1547: #define VD 10; /* Varying dummy covariate */
1548: #define VQ 11; /* Varying quantitative covariate */
1549: #define VP 12; /* Varying product covariate */
1550: #define VPDD 13; /* Varying product dummy*dummy covariate */
1551: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1552: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1553: #define APFD 16; /* Age product * fixed dummy covariate */
1554: #define APFQ 17; /* Age product * fixed quantitative covariate */
1555: #define APVD 18; /* Age product * varying dummy covariate */
1556: #define APVQ 19; /* Age product * varying quantitative covariate */
1557:
1558: #define FTYPE 1; /* Fixed covariate */
1559: #define VTYPE 2; /* Varying covariate (loop in wave) */
1560: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1561:
1562: struct kmodel{
1563: int maintype; /* main type */
1564: int subtype; /* subtype */
1565: };
1566: struct kmodel modell[NCOVMAX];
1567:
1.143 brouard 1568: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1569: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1570:
1571: /**************** split *************************/
1572: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1573: {
1574: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1575: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1576: */
1577: char *ss; /* pointer */
1.186 brouard 1578: int l1=0, l2=0; /* length counters */
1.126 brouard 1579:
1580: l1 = strlen(path ); /* length of path */
1581: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1582: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1583: if ( ss == NULL ) { /* no directory, so determine current directory */
1584: strcpy( name, path ); /* we got the fullname name because no directory */
1585: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1586: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1587: /* get current working directory */
1588: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1589: #ifdef WIN32
1590: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1591: #else
1592: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1593: #endif
1.126 brouard 1594: return( GLOCK_ERROR_GETCWD );
1595: }
1596: /* got dirc from getcwd*/
1597: printf(" DIRC = %s \n",dirc);
1.205 brouard 1598: } else { /* strip directory from path */
1.126 brouard 1599: ss++; /* after this, the filename */
1600: l2 = strlen( ss ); /* length of filename */
1601: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1602: strcpy( name, ss ); /* save file name */
1603: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1604: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1605: printf(" DIRC2 = %s \n",dirc);
1606: }
1607: /* We add a separator at the end of dirc if not exists */
1608: l1 = strlen( dirc ); /* length of directory */
1609: if( dirc[l1-1] != DIRSEPARATOR ){
1610: dirc[l1] = DIRSEPARATOR;
1611: dirc[l1+1] = 0;
1612: printf(" DIRC3 = %s \n",dirc);
1613: }
1614: ss = strrchr( name, '.' ); /* find last / */
1615: if (ss >0){
1616: ss++;
1617: strcpy(ext,ss); /* save extension */
1618: l1= strlen( name);
1619: l2= strlen(ss)+1;
1620: strncpy( finame, name, l1-l2);
1621: finame[l1-l2]= 0;
1622: }
1623:
1624: return( 0 ); /* we're done */
1625: }
1626:
1627:
1628: /******************************************/
1629:
1630: void replace_back_to_slash(char *s, char*t)
1631: {
1632: int i;
1633: int lg=0;
1634: i=0;
1635: lg=strlen(t);
1636: for(i=0; i<= lg; i++) {
1637: (s[i] = t[i]);
1638: if (t[i]== '\\') s[i]='/';
1639: }
1640: }
1641:
1.132 brouard 1642: char *trimbb(char *out, char *in)
1.137 brouard 1643: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1644: char *s;
1645: s=out;
1646: while (*in != '\0'){
1.137 brouard 1647: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1648: in++;
1649: }
1650: *out++ = *in++;
1651: }
1652: *out='\0';
1653: return s;
1654: }
1655:
1.187 brouard 1656: /* char *substrchaine(char *out, char *in, char *chain) */
1657: /* { */
1658: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1659: /* char *s, *t; */
1660: /* t=in;s=out; */
1661: /* while ((*in != *chain) && (*in != '\0')){ */
1662: /* *out++ = *in++; */
1663: /* } */
1664:
1665: /* /\* *in matches *chain *\/ */
1666: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1667: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1668: /* } */
1669: /* in--; chain--; */
1670: /* while ( (*in != '\0')){ */
1671: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1672: /* *out++ = *in++; */
1673: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1674: /* } */
1675: /* *out='\0'; */
1676: /* out=s; */
1677: /* return out; */
1678: /* } */
1679: char *substrchaine(char *out, char *in, char *chain)
1680: {
1681: /* Substract chain 'chain' from 'in', return and output 'out' */
1682: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1683:
1684: char *strloc;
1685:
1686: strcpy (out, in);
1687: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1688: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1689: if(strloc != NULL){
1690: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1691: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1692: /* strcpy (strloc, strloc +strlen(chain));*/
1693: }
1694: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1695: return out;
1696: }
1697:
1698:
1.145 brouard 1699: char *cutl(char *blocc, char *alocc, char *in, char occ)
1700: {
1.187 brouard 1701: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1702: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1703: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1704: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1705: */
1.160 brouard 1706: char *s, *t;
1.145 brouard 1707: t=in;s=in;
1708: while ((*in != occ) && (*in != '\0')){
1709: *alocc++ = *in++;
1710: }
1711: if( *in == occ){
1712: *(alocc)='\0';
1713: s=++in;
1714: }
1715:
1716: if (s == t) {/* occ not found */
1717: *(alocc-(in-s))='\0';
1718: in=s;
1719: }
1720: while ( *in != '\0'){
1721: *blocc++ = *in++;
1722: }
1723:
1724: *blocc='\0';
1725: return t;
1726: }
1.137 brouard 1727: char *cutv(char *blocc, char *alocc, char *in, char occ)
1728: {
1.187 brouard 1729: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1730: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1731: gives blocc="abcdef2ghi" and alocc="j".
1732: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1733: */
1734: char *s, *t;
1735: t=in;s=in;
1736: while (*in != '\0'){
1737: while( *in == occ){
1738: *blocc++ = *in++;
1739: s=in;
1740: }
1741: *blocc++ = *in++;
1742: }
1743: if (s == t) /* occ not found */
1744: *(blocc-(in-s))='\0';
1745: else
1746: *(blocc-(in-s)-1)='\0';
1747: in=s;
1748: while ( *in != '\0'){
1749: *alocc++ = *in++;
1750: }
1751:
1752: *alocc='\0';
1753: return s;
1754: }
1755:
1.126 brouard 1756: int nbocc(char *s, char occ)
1757: {
1758: int i,j=0;
1759: int lg=20;
1760: i=0;
1761: lg=strlen(s);
1762: for(i=0; i<= lg; i++) {
1.234 brouard 1763: if (s[i] == occ ) j++;
1.126 brouard 1764: }
1765: return j;
1766: }
1767:
1.137 brouard 1768: /* void cutv(char *u,char *v, char*t, char occ) */
1769: /* { */
1770: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1771: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1772: /* gives u="abcdef2ghi" and v="j" *\/ */
1773: /* int i,lg,j,p=0; */
1774: /* i=0; */
1775: /* lg=strlen(t); */
1776: /* for(j=0; j<=lg-1; j++) { */
1777: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1778: /* } */
1.126 brouard 1779:
1.137 brouard 1780: /* for(j=0; j<p; j++) { */
1781: /* (u[j] = t[j]); */
1782: /* } */
1783: /* u[p]='\0'; */
1.126 brouard 1784:
1.137 brouard 1785: /* for(j=0; j<= lg; j++) { */
1786: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1787: /* } */
1788: /* } */
1.126 brouard 1789:
1.160 brouard 1790: #ifdef _WIN32
1791: char * strsep(char **pp, const char *delim)
1792: {
1793: char *p, *q;
1794:
1795: if ((p = *pp) == NULL)
1796: return 0;
1797: if ((q = strpbrk (p, delim)) != NULL)
1798: {
1799: *pp = q + 1;
1800: *q = '\0';
1801: }
1802: else
1803: *pp = 0;
1804: return p;
1805: }
1806: #endif
1807:
1.126 brouard 1808: /********************** nrerror ********************/
1809:
1810: void nrerror(char error_text[])
1811: {
1812: fprintf(stderr,"ERREUR ...\n");
1813: fprintf(stderr,"%s\n",error_text);
1814: exit(EXIT_FAILURE);
1815: }
1816: /*********************** vector *******************/
1817: double *vector(int nl, int nh)
1818: {
1819: double *v;
1820: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1821: if (!v) nrerror("allocation failure in vector");
1822: return v-nl+NR_END;
1823: }
1824:
1825: /************************ free vector ******************/
1826: void free_vector(double*v, int nl, int nh)
1827: {
1828: free((FREE_ARG)(v+nl-NR_END));
1829: }
1830:
1831: /************************ivector *******************************/
1832: int *ivector(long nl,long nh)
1833: {
1834: int *v;
1835: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1836: if (!v) nrerror("allocation failure in ivector");
1837: return v-nl+NR_END;
1838: }
1839:
1840: /******************free ivector **************************/
1841: void free_ivector(int *v, long nl, long nh)
1842: {
1843: free((FREE_ARG)(v+nl-NR_END));
1844: }
1845:
1846: /************************lvector *******************************/
1847: long *lvector(long nl,long nh)
1848: {
1849: long *v;
1850: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1851: if (!v) nrerror("allocation failure in ivector");
1852: return v-nl+NR_END;
1853: }
1854:
1855: /******************free lvector **************************/
1856: void free_lvector(long *v, long nl, long nh)
1857: {
1858: free((FREE_ARG)(v+nl-NR_END));
1859: }
1860:
1861: /******************* imatrix *******************************/
1862: int **imatrix(long nrl, long nrh, long ncl, long nch)
1863: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1864: {
1865: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1866: int **m;
1867:
1868: /* allocate pointers to rows */
1869: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1870: if (!m) nrerror("allocation failure 1 in matrix()");
1871: m += NR_END;
1872: m -= nrl;
1873:
1874:
1875: /* allocate rows and set pointers to them */
1876: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1877: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1878: m[nrl] += NR_END;
1879: m[nrl] -= ncl;
1880:
1881: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1882:
1883: /* return pointer to array of pointers to rows */
1884: return m;
1885: }
1886:
1887: /****************** free_imatrix *************************/
1888: void free_imatrix(m,nrl,nrh,ncl,nch)
1889: int **m;
1890: long nch,ncl,nrh,nrl;
1891: /* free an int matrix allocated by imatrix() */
1892: {
1893: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1894: free((FREE_ARG) (m+nrl-NR_END));
1895: }
1896:
1897: /******************* matrix *******************************/
1898: double **matrix(long nrl, long nrh, long ncl, long nch)
1899: {
1900: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1901: double **m;
1902:
1903: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1904: if (!m) nrerror("allocation failure 1 in matrix()");
1905: m += NR_END;
1906: m -= nrl;
1907:
1908: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1909: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1910: m[nrl] += NR_END;
1911: m[nrl] -= ncl;
1912:
1913: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1914: return m;
1.145 brouard 1915: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1916: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1917: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1918: */
1919: }
1920:
1921: /*************************free matrix ************************/
1922: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1923: {
1924: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1925: free((FREE_ARG)(m+nrl-NR_END));
1926: }
1927:
1928: /******************* ma3x *******************************/
1929: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1930: {
1931: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1932: double ***m;
1933:
1934: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1935: if (!m) nrerror("allocation failure 1 in matrix()");
1936: m += NR_END;
1937: m -= nrl;
1938:
1939: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1940: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1941: m[nrl] += NR_END;
1942: m[nrl] -= ncl;
1943:
1944: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1945:
1946: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1947: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1948: m[nrl][ncl] += NR_END;
1949: m[nrl][ncl] -= nll;
1950: for (j=ncl+1; j<=nch; j++)
1951: m[nrl][j]=m[nrl][j-1]+nlay;
1952:
1953: for (i=nrl+1; i<=nrh; i++) {
1954: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1955: for (j=ncl+1; j<=nch; j++)
1956: m[i][j]=m[i][j-1]+nlay;
1957: }
1958: return m;
1959: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1960: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1961: */
1962: }
1963:
1964: /*************************free ma3x ************************/
1965: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1966: {
1967: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1968: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1969: free((FREE_ARG)(m+nrl-NR_END));
1970: }
1971:
1972: /*************** function subdirf ***********/
1973: char *subdirf(char fileres[])
1974: {
1975: /* Caution optionfilefiname is hidden */
1976: strcpy(tmpout,optionfilefiname);
1977: strcat(tmpout,"/"); /* Add to the right */
1978: strcat(tmpout,fileres);
1979: return tmpout;
1980: }
1981:
1982: /*************** function subdirf2 ***********/
1983: char *subdirf2(char fileres[], char *preop)
1984: {
1.314 brouard 1985: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
1986: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 1987: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 1988: /* Caution optionfilefiname is hidden */
1989: strcpy(tmpout,optionfilefiname);
1990: strcat(tmpout,"/");
1991: strcat(tmpout,preop);
1992: strcat(tmpout,fileres);
1993: return tmpout;
1994: }
1995:
1996: /*************** function subdirf3 ***********/
1997: char *subdirf3(char fileres[], char *preop, char *preop2)
1998: {
1999:
2000: /* Caution optionfilefiname is hidden */
2001: strcpy(tmpout,optionfilefiname);
2002: strcat(tmpout,"/");
2003: strcat(tmpout,preop);
2004: strcat(tmpout,preop2);
2005: strcat(tmpout,fileres);
2006: return tmpout;
2007: }
1.213 brouard 2008:
2009: /*************** function subdirfext ***********/
2010: char *subdirfext(char fileres[], char *preop, char *postop)
2011: {
2012:
2013: strcpy(tmpout,preop);
2014: strcat(tmpout,fileres);
2015: strcat(tmpout,postop);
2016: return tmpout;
2017: }
1.126 brouard 2018:
1.213 brouard 2019: /*************** function subdirfext3 ***********/
2020: char *subdirfext3(char fileres[], char *preop, char *postop)
2021: {
2022:
2023: /* Caution optionfilefiname is hidden */
2024: strcpy(tmpout,optionfilefiname);
2025: strcat(tmpout,"/");
2026: strcat(tmpout,preop);
2027: strcat(tmpout,fileres);
2028: strcat(tmpout,postop);
2029: return tmpout;
2030: }
2031:
1.162 brouard 2032: char *asc_diff_time(long time_sec, char ascdiff[])
2033: {
2034: long sec_left, days, hours, minutes;
2035: days = (time_sec) / (60*60*24);
2036: sec_left = (time_sec) % (60*60*24);
2037: hours = (sec_left) / (60*60) ;
2038: sec_left = (sec_left) %(60*60);
2039: minutes = (sec_left) /60;
2040: sec_left = (sec_left) % (60);
2041: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2042: return ascdiff;
2043: }
2044:
1.126 brouard 2045: /***************** f1dim *************************/
2046: extern int ncom;
2047: extern double *pcom,*xicom;
2048: extern double (*nrfunc)(double []);
2049:
2050: double f1dim(double x)
2051: {
2052: int j;
2053: double f;
2054: double *xt;
2055:
2056: xt=vector(1,ncom);
2057: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2058: f=(*nrfunc)(xt);
2059: free_vector(xt,1,ncom);
2060: return f;
2061: }
2062:
2063: /*****************brent *************************/
2064: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2065: {
2066: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2067: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2068: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2069: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2070: * returned function value.
2071: */
1.126 brouard 2072: int iter;
2073: double a,b,d,etemp;
1.159 brouard 2074: double fu=0,fv,fw,fx;
1.164 brouard 2075: double ftemp=0.;
1.126 brouard 2076: double p,q,r,tol1,tol2,u,v,w,x,xm;
2077: double e=0.0;
2078:
2079: a=(ax < cx ? ax : cx);
2080: b=(ax > cx ? ax : cx);
2081: x=w=v=bx;
2082: fw=fv=fx=(*f)(x);
2083: for (iter=1;iter<=ITMAX;iter++) {
2084: xm=0.5*(a+b);
2085: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2086: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2087: printf(".");fflush(stdout);
2088: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2089: #ifdef DEBUGBRENT
1.126 brouard 2090: 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);
2091: 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);
2092: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2093: #endif
2094: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2095: *xmin=x;
2096: return fx;
2097: }
2098: ftemp=fu;
2099: if (fabs(e) > tol1) {
2100: r=(x-w)*(fx-fv);
2101: q=(x-v)*(fx-fw);
2102: p=(x-v)*q-(x-w)*r;
2103: q=2.0*(q-r);
2104: if (q > 0.0) p = -p;
2105: q=fabs(q);
2106: etemp=e;
2107: e=d;
2108: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2109: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2110: else {
1.224 brouard 2111: d=p/q;
2112: u=x+d;
2113: if (u-a < tol2 || b-u < tol2)
2114: d=SIGN(tol1,xm-x);
1.126 brouard 2115: }
2116: } else {
2117: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2118: }
2119: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2120: fu=(*f)(u);
2121: if (fu <= fx) {
2122: if (u >= x) a=x; else b=x;
2123: SHFT(v,w,x,u)
1.183 brouard 2124: SHFT(fv,fw,fx,fu)
2125: } else {
2126: if (u < x) a=u; else b=u;
2127: if (fu <= fw || w == x) {
1.224 brouard 2128: v=w;
2129: w=u;
2130: fv=fw;
2131: fw=fu;
1.183 brouard 2132: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2133: v=u;
2134: fv=fu;
1.183 brouard 2135: }
2136: }
1.126 brouard 2137: }
2138: nrerror("Too many iterations in brent");
2139: *xmin=x;
2140: return fx;
2141: }
2142:
2143: /****************** mnbrak ***********************/
2144:
2145: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2146: double (*func)(double))
1.183 brouard 2147: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2148: the downhill direction (defined by the function as evaluated at the initial points) and returns
2149: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2150: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2151: */
1.126 brouard 2152: double ulim,u,r,q, dum;
2153: double fu;
1.187 brouard 2154:
2155: double scale=10.;
2156: int iterscale=0;
2157:
2158: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2159: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2160:
2161:
2162: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2163: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2164: /* *bx = *ax - (*ax - *bx)/scale; */
2165: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2166: /* } */
2167:
1.126 brouard 2168: if (*fb > *fa) {
2169: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2170: SHFT(dum,*fb,*fa,dum)
2171: }
1.126 brouard 2172: *cx=(*bx)+GOLD*(*bx-*ax);
2173: *fc=(*func)(*cx);
1.183 brouard 2174: #ifdef DEBUG
1.224 brouard 2175: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2176: 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 2177: #endif
1.224 brouard 2178: 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 2179: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2180: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2181: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2182: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2183: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2184: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2185: fu=(*func)(u);
1.163 brouard 2186: #ifdef DEBUG
2187: /* f(x)=A(x-u)**2+f(u) */
2188: double A, fparabu;
2189: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2190: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2191: 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);
2192: 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 2193: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2194: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2195: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2196: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2197: #endif
1.184 brouard 2198: #ifdef MNBRAKORIGINAL
1.183 brouard 2199: #else
1.191 brouard 2200: /* if (fu > *fc) { */
2201: /* #ifdef DEBUG */
2202: /* printf("mnbrak4 fu > fc \n"); */
2203: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2204: /* #endif */
2205: /* /\* 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 *\\/ *\/ */
2206: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2207: /* dum=u; /\* Shifting c and u *\/ */
2208: /* u = *cx; */
2209: /* *cx = dum; */
2210: /* dum = fu; */
2211: /* fu = *fc; */
2212: /* *fc =dum; */
2213: /* } else { /\* end *\/ */
2214: /* #ifdef DEBUG */
2215: /* printf("mnbrak3 fu < fc \n"); */
2216: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2217: /* #endif */
2218: /* dum=u; /\* Shifting c and u *\/ */
2219: /* u = *cx; */
2220: /* *cx = dum; */
2221: /* dum = fu; */
2222: /* fu = *fc; */
2223: /* *fc =dum; */
2224: /* } */
1.224 brouard 2225: #ifdef DEBUGMNBRAK
2226: double A, fparabu;
2227: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2228: fparabu= *fa - A*(*ax-u)*(*ax-u);
2229: 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);
2230: 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 2231: #endif
1.191 brouard 2232: dum=u; /* Shifting c and u */
2233: u = *cx;
2234: *cx = dum;
2235: dum = fu;
2236: fu = *fc;
2237: *fc =dum;
1.183 brouard 2238: #endif
1.162 brouard 2239: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2240: #ifdef DEBUG
1.224 brouard 2241: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2242: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2243: #endif
1.126 brouard 2244: fu=(*func)(u);
2245: if (fu < *fc) {
1.183 brouard 2246: #ifdef DEBUG
1.224 brouard 2247: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2248: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2249: #endif
2250: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2251: SHFT(*fb,*fc,fu,(*func)(u))
2252: #ifdef DEBUG
2253: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2254: #endif
2255: }
1.162 brouard 2256: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2257: #ifdef DEBUG
1.224 brouard 2258: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2259: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2260: #endif
1.126 brouard 2261: u=ulim;
2262: fu=(*func)(u);
1.183 brouard 2263: } else { /* u could be left to b (if r > q parabola has a maximum) */
2264: #ifdef DEBUG
1.224 brouard 2265: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2266: 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 2267: #endif
1.126 brouard 2268: u=(*cx)+GOLD*(*cx-*bx);
2269: fu=(*func)(u);
1.224 brouard 2270: #ifdef DEBUG
2271: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2272: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2273: #endif
1.183 brouard 2274: } /* end tests */
1.126 brouard 2275: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2276: SHFT(*fa,*fb,*fc,fu)
2277: #ifdef DEBUG
1.224 brouard 2278: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2279: 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 2280: #endif
2281: } /* 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 2282: }
2283:
2284: /*************** linmin ************************/
1.162 brouard 2285: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2286: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2287: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2288: the value of func at the returned location p . This is actually all accomplished by calling the
2289: routines mnbrak and brent .*/
1.126 brouard 2290: int ncom;
2291: double *pcom,*xicom;
2292: double (*nrfunc)(double []);
2293:
1.224 brouard 2294: #ifdef LINMINORIGINAL
1.126 brouard 2295: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2296: #else
2297: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2298: #endif
1.126 brouard 2299: {
2300: double brent(double ax, double bx, double cx,
2301: double (*f)(double), double tol, double *xmin);
2302: double f1dim(double x);
2303: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2304: double *fc, double (*func)(double));
2305: int j;
2306: double xx,xmin,bx,ax;
2307: double fx,fb,fa;
1.187 brouard 2308:
1.203 brouard 2309: #ifdef LINMINORIGINAL
2310: #else
2311: double scale=10., axs, xxs; /* Scale added for infinity */
2312: #endif
2313:
1.126 brouard 2314: ncom=n;
2315: pcom=vector(1,n);
2316: xicom=vector(1,n);
2317: nrfunc=func;
2318: for (j=1;j<=n;j++) {
2319: pcom[j]=p[j];
1.202 brouard 2320: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2321: }
1.187 brouard 2322:
1.203 brouard 2323: #ifdef LINMINORIGINAL
2324: xx=1.;
2325: #else
2326: axs=0.0;
2327: xxs=1.;
2328: do{
2329: xx= xxs;
2330: #endif
1.187 brouard 2331: ax=0.;
2332: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2333: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2334: /* 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)) */
2335: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2336: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2337: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2338: /* 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 2339: #ifdef LINMINORIGINAL
2340: #else
2341: if (fx != fx){
1.224 brouard 2342: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2343: printf("|");
2344: fprintf(ficlog,"|");
1.203 brouard 2345: #ifdef DEBUGLINMIN
1.224 brouard 2346: 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 2347: #endif
2348: }
1.224 brouard 2349: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2350: #endif
2351:
1.191 brouard 2352: #ifdef DEBUGLINMIN
2353: 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 2354: 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 2355: #endif
1.224 brouard 2356: #ifdef LINMINORIGINAL
2357: #else
1.317 brouard 2358: if(fb == fx){ /* Flat function in the direction */
2359: xmin=xx;
1.224 brouard 2360: *flat=1;
1.317 brouard 2361: }else{
1.224 brouard 2362: *flat=0;
2363: #endif
2364: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2365: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2366: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2367: /* fmin = f(p[j] + xmin * xi[j]) */
2368: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2369: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2370: #ifdef DEBUG
1.224 brouard 2371: 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);
2372: 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);
2373: #endif
2374: #ifdef LINMINORIGINAL
2375: #else
2376: }
1.126 brouard 2377: #endif
1.191 brouard 2378: #ifdef DEBUGLINMIN
2379: printf("linmin end ");
1.202 brouard 2380: fprintf(ficlog,"linmin end ");
1.191 brouard 2381: #endif
1.126 brouard 2382: for (j=1;j<=n;j++) {
1.203 brouard 2383: #ifdef LINMINORIGINAL
2384: xi[j] *= xmin;
2385: #else
2386: #ifdef DEBUGLINMIN
2387: if(xxs <1.0)
2388: printf(" before xi[%d]=%12.8f", j,xi[j]);
2389: #endif
2390: 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) */
2391: #ifdef DEBUGLINMIN
2392: if(xxs <1.0)
2393: 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 );
2394: #endif
2395: #endif
1.187 brouard 2396: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2397: }
1.191 brouard 2398: #ifdef DEBUGLINMIN
1.203 brouard 2399: printf("\n");
1.191 brouard 2400: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2401: 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 2402: for (j=1;j<=n;j++) {
1.202 brouard 2403: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2404: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2405: if(j % ncovmodel == 0){
1.191 brouard 2406: printf("\n");
1.202 brouard 2407: fprintf(ficlog,"\n");
2408: }
1.191 brouard 2409: }
1.203 brouard 2410: #else
1.191 brouard 2411: #endif
1.126 brouard 2412: free_vector(xicom,1,n);
2413: free_vector(pcom,1,n);
2414: }
2415:
2416:
2417: /*************** powell ************************/
1.162 brouard 2418: /*
1.317 brouard 2419: Minimization of a function func of n variables. Input consists in an initial starting point
2420: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2421: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2422: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2423: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2424: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2425: */
1.224 brouard 2426: #ifdef LINMINORIGINAL
2427: #else
2428: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2429: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2430: #endif
1.126 brouard 2431: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2432: double (*func)(double []))
2433: {
1.224 brouard 2434: #ifdef LINMINORIGINAL
2435: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2436: double (*func)(double []));
1.224 brouard 2437: #else
1.241 brouard 2438: void linmin(double p[], double xi[], int n, double *fret,
2439: double (*func)(double []),int *flat);
1.224 brouard 2440: #endif
1.239 brouard 2441: int i,ibig,j,jk,k;
1.126 brouard 2442: double del,t,*pt,*ptt,*xit;
1.181 brouard 2443: double directest;
1.126 brouard 2444: double fp,fptt;
2445: double *xits;
2446: int niterf, itmp;
2447:
2448: pt=vector(1,n);
2449: ptt=vector(1,n);
2450: xit=vector(1,n);
2451: xits=vector(1,n);
2452: *fret=(*func)(p);
2453: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2454: rcurr_time = time(NULL);
1.126 brouard 2455: for (*iter=1;;++(*iter)) {
2456: ibig=0;
2457: del=0.0;
1.157 brouard 2458: rlast_time=rcurr_time;
2459: /* (void) gettimeofday(&curr_time,&tzp); */
2460: rcurr_time = time(NULL);
2461: curr_time = *localtime(&rcurr_time);
1.324 brouard 2462: 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);
2463: 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);
1.157 brouard 2464: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.324 brouard 2465: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2466: for (i=1;i<=n;i++) {
1.126 brouard 2467: fprintf(ficrespow," %.12lf", p[i]);
2468: }
1.239 brouard 2469: fprintf(ficrespow,"\n");fflush(ficrespow);
2470: printf("\n#model= 1 + age ");
2471: fprintf(ficlog,"\n#model= 1 + age ");
2472: if(nagesqr==1){
1.241 brouard 2473: printf(" + age*age ");
2474: fprintf(ficlog," + age*age ");
1.239 brouard 2475: }
2476: for(j=1;j <=ncovmodel-2;j++){
2477: if(Typevar[j]==0) {
2478: printf(" + V%d ",Tvar[j]);
2479: fprintf(ficlog," + V%d ",Tvar[j]);
2480: }else if(Typevar[j]==1) {
2481: printf(" + V%d*age ",Tvar[j]);
2482: fprintf(ficlog," + V%d*age ",Tvar[j]);
2483: }else if(Typevar[j]==2) {
2484: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2485: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2486: }
2487: }
1.126 brouard 2488: printf("\n");
1.239 brouard 2489: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2490: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2491: fprintf(ficlog,"\n");
1.239 brouard 2492: for(i=1,jk=1; i <=nlstate; i++){
2493: for(k=1; k <=(nlstate+ndeath); k++){
2494: if (k != i) {
2495: printf("%d%d ",i,k);
2496: fprintf(ficlog,"%d%d ",i,k);
2497: for(j=1; j <=ncovmodel; j++){
2498: printf("%12.7f ",p[jk]);
2499: fprintf(ficlog,"%12.7f ",p[jk]);
2500: jk++;
2501: }
2502: printf("\n");
2503: fprintf(ficlog,"\n");
2504: }
2505: }
2506: }
1.241 brouard 2507: if(*iter <=3 && *iter >1){
1.157 brouard 2508: tml = *localtime(&rcurr_time);
2509: strcpy(strcurr,asctime(&tml));
2510: rforecast_time=rcurr_time;
1.126 brouard 2511: itmp = strlen(strcurr);
2512: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2513: strcurr[itmp-1]='\0';
1.162 brouard 2514: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2515: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2516: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2517: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2518: forecast_time = *localtime(&rforecast_time);
2519: strcpy(strfor,asctime(&forecast_time));
2520: itmp = strlen(strfor);
2521: if(strfor[itmp-1]=='\n')
2522: strfor[itmp-1]='\0';
2523: printf(" - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
2524: fprintf(ficlog," - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
1.126 brouard 2525: }
2526: }
1.187 brouard 2527: for (i=1;i<=n;i++) { /* For each direction i */
2528: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2529: fptt=(*fret);
2530: #ifdef DEBUG
1.203 brouard 2531: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2532: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2533: #endif
1.203 brouard 2534: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2535: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2536: #ifdef LINMINORIGINAL
1.188 brouard 2537: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2538: #else
2539: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2540: flatdir[i]=flat; /* Function is vanishing in that direction i */
2541: #endif
2542: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2543: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2544: /* because that direction will be replaced unless the gain del is small */
2545: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2546: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2547: /* with the new direction. */
2548: del=fabs(fptt-(*fret));
2549: ibig=i;
1.126 brouard 2550: }
2551: #ifdef DEBUG
2552: printf("%d %.12e",i,(*fret));
2553: fprintf(ficlog,"%d %.12e",i,(*fret));
2554: for (j=1;j<=n;j++) {
1.224 brouard 2555: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2556: printf(" x(%d)=%.12e",j,xit[j]);
2557: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2558: }
2559: for(j=1;j<=n;j++) {
1.225 brouard 2560: printf(" p(%d)=%.12e",j,p[j]);
2561: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2562: }
2563: printf("\n");
2564: fprintf(ficlog,"\n");
2565: #endif
1.187 brouard 2566: } /* end loop on each direction i */
2567: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2568: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2569: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2570: for(j=1;j<=n;j++) {
2571: if(flatdir[j] >0){
2572: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2573: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2574: }
1.319 brouard 2575: /* printf("\n"); */
2576: /* fprintf(ficlog,"\n"); */
2577: }
1.243 brouard 2578: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2579: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2580: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2581: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2582: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2583: /* decreased of more than 3.84 */
2584: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2585: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2586: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2587:
1.188 brouard 2588: /* Starting the program with initial values given by a former maximization will simply change */
2589: /* the scales of the directions and the directions, because the are reset to canonical directions */
2590: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2591: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2592: #ifdef DEBUG
2593: int k[2],l;
2594: k[0]=1;
2595: k[1]=-1;
2596: printf("Max: %.12e",(*func)(p));
2597: fprintf(ficlog,"Max: %.12e",(*func)(p));
2598: for (j=1;j<=n;j++) {
2599: printf(" %.12e",p[j]);
2600: fprintf(ficlog," %.12e",p[j]);
2601: }
2602: printf("\n");
2603: fprintf(ficlog,"\n");
2604: for(l=0;l<=1;l++) {
2605: for (j=1;j<=n;j++) {
2606: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2607: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2608: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2609: }
2610: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2611: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2612: }
2613: #endif
2614:
2615: free_vector(xit,1,n);
2616: free_vector(xits,1,n);
2617: free_vector(ptt,1,n);
2618: free_vector(pt,1,n);
2619: return;
1.192 brouard 2620: } /* enough precision */
1.240 brouard 2621: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2622: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2623: ptt[j]=2.0*p[j]-pt[j];
2624: xit[j]=p[j]-pt[j];
2625: pt[j]=p[j];
2626: }
1.181 brouard 2627: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2628: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2629: if (*iter <=4) {
1.225 brouard 2630: #else
2631: #endif
1.224 brouard 2632: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2633: #else
1.161 brouard 2634: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2635: #endif
1.162 brouard 2636: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2637: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2638: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2639: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2640: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2641: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2642: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2643: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2644: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2645: /* Even if f3 <f1, directest can be negative and t >0 */
2646: /* mu² and del² are equal when f3=f1 */
2647: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2648: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2649: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2650: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2651: #ifdef NRCORIGINAL
2652: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2653: #else
2654: 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 2655: t= t- del*SQR(fp-fptt);
1.183 brouard 2656: #endif
1.202 brouard 2657: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2658: #ifdef DEBUG
1.181 brouard 2659: 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);
2660: 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 2661: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2662: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2663: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2664: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2665: 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);
2666: 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);
2667: #endif
1.183 brouard 2668: #ifdef POWELLORIGINAL
2669: if (t < 0.0) { /* Then we use it for new direction */
2670: #else
1.182 brouard 2671: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2672: 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 2673: 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 2674: 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 2675: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2676: }
1.181 brouard 2677: if (directest < 0.0) { /* Then we use it for new direction */
2678: #endif
1.191 brouard 2679: #ifdef DEBUGLINMIN
1.234 brouard 2680: printf("Before linmin in direction P%d-P0\n",n);
2681: for (j=1;j<=n;j++) {
2682: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2683: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2684: if(j % ncovmodel == 0){
2685: printf("\n");
2686: fprintf(ficlog,"\n");
2687: }
2688: }
1.224 brouard 2689: #endif
2690: #ifdef LINMINORIGINAL
1.234 brouard 2691: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2692: #else
1.234 brouard 2693: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2694: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2695: #endif
1.234 brouard 2696:
1.191 brouard 2697: #ifdef DEBUGLINMIN
1.234 brouard 2698: for (j=1;j<=n;j++) {
2699: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2700: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2701: if(j % ncovmodel == 0){
2702: printf("\n");
2703: fprintf(ficlog,"\n");
2704: }
2705: }
1.224 brouard 2706: #endif
1.234 brouard 2707: for (j=1;j<=n;j++) {
2708: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2709: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2710: }
1.224 brouard 2711: #ifdef LINMINORIGINAL
2712: #else
1.234 brouard 2713: for (j=1, flatd=0;j<=n;j++) {
2714: if(flatdir[j]>0)
2715: flatd++;
2716: }
2717: if(flatd >0){
1.255 brouard 2718: printf("%d flat directions: ",flatd);
2719: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2720: for (j=1;j<=n;j++) {
2721: if(flatdir[j]>0){
2722: printf("%d ",j);
2723: fprintf(ficlog,"%d ",j);
2724: }
2725: }
2726: printf("\n");
2727: fprintf(ficlog,"\n");
1.319 brouard 2728: #ifdef FLATSUP
2729: free_vector(xit,1,n);
2730: free_vector(xits,1,n);
2731: free_vector(ptt,1,n);
2732: free_vector(pt,1,n);
2733: return;
2734: #endif
1.234 brouard 2735: }
1.191 brouard 2736: #endif
1.234 brouard 2737: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2738: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2739:
1.126 brouard 2740: #ifdef DEBUG
1.234 brouard 2741: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2742: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2743: for(j=1;j<=n;j++){
2744: printf(" %lf",xit[j]);
2745: fprintf(ficlog," %lf",xit[j]);
2746: }
2747: printf("\n");
2748: fprintf(ficlog,"\n");
1.126 brouard 2749: #endif
1.192 brouard 2750: } /* end of t or directest negative */
1.224 brouard 2751: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2752: #else
1.234 brouard 2753: } /* end if (fptt < fp) */
1.192 brouard 2754: #endif
1.225 brouard 2755: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2756: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2757: #else
1.224 brouard 2758: #endif
1.234 brouard 2759: } /* loop iteration */
1.126 brouard 2760: }
1.234 brouard 2761:
1.126 brouard 2762: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2763:
1.235 brouard 2764: 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 2765: {
1.279 brouard 2766: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2767: * (and selected quantitative values in nres)
2768: * by left multiplying the unit
2769: * matrix by transitions matrix until convergence is reached with precision ftolpl
2770: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2771: * Wx is row vector: population in state 1, population in state 2, population dead
2772: * or prevalence in state 1, prevalence in state 2, 0
2773: * newm is the matrix after multiplications, its rows are identical at a factor.
2774: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2775: * Output is prlim.
2776: * Initial matrix pimij
2777: */
1.206 brouard 2778: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2779: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2780: /* 0, 0 , 1} */
2781: /*
2782: * and after some iteration: */
2783: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2784: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2785: /* 0, 0 , 1} */
2786: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2787: /* {0.51571254859325999, 0.4842874514067399, */
2788: /* 0.51326036147820708, 0.48673963852179264} */
2789: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2790:
1.332 ! brouard 2791: int i, ii,j,k, k1;
1.209 brouard 2792: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2793: /* double **matprod2(); */ /* test */
1.218 brouard 2794: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2795: double **newm;
1.209 brouard 2796: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2797: int ncvloop=0;
1.288 brouard 2798: int first=0;
1.169 brouard 2799:
1.209 brouard 2800: min=vector(1,nlstate);
2801: max=vector(1,nlstate);
2802: meandiff=vector(1,nlstate);
2803:
1.218 brouard 2804: /* Starting with matrix unity */
1.126 brouard 2805: for (ii=1;ii<=nlstate+ndeath;ii++)
2806: for (j=1;j<=nlstate+ndeath;j++){
2807: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2808: }
1.169 brouard 2809:
2810: cov[1]=1.;
2811:
2812: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2813: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2814: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2815: ncvloop++;
1.126 brouard 2816: newm=savm;
2817: /* Covariates have to be included here again */
1.138 brouard 2818: cov[2]=agefin;
1.319 brouard 2819: if(nagesqr==1){
2820: cov[3]= agefin*agefin;
2821: }
1.332 ! brouard 2822: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
! 2823: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
! 2824: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
! 2825: if(Typevar[k1]==1){ /* A product with age */
! 2826: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
! 2827: }else{
! 2828: cov[2+nagesqr+k1]=precov[nres][k1];
! 2829: }
! 2830: }/* End of loop on model equation */
! 2831:
! 2832: /* Start of old code (replaced by a loop on position in the model equation */
! 2833: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
! 2834: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
! 2835: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
! 2836: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
! 2837: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
! 2838: /* * k 1 2 3 4 5 6 7 8 */
! 2839: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
! 2840: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
! 2841: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
! 2842: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
! 2843: /* *nsd=3 (1) (2) (3) */
! 2844: /* *TvarsD[nsd] [1]=2 1 3 */
! 2845: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
! 2846: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
! 2847: /* *Tage[] [1]=1 [2]=2 [3]=3 */
! 2848: /* *Tvard[] [1][1]=1 [2][1]=1 */
! 2849: /* * [1][2]=3 [2][2]=2 */
! 2850: /* *Tprod[](=k) [1]=1 [2]=8 */
! 2851: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
! 2852: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
! 2853: /* *TvarsDpType */
! 2854: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
! 2855: /* * nsd=1 (1) (2) */
! 2856: /* *TvarsD[nsd] 3 2 */
! 2857: /* *TnsdVar (3)=1 (2)=2 */
! 2858: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
! 2859: /* *Tage[] [1]=2 [2]= 3 */
! 2860: /* *\/ */
! 2861: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
! 2862: /* /\* 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)); *\/ */
! 2863: /* } */
! 2864: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
! 2865: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
! 2866: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
! 2867: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
! 2868: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
! 2869: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
! 2870: /* /\* 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]); *\/ */
! 2871: /* } */
! 2872: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
! 2873: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
! 2874: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
! 2875: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
! 2876: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
! 2877: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
! 2878: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
! 2879: /* } */
! 2880: /* /\* 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]); *\/ */
! 2881: /* } */
! 2882: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
! 2883: /* /\* 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]); *\/ */
! 2884: /* if(Dummy[Tvard[k][1]]==0){ */
! 2885: /* if(Dummy[Tvard[k][2]]==0){ */
! 2886: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
! 2887: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
! 2888: /* }else{ */
! 2889: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
! 2890: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
! 2891: /* } */
! 2892: /* }else{ */
! 2893: /* if(Dummy[Tvard[k][2]]==0){ */
! 2894: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
! 2895: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
! 2896: /* }else{ */
! 2897: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
! 2898: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
! 2899: /* } */
! 2900: /* } */
! 2901: /* } /\* End product without age *\/ */
! 2902: /* ENd of old code */
1.138 brouard 2903: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2904: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2905: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2906: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2907: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 2908: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2909: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2910:
1.126 brouard 2911: savm=oldm;
2912: oldm=newm;
1.209 brouard 2913:
2914: for(j=1; j<=nlstate; j++){
2915: max[j]=0.;
2916: min[j]=1.;
2917: }
2918: for(i=1;i<=nlstate;i++){
2919: sumnew=0;
2920: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2921: for(j=1; j<=nlstate; j++){
2922: prlim[i][j]= newm[i][j]/(1-sumnew);
2923: max[j]=FMAX(max[j],prlim[i][j]);
2924: min[j]=FMIN(min[j],prlim[i][j]);
2925: }
2926: }
2927:
1.126 brouard 2928: maxmax=0.;
1.209 brouard 2929: for(j=1; j<=nlstate; j++){
2930: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2931: maxmax=FMAX(maxmax,meandiff[j]);
2932: /* 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 2933: } /* j loop */
1.203 brouard 2934: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2935: /* 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 2936: if(maxmax < ftolpl){
1.209 brouard 2937: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2938: free_vector(min,1,nlstate);
2939: free_vector(max,1,nlstate);
2940: free_vector(meandiff,1,nlstate);
1.126 brouard 2941: return prlim;
2942: }
1.288 brouard 2943: } /* agefin loop */
1.208 brouard 2944: /* After some age loop it doesn't converge */
1.288 brouard 2945: if(!first){
2946: first=1;
2947: 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 2948: 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);
2949: }else if (first >=1 && first <10){
2950: 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);
2951: first++;
2952: }else if (first ==10){
2953: 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);
2954: 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");
2955: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
2956: first++;
1.288 brouard 2957: }
2958:
1.209 brouard 2959: /* 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); */
2960: free_vector(min,1,nlstate);
2961: free_vector(max,1,nlstate);
2962: free_vector(meandiff,1,nlstate);
1.208 brouard 2963:
1.169 brouard 2964: return prlim; /* should not reach here */
1.126 brouard 2965: }
2966:
1.217 brouard 2967:
2968: /**** Back Prevalence limit (stable or period prevalence) ****************/
2969:
1.218 brouard 2970: /* 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) */
2971: /* 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 2972: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2973: {
1.264 brouard 2974: /* 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 2975: matrix by transitions matrix until convergence is reached with precision ftolpl */
2976: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2977: /* Wx is row vector: population in state 1, population in state 2, population dead */
2978: /* or prevalence in state 1, prevalence in state 2, 0 */
2979: /* newm is the matrix after multiplications, its rows are identical at a factor */
2980: /* Initial matrix pimij */
2981: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2982: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2983: /* 0, 0 , 1} */
2984: /*
2985: * and after some iteration: */
2986: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2987: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2988: /* 0, 0 , 1} */
2989: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2990: /* {0.51571254859325999, 0.4842874514067399, */
2991: /* 0.51326036147820708, 0.48673963852179264} */
2992: /* If we start from prlim again, prlim tends to a constant matrix */
2993:
1.332 ! brouard 2994: int i, ii,j,k, k1;
1.247 brouard 2995: int first=0;
1.217 brouard 2996: double *min, *max, *meandiff, maxmax,sumnew=0.;
2997: /* double **matprod2(); */ /* test */
2998: double **out, cov[NCOVMAX+1], **bmij();
2999: double **newm;
1.218 brouard 3000: double **dnewm, **doldm, **dsavm; /* for use */
3001: double **oldm, **savm; /* for use */
3002:
1.217 brouard 3003: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3004: int ncvloop=0;
3005:
3006: min=vector(1,nlstate);
3007: max=vector(1,nlstate);
3008: meandiff=vector(1,nlstate);
3009:
1.266 brouard 3010: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3011: oldm=oldms; savm=savms;
3012:
3013: /* Starting with matrix unity */
3014: for (ii=1;ii<=nlstate+ndeath;ii++)
3015: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3016: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3017: }
3018:
3019: cov[1]=1.;
3020:
3021: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3022: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3023: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3024: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3025: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3026: ncvloop++;
1.218 brouard 3027: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3028: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3029: /* Covariates have to be included here again */
3030: cov[2]=agefin;
1.319 brouard 3031: if(nagesqr==1){
1.217 brouard 3032: cov[3]= agefin*agefin;;
1.319 brouard 3033: }
1.332 ! brouard 3034: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
! 3035: if(Typevar[k1]==1){ /* A product with age */
! 3036: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3037: }else{
1.332 ! brouard 3038: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3039: }
1.332 ! brouard 3040: }/* End of loop on model equation */
! 3041:
! 3042: /* Old code */
! 3043:
! 3044: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
! 3045: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
! 3046: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
! 3047: /* /\* 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)); *\/ */
! 3048: /* } */
! 3049: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
! 3050: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
! 3051: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
! 3052: /* /\* /\\* 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])]); *\\/ *\/ */
! 3053: /* /\* } *\/ */
! 3054: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
! 3055: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
! 3056: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
! 3057: /* /\* 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]); *\/ */
! 3058: /* } */
! 3059: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
! 3060: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
! 3061: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
! 3062: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
! 3063: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
! 3064: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
! 3065: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
! 3066: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
! 3067: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
! 3068: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
! 3069: /* } */
! 3070: /* /\* 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]); *\/ */
! 3071: /* } */
! 3072: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
! 3073: /* /\* 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]); *\/ */
! 3074: /* if(Dummy[Tvard[k][1]]==0){ */
! 3075: /* if(Dummy[Tvard[k][2]]==0){ */
! 3076: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
! 3077: /* }else{ */
! 3078: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
! 3079: /* } */
! 3080: /* }else{ */
! 3081: /* if(Dummy[Tvard[k][2]]==0){ */
! 3082: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
! 3083: /* }else{ */
! 3084: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
! 3085: /* } */
! 3086: /* } */
! 3087: /* } */
1.217 brouard 3088:
3089: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3090: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3091: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3092: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3093: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3094: /* ij should be linked to the correct index of cov */
3095: /* age and covariate values ij are in 'cov', but we need to pass
3096: * ij for the observed prevalence at age and status and covariate
3097: * number: prevacurrent[(int)agefin][ii][ij]
3098: */
3099: /* 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 *\/ */
3100: /* 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 *\/ */
3101: 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 3102: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3103: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3104: /* for(i=1; i<=nlstate+ndeath; i++) { */
3105: /* printf("%d newm= ",i); */
3106: /* for(j=1;j<=nlstate+ndeath;j++) { */
3107: /* printf("%f ",newm[i][j]); */
3108: /* } */
3109: /* printf("oldm * "); */
3110: /* for(j=1;j<=nlstate+ndeath;j++) { */
3111: /* printf("%f ",oldm[i][j]); */
3112: /* } */
1.268 brouard 3113: /* printf(" bmmij "); */
1.266 brouard 3114: /* for(j=1;j<=nlstate+ndeath;j++) { */
3115: /* printf("%f ",pmmij[i][j]); */
3116: /* } */
3117: /* printf("\n"); */
3118: /* } */
3119: /* } */
1.217 brouard 3120: savm=oldm;
3121: oldm=newm;
1.266 brouard 3122:
1.217 brouard 3123: for(j=1; j<=nlstate; j++){
3124: max[j]=0.;
3125: min[j]=1.;
3126: }
3127: for(j=1; j<=nlstate; j++){
3128: for(i=1;i<=nlstate;i++){
1.234 brouard 3129: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3130: bprlim[i][j]= newm[i][j];
3131: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3132: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3133: }
3134: }
1.218 brouard 3135:
1.217 brouard 3136: maxmax=0.;
3137: for(i=1; i<=nlstate; i++){
1.318 brouard 3138: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3139: maxmax=FMAX(maxmax,meandiff[i]);
3140: /* 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 3141: } /* i loop */
1.217 brouard 3142: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3143: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3144: if(maxmax < ftolpl){
1.220 brouard 3145: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3146: free_vector(min,1,nlstate);
3147: free_vector(max,1,nlstate);
3148: free_vector(meandiff,1,nlstate);
3149: return bprlim;
3150: }
1.288 brouard 3151: } /* agefin loop */
1.217 brouard 3152: /* After some age loop it doesn't converge */
1.288 brouard 3153: if(!first){
1.247 brouard 3154: first=1;
3155: 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\
3156: 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);
3157: }
3158: 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 3159: 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);
3160: /* 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); */
3161: free_vector(min,1,nlstate);
3162: free_vector(max,1,nlstate);
3163: free_vector(meandiff,1,nlstate);
3164:
3165: return bprlim; /* should not reach here */
3166: }
3167:
1.126 brouard 3168: /*************** transition probabilities ***************/
3169:
3170: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3171: {
1.138 brouard 3172: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3173: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3174: model to the ncovmodel covariates (including constant and age).
3175: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3176: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3177: ncth covariate in the global vector x is given by the formula:
3178: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3179: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3180: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3181: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3182: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3183: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3184: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3185: */
3186: double s1, lnpijopii;
1.126 brouard 3187: /*double t34;*/
1.164 brouard 3188: int i,j, nc, ii, jj;
1.126 brouard 3189:
1.223 brouard 3190: for(i=1; i<= nlstate; i++){
3191: for(j=1; j<i;j++){
3192: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3193: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3194: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3195: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3196: }
3197: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3198: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3199: }
3200: for(j=i+1; j<=nlstate+ndeath;j++){
3201: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3202: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3203: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3204: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3205: }
3206: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3207: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3208: }
3209: }
1.218 brouard 3210:
1.223 brouard 3211: for(i=1; i<= nlstate; i++){
3212: s1=0;
3213: for(j=1; j<i; j++){
3214: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
1.330 brouard 3215: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
1.223 brouard 3216: }
3217: for(j=i+1; j<=nlstate+ndeath; j++){
3218: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
1.330 brouard 3219: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
1.223 brouard 3220: }
3221: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3222: ps[i][i]=1./(s1+1.);
3223: /* Computing other pijs */
3224: for(j=1; j<i; j++)
1.325 brouard 3225: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3226: for(j=i+1; j<=nlstate+ndeath; j++)
3227: ps[i][j]= exp(ps[i][j])*ps[i][i];
3228: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3229: } /* end i */
1.218 brouard 3230:
1.223 brouard 3231: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3232: for(jj=1; jj<= nlstate+ndeath; jj++){
3233: ps[ii][jj]=0;
3234: ps[ii][ii]=1;
3235: }
3236: }
1.294 brouard 3237:
3238:
1.223 brouard 3239: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3240: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3241: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3242: /* } */
3243: /* printf("\n "); */
3244: /* } */
3245: /* printf("\n ");printf("%lf ",cov[2]);*/
3246: /*
3247: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3248: goto end;*/
1.266 brouard 3249: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3250: }
3251:
1.218 brouard 3252: /*************** backward transition probabilities ***************/
3253:
3254: /* 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 ) */
3255: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3256: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3257: {
1.302 brouard 3258: /* 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 3259: * 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 3260: */
1.218 brouard 3261: int i, ii, j,k;
1.222 brouard 3262:
3263: double **out, **pmij();
3264: double sumnew=0.;
1.218 brouard 3265: double agefin;
1.292 brouard 3266: 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 3267: double **dnewm, **dsavm, **doldm;
3268: double **bbmij;
3269:
1.218 brouard 3270: doldm=ddoldms; /* global pointers */
1.222 brouard 3271: dnewm=ddnewms;
3272: dsavm=ddsavms;
1.318 brouard 3273:
3274: /* Debug */
3275: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3276: agefin=cov[2];
1.268 brouard 3277: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3278: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3279: the observed prevalence (with this covariate ij) at beginning of transition */
3280: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3281:
3282: /* P_x */
1.325 brouard 3283: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3284: /* outputs pmmij which is a stochastic matrix in row */
3285:
3286: /* Diag(w_x) */
1.292 brouard 3287: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3288: sumnew=0.;
1.269 brouard 3289: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3290: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3291: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3292: sumnew+=prevacurrent[(int)agefin][ii][ij];
3293: }
3294: if(sumnew >0.01){ /* At least some value in the prevalence */
3295: for (ii=1;ii<=nlstate+ndeath;ii++){
3296: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3297: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3298: }
3299: }else{
3300: for (ii=1;ii<=nlstate+ndeath;ii++){
3301: for (j=1;j<=nlstate+ndeath;j++)
3302: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3303: }
3304: /* if(sumnew <0.9){ */
3305: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3306: /* } */
3307: }
3308: k3=0.0; /* We put the last diagonal to 0 */
3309: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3310: doldm[ii][ii]= k3;
3311: }
3312: /* End doldm, At the end doldm is diag[(w_i)] */
3313:
1.292 brouard 3314: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3315: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3316:
1.292 brouard 3317: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3318: /* 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 3319: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3320: sumnew=0.;
1.222 brouard 3321: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3322: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3323: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3324: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3325: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3326: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3327: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3328: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3329: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3330: /* }else */
1.268 brouard 3331: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3332: } /*End ii */
3333: } /* 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 */
3334:
1.292 brouard 3335: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3336: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3337: /* end bmij */
1.266 brouard 3338: return ps; /*pointer is unchanged */
1.218 brouard 3339: }
1.217 brouard 3340: /*************** transition probabilities ***************/
3341:
1.218 brouard 3342: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3343: {
3344: /* According to parameters values stored in x and the covariate's values stored in cov,
3345: computes the probability to be observed in state j being in state i by appying the
3346: model to the ncovmodel covariates (including constant and age).
3347: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3348: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3349: ncth covariate in the global vector x is given by the formula:
3350: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3351: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3352: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3353: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3354: Outputs ps[i][j] the probability to be observed in j being in j according to
3355: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3356: */
3357: double s1, lnpijopii;
3358: /*double t34;*/
3359: int i,j, nc, ii, jj;
3360:
1.234 brouard 3361: for(i=1; i<= nlstate; i++){
3362: for(j=1; j<i;j++){
3363: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3364: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3365: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3366: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3367: }
3368: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3369: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3370: }
3371: for(j=i+1; j<=nlstate+ndeath;j++){
3372: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3373: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3374: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3375: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3376: }
3377: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3378: }
3379: }
3380:
3381: for(i=1; i<= nlstate; i++){
3382: s1=0;
3383: for(j=1; j<i; j++){
3384: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3385: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3386: }
3387: for(j=i+1; j<=nlstate+ndeath; j++){
3388: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3389: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3390: }
3391: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3392: ps[i][i]=1./(s1+1.);
3393: /* Computing other pijs */
3394: for(j=1; j<i; j++)
3395: ps[i][j]= exp(ps[i][j])*ps[i][i];
3396: for(j=i+1; j<=nlstate+ndeath; j++)
3397: ps[i][j]= exp(ps[i][j])*ps[i][i];
3398: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3399: } /* end i */
3400:
3401: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3402: for(jj=1; jj<= nlstate+ndeath; jj++){
3403: ps[ii][jj]=0;
3404: ps[ii][ii]=1;
3405: }
3406: }
1.296 brouard 3407: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3408: for(jj=1; jj<= nlstate+ndeath; jj++){
3409: s1=0.;
3410: for(ii=1; ii<= nlstate+ndeath; ii++){
3411: s1+=ps[ii][jj];
3412: }
3413: for(ii=1; ii<= nlstate; ii++){
3414: ps[ii][jj]=ps[ii][jj]/s1;
3415: }
3416: }
3417: /* Transposition */
3418: for(jj=1; jj<= nlstate+ndeath; jj++){
3419: for(ii=jj; ii<= nlstate+ndeath; ii++){
3420: s1=ps[ii][jj];
3421: ps[ii][jj]=ps[jj][ii];
3422: ps[jj][ii]=s1;
3423: }
3424: }
3425: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3426: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3427: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3428: /* } */
3429: /* printf("\n "); */
3430: /* } */
3431: /* printf("\n ");printf("%lf ",cov[2]);*/
3432: /*
3433: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3434: goto end;*/
3435: return ps;
1.217 brouard 3436: }
3437:
3438:
1.126 brouard 3439: /**************** Product of 2 matrices ******************/
3440:
1.145 brouard 3441: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3442: {
3443: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3444: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3445: /* in, b, out are matrice of pointers which should have been initialized
3446: before: only the contents of out is modified. The function returns
3447: a pointer to pointers identical to out */
1.145 brouard 3448: int i, j, k;
1.126 brouard 3449: for(i=nrl; i<= nrh; i++)
1.145 brouard 3450: for(k=ncolol; k<=ncoloh; k++){
3451: out[i][k]=0.;
3452: for(j=ncl; j<=nch; j++)
3453: out[i][k] +=in[i][j]*b[j][k];
3454: }
1.126 brouard 3455: return out;
3456: }
3457:
3458:
3459: /************* Higher Matrix Product ***************/
3460:
1.235 brouard 3461: 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 3462: {
1.332 ! brouard 3463: /* 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 3464: 'nhstepm*hstepm*stepm' months (i.e. until
3465: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3466: nhstepm*hstepm matrices.
3467: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3468: (typically every 2 years instead of every month which is too big
3469: for the memory).
3470: Model is determined by parameters x and covariates have to be
3471: included manually here.
3472:
3473: */
3474:
1.330 brouard 3475: int i, j, d, h, k, k1;
1.131 brouard 3476: double **out, cov[NCOVMAX+1];
1.126 brouard 3477: double **newm;
1.187 brouard 3478: double agexact;
1.214 brouard 3479: double agebegin, ageend;
1.126 brouard 3480:
3481: /* Hstepm could be zero and should return the unit matrix */
3482: for (i=1;i<=nlstate+ndeath;i++)
3483: for (j=1;j<=nlstate+ndeath;j++){
3484: oldm[i][j]=(i==j ? 1.0 : 0.0);
3485: po[i][j][0]=(i==j ? 1.0 : 0.0);
3486: }
3487: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3488: for(h=1; h <=nhstepm; h++){
3489: for(d=1; d <=hstepm; d++){
3490: newm=savm;
3491: /* Covariates have to be included here again */
3492: cov[1]=1.;
1.214 brouard 3493: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3494: cov[2]=agexact;
1.319 brouard 3495: if(nagesqr==1){
1.227 brouard 3496: cov[3]= agexact*agexact;
1.319 brouard 3497: }
1.330 brouard 3498: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3499: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3500: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.332 ! brouard 3501: if(Typevar[k1]==1){ /* A product with age */
! 3502: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
! 3503: }else{
! 3504: cov[2+nagesqr+k1]=precov[nres][k1];
! 3505: }
! 3506: }/* End of loop on model equation */
! 3507: /* Old code */
! 3508: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
! 3509: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
! 3510: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
! 3511: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
! 3512: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
! 3513: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
! 3514: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
! 3515: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
! 3516: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
! 3517: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
! 3518: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
! 3519: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
! 3520: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
! 3521: /* /\* 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]])); *\/ */
! 3522: /* 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); */
! 3523: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
! 3524: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
! 3525: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
! 3526: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
! 3527: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
! 3528: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
! 3529: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
! 3530: /* 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]]); */
! 3531: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
! 3532: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
! 3533: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
! 3534: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
! 3535: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
! 3536: /* 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]); */
! 3537: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
! 3538:
! 3539: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
! 3540: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
! 3541: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
! 3542: /* /\* *\/ */
1.330 brouard 3543: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3544: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3545: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 ! brouard 3546: /* /\*cptcovage=2 1 2 *\/ */
! 3547: /* /\*Tage[k]= 5 8 *\/ */
! 3548: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
! 3549: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
! 3550: /* 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]]); */
! 3551: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
! 3552: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
! 3553: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
! 3554: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
! 3555: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
! 3556: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
! 3557: /* /\* 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); *\/ */
! 3558: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
! 3559: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
! 3560: /* /\* } *\/ */
! 3561: /* /\* 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]); *\/ */
! 3562: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
! 3563: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
! 3564: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
! 3565: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
! 3566: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
! 3567: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
! 3568: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
! 3569: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
! 3570: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3571:
1.332 ! brouard 3572: /* /\* 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])]); *\/ */
! 3573: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
! 3574: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
! 3575: /* 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]]); */
! 3576: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
! 3577:
! 3578: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
! 3579: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
! 3580: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
! 3581: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
! 3582: /* /\* 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]])]; *\/ */
! 3583: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
! 3584: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
! 3585: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
! 3586: /* /\* } *\/ */
! 3587: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
! 3588: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
! 3589: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
! 3590: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
! 3591: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
! 3592: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
! 3593: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
! 3594: /* /\* } *\/ */
! 3595: /* /\* }/\\*end of products quantitative *\\/ *\/ */
! 3596: /* }/\*end of products *\/ */
! 3597: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3598: /* for (k=1; k<=cptcovn;k++) */
3599: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3600: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3601: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3602: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3603: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3604:
3605:
1.126 brouard 3606: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3607: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3608: /* right multiplication of oldm by the current matrix */
1.126 brouard 3609: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3610: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3611: /* if((int)age == 70){ */
3612: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3613: /* for(i=1; i<=nlstate+ndeath; i++) { */
3614: /* printf("%d pmmij ",i); */
3615: /* for(j=1;j<=nlstate+ndeath;j++) { */
3616: /* printf("%f ",pmmij[i][j]); */
3617: /* } */
3618: /* printf(" oldm "); */
3619: /* for(j=1;j<=nlstate+ndeath;j++) { */
3620: /* printf("%f ",oldm[i][j]); */
3621: /* } */
3622: /* printf("\n"); */
3623: /* } */
3624: /* } */
1.126 brouard 3625: savm=oldm;
3626: oldm=newm;
3627: }
3628: for(i=1; i<=nlstate+ndeath; i++)
3629: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3630: po[i][j][h]=newm[i][j];
3631: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3632: }
1.128 brouard 3633: /*printf("h=%d ",h);*/
1.126 brouard 3634: } /* end h */
1.267 brouard 3635: /* printf("\n H=%d \n",h); */
1.126 brouard 3636: return po;
3637: }
3638:
1.217 brouard 3639: /************* Higher Back Matrix Product ***************/
1.218 brouard 3640: /* 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 3641: 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 3642: {
1.332 ! brouard 3643: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
! 3644: computes the transition matrix starting at age 'age' over
1.217 brouard 3645: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3646: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3647: nhstepm*hstepm matrices.
3648: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3649: (typically every 2 years instead of every month which is too big
1.217 brouard 3650: for the memory).
1.218 brouard 3651: Model is determined by parameters x and covariates have to be
1.266 brouard 3652: included manually here. Then we use a call to bmij(x and cov)
3653: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3654: */
1.217 brouard 3655:
1.332 ! brouard 3656: int i, j, d, h, k, k1;
1.266 brouard 3657: double **out, cov[NCOVMAX+1], **bmij();
3658: double **newm, ***newmm;
1.217 brouard 3659: double agexact;
3660: double agebegin, ageend;
1.222 brouard 3661: double **oldm, **savm;
1.217 brouard 3662:
1.266 brouard 3663: newmm=po; /* To be saved */
3664: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3665: /* Hstepm could be zero and should return the unit matrix */
3666: for (i=1;i<=nlstate+ndeath;i++)
3667: for (j=1;j<=nlstate+ndeath;j++){
3668: oldm[i][j]=(i==j ? 1.0 : 0.0);
3669: po[i][j][0]=(i==j ? 1.0 : 0.0);
3670: }
3671: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3672: for(h=1; h <=nhstepm; h++){
3673: for(d=1; d <=hstepm; d++){
3674: newm=savm;
3675: /* Covariates have to be included here again */
3676: cov[1]=1.;
1.271 brouard 3677: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3678: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3679: /* Debug */
3680: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3681: cov[2]=agexact;
1.332 ! brouard 3682: if(nagesqr==1){
1.222 brouard 3683: cov[3]= agexact*agexact;
1.332 ! brouard 3684: }
! 3685: /** New code */
! 3686: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
! 3687: if(Typevar[k1]==1){ /* A product with age */
! 3688: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3689: }else{
1.332 ! brouard 3690: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3691: }
1.332 ! brouard 3692: }/* End of loop on model equation */
! 3693: /** End of new code */
! 3694: /** This was old code */
! 3695: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
! 3696: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
! 3697: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
! 3698: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
! 3699: /* /\* 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)); *\/ */
! 3700: /* } */
! 3701: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
! 3702: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
! 3703: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
! 3704: /* /\* printf("hPxij Quantitative 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]); *\/ */
! 3705: /* } */
! 3706: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
! 3707: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
! 3708: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
! 3709: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
! 3710: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
! 3711: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
! 3712: /* } */
! 3713: /* /\* 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]); *\/ */
! 3714: /* } */
! 3715: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
! 3716: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
! 3717: /* if(Dummy[Tvard[k][1]]==0){ */
! 3718: /* if(Dummy[Tvard[k][2]]==0){ */
! 3719: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
! 3720: /* }else{ */
! 3721: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
! 3722: /* } */
! 3723: /* }else{ */
! 3724: /* if(Dummy[Tvard[k][2]]==0){ */
! 3725: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
! 3726: /* }else{ */
! 3727: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
! 3728: /* } */
! 3729: /* } */
! 3730: /* } */
! 3731: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
! 3732: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
! 3733: /** End of old code */
! 3734:
1.218 brouard 3735: /* Careful transposed matrix */
1.266 brouard 3736: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3737: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3738: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3739: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3740: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3741: /* if((int)age == 70){ */
3742: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3743: /* for(i=1; i<=nlstate+ndeath; i++) { */
3744: /* printf("%d pmmij ",i); */
3745: /* for(j=1;j<=nlstate+ndeath;j++) { */
3746: /* printf("%f ",pmmij[i][j]); */
3747: /* } */
3748: /* printf(" oldm "); */
3749: /* for(j=1;j<=nlstate+ndeath;j++) { */
3750: /* printf("%f ",oldm[i][j]); */
3751: /* } */
3752: /* printf("\n"); */
3753: /* } */
3754: /* } */
3755: savm=oldm;
3756: oldm=newm;
3757: }
3758: for(i=1; i<=nlstate+ndeath; i++)
3759: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3760: po[i][j][h]=newm[i][j];
1.268 brouard 3761: /* if(h==nhstepm) */
3762: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3763: }
1.268 brouard 3764: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3765: } /* end h */
1.268 brouard 3766: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3767: return po;
3768: }
3769:
3770:
1.162 brouard 3771: #ifdef NLOPT
3772: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3773: double fret;
3774: double *xt;
3775: int j;
3776: myfunc_data *d2 = (myfunc_data *) pd;
3777: /* xt = (p1-1); */
3778: xt=vector(1,n);
3779: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3780:
3781: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3782: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3783: printf("Function = %.12lf ",fret);
3784: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3785: printf("\n");
3786: free_vector(xt,1,n);
3787: return fret;
3788: }
3789: #endif
1.126 brouard 3790:
3791: /*************** log-likelihood *************/
3792: double func( double *x)
3793: {
1.226 brouard 3794: int i, ii, j, k, mi, d, kk;
3795: int ioffset=0;
3796: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3797: double **out;
3798: double lli; /* Individual log likelihood */
3799: int s1, s2;
1.228 brouard 3800: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
1.226 brouard 3801: double bbh, survp;
3802: long ipmx;
3803: double agexact;
3804: /*extern weight */
3805: /* We are differentiating ll according to initial status */
3806: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3807: /*for(i=1;i<imx;i++)
3808: printf(" %d\n",s[4][i]);
3809: */
1.162 brouard 3810:
1.226 brouard 3811: ++countcallfunc;
1.162 brouard 3812:
1.226 brouard 3813: cov[1]=1.;
1.126 brouard 3814:
1.226 brouard 3815: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3816: ioffset=0;
1.226 brouard 3817: if(mle==1){
3818: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3819: /* Computes the values of the ncovmodel covariates of the model
3820: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3821: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3822: to be observed in j being in i according to the model.
3823: */
1.243 brouard 3824: ioffset=2+nagesqr ;
1.233 brouard 3825: /* Fixed */
1.319 brouard 3826: for (k=1; k<=ncovf;k++){ /* For each fixed covariate dummu or quant or prod */
3827: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
3828: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3829: /* 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 3830: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.319 brouard 3831: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (TvarFind[1]=6)*/
3832: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 3833: }
1.226 brouard 3834: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 3835: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 3836: has been calculated etc */
3837: /* For an individual i, wav[i] gives the number of effective waves */
3838: /* We compute the contribution to Likelihood of each effective transition
3839: mw[mi][i] is real wave of the mi th effectve wave */
3840: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3841: s2=s[mw[mi+1][i]][i];
3842: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3843: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3844: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3845: */
3846: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 3847: 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*/
3848: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? */
1.242 brouard 3849: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3850: }
3851: for (ii=1;ii<=nlstate+ndeath;ii++)
3852: for (j=1;j<=nlstate+ndeath;j++){
3853: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3854: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3855: }
3856: for(d=0; d<dh[mi][i]; d++){
3857: newm=savm;
3858: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3859: cov[2]=agexact;
3860: if(nagesqr==1)
3861: cov[3]= agexact*agexact; /* Should be changed here */
3862: for (kk=1; kk<=cptcovage;kk++) {
1.318 brouard 3863: if(!FixedV[Tvar[Tage[kk]]])
3864: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
3865: else
3866: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3867: }
3868: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3869: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3870: savm=oldm;
3871: oldm=newm;
3872: } /* end mult */
3873:
3874: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3875: /* But now since version 0.9 we anticipate for bias at large stepm.
3876: * If stepm is larger than one month (smallest stepm) and if the exact delay
3877: * (in months) between two waves is not a multiple of stepm, we rounded to
3878: * the nearest (and in case of equal distance, to the lowest) interval but now
3879: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3880: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3881: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3882: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3883: * -stepm/2 to stepm/2 .
3884: * For stepm=1 the results are the same as for previous versions of Imach.
3885: * For stepm > 1 the results are less biased than in previous versions.
3886: */
1.234 brouard 3887: s1=s[mw[mi][i]][i];
3888: s2=s[mw[mi+1][i]][i];
3889: bbh=(double)bh[mi][i]/(double)stepm;
3890: /* bias bh is positive if real duration
3891: * is higher than the multiple of stepm and negative otherwise.
3892: */
3893: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3894: if( s2 > nlstate){
3895: /* i.e. if s2 is a death state and if the date of death is known
3896: then the contribution to the likelihood is the probability to
3897: die between last step unit time and current step unit time,
3898: which is also equal to probability to die before dh
3899: minus probability to die before dh-stepm .
3900: In version up to 0.92 likelihood was computed
3901: as if date of death was unknown. Death was treated as any other
3902: health state: the date of the interview describes the actual state
3903: and not the date of a change in health state. The former idea was
3904: to consider that at each interview the state was recorded
3905: (healthy, disable or death) and IMaCh was corrected; but when we
3906: introduced the exact date of death then we should have modified
3907: the contribution of an exact death to the likelihood. This new
3908: contribution is smaller and very dependent of the step unit
3909: stepm. It is no more the probability to die between last interview
3910: and month of death but the probability to survive from last
3911: interview up to one month before death multiplied by the
3912: probability to die within a month. Thanks to Chris
3913: Jackson for correcting this bug. Former versions increased
3914: mortality artificially. The bad side is that we add another loop
3915: which slows down the processing. The difference can be up to 10%
3916: lower mortality.
3917: */
3918: /* If, at the beginning of the maximization mostly, the
3919: cumulative probability or probability to be dead is
3920: constant (ie = 1) over time d, the difference is equal to
3921: 0. out[s1][3] = savm[s1][3]: probability, being at state
3922: s1 at precedent wave, to be dead a month before current
3923: wave is equal to probability, being at state s1 at
3924: precedent wave, to be dead at mont of the current
3925: wave. Then the observed probability (that this person died)
3926: is null according to current estimated parameter. In fact,
3927: it should be very low but not zero otherwise the log go to
3928: infinity.
3929: */
1.183 brouard 3930: /* #ifdef INFINITYORIGINAL */
3931: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3932: /* #else */
3933: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3934: /* lli=log(mytinydouble); */
3935: /* else */
3936: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3937: /* #endif */
1.226 brouard 3938: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3939:
1.226 brouard 3940: } else if ( s2==-1 ) { /* alive */
3941: for (j=1,survp=0. ; j<=nlstate; j++)
3942: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3943: /*survp += out[s1][j]; */
3944: lli= log(survp);
3945: }
3946: else if (s2==-4) {
3947: for (j=3,survp=0. ; j<=nlstate; j++)
3948: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3949: lli= log(survp);
3950: }
3951: else if (s2==-5) {
3952: for (j=1,survp=0. ; j<=2; j++)
3953: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3954: lli= log(survp);
3955: }
3956: else{
3957: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3958: /* 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 */
3959: }
3960: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3961: /*if(lli ==000.0)*/
3962: /*printf("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); */
3963: ipmx +=1;
3964: sw += weight[i];
3965: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3966: /* if (lli < log(mytinydouble)){ */
3967: /* 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); */
3968: /* 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]); */
3969: /* } */
3970: } /* end of wave */
3971: } /* end of individual */
3972: } else if(mle==2){
3973: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 3974: ioffset=2+nagesqr ;
3975: for (k=1; k<=ncovf;k++)
3976: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 3977: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 3978: for(k=1; k <= ncovv ; k++){
3979: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3980: }
1.226 brouard 3981: for (ii=1;ii<=nlstate+ndeath;ii++)
3982: for (j=1;j<=nlstate+ndeath;j++){
3983: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3984: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3985: }
3986: for(d=0; d<=dh[mi][i]; d++){
3987: newm=savm;
3988: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3989: cov[2]=agexact;
3990: if(nagesqr==1)
3991: cov[3]= agexact*agexact;
3992: for (kk=1; kk<=cptcovage;kk++) {
3993: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3994: }
3995: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3996: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3997: savm=oldm;
3998: oldm=newm;
3999: } /* end mult */
4000:
4001: s1=s[mw[mi][i]][i];
4002: s2=s[mw[mi+1][i]][i];
4003: bbh=(double)bh[mi][i]/(double)stepm;
4004: 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 */
4005: ipmx +=1;
4006: sw += weight[i];
4007: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4008: } /* end of wave */
4009: } /* end of individual */
4010: } else if(mle==3){ /* exponential inter-extrapolation */
4011: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4012: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4013: for(mi=1; mi<= wav[i]-1; mi++){
4014: for (ii=1;ii<=nlstate+ndeath;ii++)
4015: for (j=1;j<=nlstate+ndeath;j++){
4016: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4017: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4018: }
4019: for(d=0; d<dh[mi][i]; d++){
4020: newm=savm;
4021: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4022: cov[2]=agexact;
4023: if(nagesqr==1)
4024: cov[3]= agexact*agexact;
4025: for (kk=1; kk<=cptcovage;kk++) {
4026: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4027: }
4028: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4029: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4030: savm=oldm;
4031: oldm=newm;
4032: } /* end mult */
4033:
4034: s1=s[mw[mi][i]][i];
4035: s2=s[mw[mi+1][i]][i];
4036: bbh=(double)bh[mi][i]/(double)stepm;
4037: 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 */
4038: ipmx +=1;
4039: sw += weight[i];
4040: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4041: } /* end of wave */
4042: } /* end of individual */
4043: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4044: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4045: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4046: for(mi=1; mi<= wav[i]-1; mi++){
4047: for (ii=1;ii<=nlstate+ndeath;ii++)
4048: for (j=1;j<=nlstate+ndeath;j++){
4049: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4050: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4051: }
4052: for(d=0; d<dh[mi][i]; d++){
4053: newm=savm;
4054: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4055: cov[2]=agexact;
4056: if(nagesqr==1)
4057: cov[3]= agexact*agexact;
4058: for (kk=1; kk<=cptcovage;kk++) {
4059: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4060: }
1.126 brouard 4061:
1.226 brouard 4062: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4063: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4064: savm=oldm;
4065: oldm=newm;
4066: } /* end mult */
4067:
4068: s1=s[mw[mi][i]][i];
4069: s2=s[mw[mi+1][i]][i];
4070: if( s2 > nlstate){
4071: lli=log(out[s1][s2] - savm[s1][s2]);
4072: } else if ( s2==-1 ) { /* alive */
4073: for (j=1,survp=0. ; j<=nlstate; j++)
4074: survp += out[s1][j];
4075: lli= log(survp);
4076: }else{
4077: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4078: }
4079: ipmx +=1;
4080: sw += weight[i];
4081: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 4082: /* 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]); */
1.226 brouard 4083: } /* end of wave */
4084: } /* end of individual */
4085: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4086: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4087: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4088: for(mi=1; mi<= wav[i]-1; mi++){
4089: for (ii=1;ii<=nlstate+ndeath;ii++)
4090: for (j=1;j<=nlstate+ndeath;j++){
4091: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4092: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4093: }
4094: for(d=0; d<dh[mi][i]; d++){
4095: newm=savm;
4096: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4097: cov[2]=agexact;
4098: if(nagesqr==1)
4099: cov[3]= agexact*agexact;
4100: for (kk=1; kk<=cptcovage;kk++) {
4101: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4102: }
1.126 brouard 4103:
1.226 brouard 4104: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4105: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4106: savm=oldm;
4107: oldm=newm;
4108: } /* end mult */
4109:
4110: s1=s[mw[mi][i]][i];
4111: s2=s[mw[mi+1][i]][i];
4112: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4113: ipmx +=1;
4114: sw += weight[i];
4115: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4116: /*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]);*/
4117: } /* end of wave */
4118: } /* end of individual */
4119: } /* End of if */
4120: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4121: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4122: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4123: return -l;
1.126 brouard 4124: }
4125:
4126: /*************** log-likelihood *************/
4127: double funcone( double *x)
4128: {
1.228 brouard 4129: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 4130: int i, ii, j, k, mi, d, kk;
1.228 brouard 4131: int ioffset=0;
1.131 brouard 4132: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4133: double **out;
4134: double lli; /* Individual log likelihood */
4135: double llt;
4136: int s1, s2;
1.228 brouard 4137: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4138:
1.126 brouard 4139: double bbh, survp;
1.187 brouard 4140: double agexact;
1.214 brouard 4141: double agebegin, ageend;
1.126 brouard 4142: /*extern weight */
4143: /* We are differentiating ll according to initial status */
4144: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4145: /*for(i=1;i<imx;i++)
4146: printf(" %d\n",s[4][i]);
4147: */
4148: cov[1]=1.;
4149:
4150: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4151: ioffset=0;
4152: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 4153: /* ioffset=2+nagesqr+cptcovage; */
4154: ioffset=2+nagesqr;
1.232 brouard 4155: /* Fixed */
1.224 brouard 4156: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4157: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.311 brouard 4158: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
1.232 brouard 4159: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (k=6)*/
4160: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4161: /* cov[2+6]=covar[Tvar[6]][i]; */
4162: /* cov[2+6]=covar[2][i]; V2 */
4163: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4164: /* cov[2+7]=covar[Tvar[7]][i]; */
4165: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4166: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4167: /* cov[2+9]=covar[Tvar[9]][i]; */
4168: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4169: }
1.232 brouard 4170: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4171: /* 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?)*\/ */
4172: /* } */
1.231 brouard 4173: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4174: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4175: /* } */
1.225 brouard 4176:
1.233 brouard 4177:
4178: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 4179: /* Wave varying (but not age varying) */
4180: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 4181: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
4182: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
4183: }
1.232 brouard 4184: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 4185: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4186: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
4187: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
4188: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
4189: /* printf(" i=%d,mi=%d,itv=%d,TmodelInvind[itv]=%d,cotvar[mw[mi][i]][TmodelInvind[itv]][i]=%f\n", i, mi, itv, TmodelInvind[itv],cotvar[mw[mi][i]][TmodelInvind[itv]][i]); */
1.232 brouard 4190: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4191: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4192: /* /\* 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]); *\/ */
4193: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4194: /* } */
1.126 brouard 4195: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4196: for (j=1;j<=nlstate+ndeath;j++){
4197: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4198: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4199: }
1.214 brouard 4200:
4201: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4202: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4203: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4204: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4205: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4206: and mw[mi+1][i]. dh depends on stepm.*/
4207: newm=savm;
1.247 brouard 4208: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4209: cov[2]=agexact;
4210: if(nagesqr==1)
4211: cov[3]= agexact*agexact;
4212: for (kk=1; kk<=cptcovage;kk++) {
4213: if(!FixedV[Tvar[Tage[kk]]])
4214: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4215: else
4216: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
4217: }
4218: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4219: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4220: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4221: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4222: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4223: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4224: savm=oldm;
4225: oldm=newm;
1.126 brouard 4226: } /* end mult */
4227:
4228: s1=s[mw[mi][i]][i];
4229: s2=s[mw[mi+1][i]][i];
1.217 brouard 4230: /* if(s2==-1){ */
1.268 brouard 4231: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4232: /* /\* exit(1); *\/ */
4233: /* } */
1.126 brouard 4234: bbh=(double)bh[mi][i]/(double)stepm;
4235: /* bias is positive if real duration
4236: * is higher than the multiple of stepm and negative otherwise.
4237: */
4238: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4239: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4240: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4241: for (j=1,survp=0. ; j<=nlstate; j++)
4242: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4243: lli= log(survp);
1.126 brouard 4244: }else if (mle==1){
1.242 brouard 4245: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4246: } else if(mle==2){
1.242 brouard 4247: 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 4248: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4249: 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 4250: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4251: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4252: } else{ /* mle=0 back to 1 */
1.242 brouard 4253: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4254: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4255: } /* End of if */
4256: ipmx +=1;
4257: sw += weight[i];
4258: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 4259: /*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]); */
1.126 brouard 4260: if(globpr){
1.246 brouard 4261: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4262: %11.6f %11.6f %11.6f ", \
1.242 brouard 4263: 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 4264: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 4265: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4266: llt +=ll[k]*gipmx/gsw;
4267: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
4268: }
4269: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 4270: }
1.232 brouard 4271: } /* end of wave */
4272: } /* end of individual */
4273: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4274: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4275: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4276: if(globpr==0){ /* First time we count the contributions and weights */
4277: gipmx=ipmx;
4278: gsw=sw;
4279: }
4280: return -l;
1.126 brouard 4281: }
4282:
4283:
4284: /*************** function likelione ***********/
1.292 brouard 4285: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4286: {
4287: /* This routine should help understanding what is done with
4288: the selection of individuals/waves and
4289: to check the exact contribution to the likelihood.
4290: Plotting could be done.
4291: */
4292: int k;
4293:
4294: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4295: strcpy(fileresilk,"ILK_");
1.202 brouard 4296: strcat(fileresilk,fileresu);
1.126 brouard 4297: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4298: printf("Problem with resultfile: %s\n", fileresilk);
4299: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4300: }
1.214 brouard 4301: 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");
4302: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4303: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4304: for(k=1; k<=nlstate; k++)
4305: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
4306: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
4307: }
4308:
1.292 brouard 4309: *fretone=(*func)(p);
1.126 brouard 4310: if(*globpri !=0){
4311: fclose(ficresilk);
1.205 brouard 4312: if (mle ==0)
4313: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4314: else if(mle >=1)
4315: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4316: 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 4317: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4318:
4319: for (k=1; k<= nlstate ; k++) {
1.211 brouard 4320: 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> \
1.208 brouard 4321: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4322: }
1.207 brouard 4323: 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> \
1.204 brouard 4324: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4325: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 4326: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4327: fflush(fichtm);
1.205 brouard 4328: }
1.126 brouard 4329: return;
4330: }
4331:
4332:
4333: /*********** Maximum Likelihood Estimation ***************/
4334:
4335: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4336: {
1.319 brouard 4337: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4338: double **xi;
4339: double fret;
4340: double fretone; /* Only one call to likelihood */
4341: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4342:
4343: #ifdef NLOPT
4344: int creturn;
4345: nlopt_opt opt;
4346: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4347: double *lb;
4348: double minf; /* the minimum objective value, upon return */
4349: double * p1; /* Shifted parameters from 0 instead of 1 */
4350: myfunc_data dinst, *d = &dinst;
4351: #endif
4352:
4353:
1.126 brouard 4354: xi=matrix(1,npar,1,npar);
4355: for (i=1;i<=npar;i++)
4356: for (j=1;j<=npar;j++)
4357: xi[i][j]=(i==j ? 1.0 : 0.0);
4358: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4359: strcpy(filerespow,"POW_");
1.126 brouard 4360: strcat(filerespow,fileres);
4361: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4362: printf("Problem with resultfile: %s\n", filerespow);
4363: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4364: }
4365: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4366: for (i=1;i<=nlstate;i++)
4367: for(j=1;j<=nlstate+ndeath;j++)
4368: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4369: fprintf(ficrespow,"\n");
1.162 brouard 4370: #ifdef POWELL
1.319 brouard 4371: #ifdef LINMINORIGINAL
4372: #else /* LINMINORIGINAL */
4373:
4374: flatdir=ivector(1,npar);
4375: for (j=1;j<=npar;j++) flatdir[j]=0;
4376: #endif /*LINMINORIGINAL */
4377:
4378: #ifdef FLATSUP
4379: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4380: /* reorganizing p by suppressing flat directions */
4381: for(i=1, jk=1; i <=nlstate; i++){
4382: for(k=1; k <=(nlstate+ndeath); k++){
4383: if (k != i) {
4384: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4385: if(flatdir[jk]==1){
4386: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4387: }
4388: for(j=1; j <=ncovmodel; j++){
4389: printf("%12.7f ",p[jk]);
4390: jk++;
4391: }
4392: printf("\n");
4393: }
4394: }
4395: }
4396: /* skipping */
4397: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4398: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4399: for(k=1; k <=(nlstate+ndeath); k++){
4400: if (k != i) {
4401: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4402: if(flatdir[jk]==1){
4403: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4404: for(j=1; j <=ncovmodel; jk++,j++){
4405: printf(" p[%d]=%12.7f",jk, p[jk]);
4406: /*q[jjk]=p[jk];*/
4407: }
4408: }else{
4409: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4410: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4411: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
4412: /*q[jjk]=p[jk];*/
4413: }
4414: }
4415: printf("\n");
4416: }
4417: fflush(stdout);
4418: }
4419: }
4420: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4421: #else /* FLATSUP */
1.126 brouard 4422: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 4423: #endif /* FLATSUP */
4424:
4425: #ifdef LINMINORIGINAL
4426: #else
4427: free_ivector(flatdir,1,npar);
4428: #endif /* LINMINORIGINAL*/
4429: #endif /* POWELL */
1.126 brouard 4430:
1.162 brouard 4431: #ifdef NLOPT
4432: #ifdef NEWUOA
4433: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4434: #else
4435: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4436: #endif
4437: lb=vector(0,npar-1);
4438: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4439: nlopt_set_lower_bounds(opt, lb);
4440: nlopt_set_initial_step1(opt, 0.1);
4441:
4442: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4443: d->function = func;
4444: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4445: nlopt_set_min_objective(opt, myfunc, d);
4446: nlopt_set_xtol_rel(opt, ftol);
4447: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4448: printf("nlopt failed! %d\n",creturn);
4449: }
4450: else {
4451: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4452: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4453: iter=1; /* not equal */
4454: }
4455: nlopt_destroy(opt);
4456: #endif
1.319 brouard 4457: #ifdef FLATSUP
4458: /* npared = npar -flatd/ncovmodel; */
4459: /* xired= matrix(1,npared,1,npared); */
4460: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
4461: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
4462: /* free_matrix(xire,1,npared,1,npared); */
4463: #else /* FLATSUP */
4464: #endif /* FLATSUP */
1.126 brouard 4465: free_matrix(xi,1,npar,1,npar);
4466: fclose(ficrespow);
1.203 brouard 4467: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4468: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4469: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4470:
4471: }
4472:
4473: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4474: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4475: {
4476: double **a,**y,*x,pd;
1.203 brouard 4477: /* double **hess; */
1.164 brouard 4478: int i, j;
1.126 brouard 4479: int *indx;
4480:
4481: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4482: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4483: void lubksb(double **a, int npar, int *indx, double b[]) ;
4484: void ludcmp(double **a, int npar, int *indx, double *d) ;
4485: double gompertz(double p[]);
1.203 brouard 4486: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4487:
4488: printf("\nCalculation of the hessian matrix. Wait...\n");
4489: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4490: for (i=1;i<=npar;i++){
1.203 brouard 4491: printf("%d-",i);fflush(stdout);
4492: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4493:
4494: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4495:
4496: /* printf(" %f ",p[i]);
4497: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4498: }
4499:
4500: for (i=1;i<=npar;i++) {
4501: for (j=1;j<=npar;j++) {
4502: if (j>i) {
1.203 brouard 4503: printf(".%d-%d",i,j);fflush(stdout);
4504: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4505: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4506:
4507: hess[j][i]=hess[i][j];
4508: /*printf(" %lf ",hess[i][j]);*/
4509: }
4510: }
4511: }
4512: printf("\n");
4513: fprintf(ficlog,"\n");
4514:
4515: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4516: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4517:
4518: a=matrix(1,npar,1,npar);
4519: y=matrix(1,npar,1,npar);
4520: x=vector(1,npar);
4521: indx=ivector(1,npar);
4522: for (i=1;i<=npar;i++)
4523: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4524: ludcmp(a,npar,indx,&pd);
4525:
4526: for (j=1;j<=npar;j++) {
4527: for (i=1;i<=npar;i++) x[i]=0;
4528: x[j]=1;
4529: lubksb(a,npar,indx,x);
4530: for (i=1;i<=npar;i++){
4531: matcov[i][j]=x[i];
4532: }
4533: }
4534:
4535: printf("\n#Hessian matrix#\n");
4536: fprintf(ficlog,"\n#Hessian matrix#\n");
4537: for (i=1;i<=npar;i++) {
4538: for (j=1;j<=npar;j++) {
1.203 brouard 4539: printf("%.6e ",hess[i][j]);
4540: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4541: }
4542: printf("\n");
4543: fprintf(ficlog,"\n");
4544: }
4545:
1.203 brouard 4546: /* printf("\n#Covariance matrix#\n"); */
4547: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4548: /* for (i=1;i<=npar;i++) { */
4549: /* for (j=1;j<=npar;j++) { */
4550: /* printf("%.6e ",matcov[i][j]); */
4551: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4552: /* } */
4553: /* printf("\n"); */
4554: /* fprintf(ficlog,"\n"); */
4555: /* } */
4556:
1.126 brouard 4557: /* Recompute Inverse */
1.203 brouard 4558: /* for (i=1;i<=npar;i++) */
4559: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4560: /* ludcmp(a,npar,indx,&pd); */
4561:
4562: /* printf("\n#Hessian matrix recomputed#\n"); */
4563:
4564: /* for (j=1;j<=npar;j++) { */
4565: /* for (i=1;i<=npar;i++) x[i]=0; */
4566: /* x[j]=1; */
4567: /* lubksb(a,npar,indx,x); */
4568: /* for (i=1;i<=npar;i++){ */
4569: /* y[i][j]=x[i]; */
4570: /* printf("%.3e ",y[i][j]); */
4571: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4572: /* } */
4573: /* printf("\n"); */
4574: /* fprintf(ficlog,"\n"); */
4575: /* } */
4576:
4577: /* Verifying the inverse matrix */
4578: #ifdef DEBUGHESS
4579: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4580:
1.203 brouard 4581: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4582: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4583:
4584: for (j=1;j<=npar;j++) {
4585: for (i=1;i<=npar;i++){
1.203 brouard 4586: printf("%.2f ",y[i][j]);
4587: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4588: }
4589: printf("\n");
4590: fprintf(ficlog,"\n");
4591: }
1.203 brouard 4592: #endif
1.126 brouard 4593:
4594: free_matrix(a,1,npar,1,npar);
4595: free_matrix(y,1,npar,1,npar);
4596: free_vector(x,1,npar);
4597: free_ivector(indx,1,npar);
1.203 brouard 4598: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4599:
4600:
4601: }
4602:
4603: /*************** hessian matrix ****************/
4604: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4605: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4606: int i;
4607: int l=1, lmax=20;
1.203 brouard 4608: double k1,k2, res, fx;
1.132 brouard 4609: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4610: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4611: int k=0,kmax=10;
4612: double l1;
4613:
4614: fx=func(x);
4615: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4616: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4617: l1=pow(10,l);
4618: delts=delt;
4619: for(k=1 ; k <kmax; k=k+1){
4620: delt = delta*(l1*k);
4621: p2[theta]=x[theta] +delt;
1.145 brouard 4622: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4623: p2[theta]=x[theta]-delt;
4624: k2=func(p2)-fx;
4625: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4626: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4627:
1.203 brouard 4628: #ifdef DEBUGHESSII
1.126 brouard 4629: 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);
4630: 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);
4631: #endif
4632: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4633: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4634: k=kmax;
4635: }
4636: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4637: k=kmax; l=lmax*10;
1.126 brouard 4638: }
4639: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4640: delts=delt;
4641: }
1.203 brouard 4642: } /* End loop k */
1.126 brouard 4643: }
4644: delti[theta]=delts;
4645: return res;
4646:
4647: }
4648:
1.203 brouard 4649: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4650: {
4651: int i;
1.164 brouard 4652: int l=1, lmax=20;
1.126 brouard 4653: double k1,k2,k3,k4,res,fx;
1.132 brouard 4654: double p2[MAXPARM+1];
1.203 brouard 4655: int k, kmax=1;
4656: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4657:
4658: int firstime=0;
1.203 brouard 4659:
1.126 brouard 4660: fx=func(x);
1.203 brouard 4661: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4662: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4663: p2[thetai]=x[thetai]+delti[thetai]*k;
4664: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4665: k1=func(p2)-fx;
4666:
1.203 brouard 4667: p2[thetai]=x[thetai]+delti[thetai]*k;
4668: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4669: k2=func(p2)-fx;
4670:
1.203 brouard 4671: p2[thetai]=x[thetai]-delti[thetai]*k;
4672: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4673: k3=func(p2)-fx;
4674:
1.203 brouard 4675: p2[thetai]=x[thetai]-delti[thetai]*k;
4676: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4677: k4=func(p2)-fx;
1.203 brouard 4678: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4679: if(k1*k2*k3*k4 <0.){
1.208 brouard 4680: firstime=1;
1.203 brouard 4681: kmax=kmax+10;
1.208 brouard 4682: }
4683: if(kmax >=10 || firstime ==1){
1.246 brouard 4684: 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);
4685: 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 4686: 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);
4687: 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);
4688: }
4689: #ifdef DEBUGHESSIJ
4690: v1=hess[thetai][thetai];
4691: v2=hess[thetaj][thetaj];
4692: cv12=res;
4693: /* Computing eigen value of Hessian matrix */
4694: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4695: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4696: if ((lc2 <0) || (lc1 <0) ){
4697: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4698: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4699: 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);
4700: 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);
4701: }
1.126 brouard 4702: #endif
4703: }
4704: return res;
4705: }
4706:
1.203 brouard 4707: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4708: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4709: /* { */
4710: /* int i; */
4711: /* int l=1, lmax=20; */
4712: /* double k1,k2,k3,k4,res,fx; */
4713: /* double p2[MAXPARM+1]; */
4714: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4715: /* int k=0,kmax=10; */
4716: /* double l1; */
4717:
4718: /* fx=func(x); */
4719: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4720: /* l1=pow(10,l); */
4721: /* delts=delt; */
4722: /* for(k=1 ; k <kmax; k=k+1){ */
4723: /* delt = delti*(l1*k); */
4724: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4725: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4726: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4727: /* k1=func(p2)-fx; */
4728:
4729: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4730: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4731: /* k2=func(p2)-fx; */
4732:
4733: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4734: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4735: /* k3=func(p2)-fx; */
4736:
4737: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4738: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4739: /* k4=func(p2)-fx; */
4740: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4741: /* #ifdef DEBUGHESSIJ */
4742: /* 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); */
4743: /* 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); */
4744: /* #endif */
4745: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4746: /* k=kmax; */
4747: /* } */
4748: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4749: /* k=kmax; l=lmax*10; */
4750: /* } */
4751: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4752: /* delts=delt; */
4753: /* } */
4754: /* } /\* End loop k *\/ */
4755: /* } */
4756: /* delti[theta]=delts; */
4757: /* return res; */
4758: /* } */
4759:
4760:
1.126 brouard 4761: /************** Inverse of matrix **************/
4762: void ludcmp(double **a, int n, int *indx, double *d)
4763: {
4764: int i,imax,j,k;
4765: double big,dum,sum,temp;
4766: double *vv;
4767:
4768: vv=vector(1,n);
4769: *d=1.0;
4770: for (i=1;i<=n;i++) {
4771: big=0.0;
4772: for (j=1;j<=n;j++)
4773: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4774: if (big == 0.0){
4775: printf(" Singular Hessian matrix at row %d:\n",i);
4776: for (j=1;j<=n;j++) {
4777: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4778: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4779: }
4780: fflush(ficlog);
4781: fclose(ficlog);
4782: nrerror("Singular matrix in routine ludcmp");
4783: }
1.126 brouard 4784: vv[i]=1.0/big;
4785: }
4786: for (j=1;j<=n;j++) {
4787: for (i=1;i<j;i++) {
4788: sum=a[i][j];
4789: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4790: a[i][j]=sum;
4791: }
4792: big=0.0;
4793: for (i=j;i<=n;i++) {
4794: sum=a[i][j];
4795: for (k=1;k<j;k++)
4796: sum -= a[i][k]*a[k][j];
4797: a[i][j]=sum;
4798: if ( (dum=vv[i]*fabs(sum)) >= big) {
4799: big=dum;
4800: imax=i;
4801: }
4802: }
4803: if (j != imax) {
4804: for (k=1;k<=n;k++) {
4805: dum=a[imax][k];
4806: a[imax][k]=a[j][k];
4807: a[j][k]=dum;
4808: }
4809: *d = -(*d);
4810: vv[imax]=vv[j];
4811: }
4812: indx[j]=imax;
4813: if (a[j][j] == 0.0) a[j][j]=TINY;
4814: if (j != n) {
4815: dum=1.0/(a[j][j]);
4816: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4817: }
4818: }
4819: free_vector(vv,1,n); /* Doesn't work */
4820: ;
4821: }
4822:
4823: void lubksb(double **a, int n, int *indx, double b[])
4824: {
4825: int i,ii=0,ip,j;
4826: double sum;
4827:
4828: for (i=1;i<=n;i++) {
4829: ip=indx[i];
4830: sum=b[ip];
4831: b[ip]=b[i];
4832: if (ii)
4833: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4834: else if (sum) ii=i;
4835: b[i]=sum;
4836: }
4837: for (i=n;i>=1;i--) {
4838: sum=b[i];
4839: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4840: b[i]=sum/a[i][i];
4841: }
4842: }
4843:
4844: void pstamp(FILE *fichier)
4845: {
1.196 brouard 4846: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4847: }
4848:
1.297 brouard 4849: void date2dmy(double date,double *day, double *month, double *year){
4850: double yp=0., yp1=0., yp2=0.;
4851:
4852: yp1=modf(date,&yp);/* extracts integral of date in yp and
4853: fractional in yp1 */
4854: *year=yp;
4855: yp2=modf((yp1*12),&yp);
4856: *month=yp;
4857: yp1=modf((yp2*30.5),&yp);
4858: *day=yp;
4859: if(*day==0) *day=1;
4860: if(*month==0) *month=1;
4861: }
4862:
1.253 brouard 4863:
4864:
1.126 brouard 4865: /************ Frequencies ********************/
1.251 brouard 4866: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4867: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4868: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4869: { /* Some frequencies as well as proposing some starting values */
1.332 ! brouard 4870: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 4871: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4872: int iind=0, iage=0;
4873: int mi; /* Effective wave */
4874: int first;
4875: double ***freq; /* Frequencies */
1.268 brouard 4876: 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 */
4877: 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 4878: double *meanq, *stdq, *idq;
1.226 brouard 4879: double **meanqt;
4880: double *pp, **prop, *posprop, *pospropt;
4881: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4882: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4883: double agebegin, ageend;
4884:
4885: pp=vector(1,nlstate);
1.251 brouard 4886: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4887: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4888: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4889: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4890: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4891: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4892: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4893: meanqt=matrix(1,lastpass,1,nqtveff);
4894: strcpy(fileresp,"P_");
4895: strcat(fileresp,fileresu);
4896: /*strcat(fileresphtm,fileresu);*/
4897: if((ficresp=fopen(fileresp,"w"))==NULL) {
4898: printf("Problem with prevalence resultfile: %s\n", fileresp);
4899: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4900: exit(0);
4901: }
1.240 brouard 4902:
1.226 brouard 4903: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4904: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4905: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4906: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4907: fflush(ficlog);
4908: exit(70);
4909: }
4910: else{
4911: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4912: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4913: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4914: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4915: }
1.319 brouard 4916: 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 4917:
1.226 brouard 4918: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4919: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4920: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4921: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4922: fflush(ficlog);
4923: exit(70);
1.240 brouard 4924: } else{
1.226 brouard 4925: 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 4926: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4927: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4928: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4929: }
1.319 brouard 4930: 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 4931:
1.253 brouard 4932: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4933: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4934: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4935: j1=0;
1.126 brouard 4936:
1.227 brouard 4937: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4938: j=cptcoveff; /* Only dummy covariates of the model */
1.330 brouard 4939: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 4940: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4941:
4942:
1.226 brouard 4943: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4944: reference=low_education V1=0,V2=0
4945: med_educ V1=1 V2=0,
4946: high_educ V1=0 V2=1
1.330 brouard 4947: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 4948: */
1.249 brouard 4949: dateintsum=0;
4950: k2cpt=0;
4951:
1.253 brouard 4952: if(cptcoveff == 0 )
1.265 brouard 4953: nl=1; /* Constant and age model only */
1.253 brouard 4954: else
4955: nl=2;
1.265 brouard 4956:
4957: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4958: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.330 brouard 4959: * Loop on j1(1 to 2**cptcovn) covariate combination
1.265 brouard 4960: * freq[s1][s2][iage] =0.
4961: * Loop on iind
4962: * ++freq[s1][s2][iage] weighted
4963: * end iind
4964: * if covariate and j!0
4965: * headers Variable on one line
4966: * endif cov j!=0
4967: * header of frequency table by age
4968: * Loop on age
4969: * pp[s1]+=freq[s1][s2][iage] weighted
4970: * pos+=freq[s1][s2][iage] weighted
4971: * Loop on s1 initial state
4972: * fprintf(ficresp
4973: * end s1
4974: * end age
4975: * if j!=0 computes starting values
4976: * end compute starting values
4977: * end j1
4978: * end nl
4979: */
1.253 brouard 4980: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4981: if(nj==1)
4982: j=0; /* First pass for the constant */
1.265 brouard 4983: else{
1.330 brouard 4984: j=cptcovs; /* Other passes for the covariate values */
1.265 brouard 4985: }
1.251 brouard 4986: first=1;
1.332 ! brouard 4987: 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 4988: posproptt=0.;
1.330 brouard 4989: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 4990: scanf("%d", i);*/
4991: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4992: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4993: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4994: freq[i][s2][m]=0;
1.251 brouard 4995:
4996: for (i=1; i<=nlstate; i++) {
1.240 brouard 4997: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4998: prop[i][m]=0;
4999: posprop[i]=0;
5000: pospropt[i]=0;
5001: }
1.283 brouard 5002: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5003: idq[z1]=0.;
5004: meanq[z1]=0.;
5005: stdq[z1]=0.;
1.283 brouard 5006: }
5007: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5008: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5009: /* meanqt[m][z1]=0.; */
5010: /* } */
5011: /* } */
1.251 brouard 5012: /* dateintsum=0; */
5013: /* k2cpt=0; */
5014:
1.265 brouard 5015: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5016: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5017: bool=1;
5018: if(j !=0){
5019: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.330 brouard 5020: if (cptcovn >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5021: for (z1=1; z1<=cptcovn; z1++) { /* loops on covariates in the model */
1.251 brouard 5022: /* if(Tvaraff[z1] ==-20){ */
5023: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5024: /* }else if(Tvaraff[z1] ==-10){ */
5025: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5026: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.332 ! brouard 5027: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5028: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5029: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 ! brouard 5030: /* 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", */
! 5031: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
! 5032: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5033: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5034: } /* Onlyf fixed */
5035: } /* end z1 */
5036: } /* cptcovn > 0 */
5037: } /* end any */
5038: }/* end j==0 */
1.265 brouard 5039: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5040: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5041: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5042: m=mw[mi][iind];
5043: if(j!=0){
5044: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.330 brouard 5045: for (z1=1; z1<=cptcovn; z1++) {
1.251 brouard 5046: if( Fixed[Tmodelind[z1]]==1){
5047: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
1.332 ! brouard 5048: 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 5049: value is -1, we don't select. It differs from the
5050: constant and age model which counts them. */
5051: bool=0; /* not selected */
5052: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.332 ! brouard 5053: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.251 brouard 5054: bool=0;
5055: }
5056: }
5057: }
5058: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5059: } /* end j==0 */
5060: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5061: if(bool==1){ /*Selected */
1.251 brouard 5062: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5063: and mw[mi+1][iind]. dh depends on stepm. */
5064: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5065: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5066: if(m >=firstpass && m <=lastpass){
5067: k2=anint[m][iind]+(mint[m][iind]/12.);
5068: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5069: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5070: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5071: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5072: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5073: if (m<lastpass) {
5074: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5075: /* 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]); */
5076: if(s[m][iind]==-1)
5077: 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.));
5078: 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 5079: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5080: if(!isnan(covar[ncovcol+z1][iind])){
1.332 ! brouard 5081: idq[z1]=idq[z1]+weight[iind];
! 5082: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
! 5083: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
! 5084: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5085: }
1.284 brouard 5086: }
1.251 brouard 5087: /* if((int)agev[m][iind] == 55) */
5088: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5089: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5090: 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 5091: }
1.251 brouard 5092: } /* end if between passes */
5093: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5094: dateintsum=dateintsum+k2; /* on all covariates ?*/
5095: k2cpt++;
5096: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5097: }
1.251 brouard 5098: }else{
5099: bool=1;
5100: }/* end bool 2 */
5101: } /* end m */
1.284 brouard 5102: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5103: /* idq[z1]=idq[z1]+weight[iind]; */
5104: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5105: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5106: /* } */
1.251 brouard 5107: } /* end bool */
5108: } /* end iind = 1 to imx */
1.319 brouard 5109: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5110: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5111:
5112:
5113: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.330 brouard 5114: if(cptcovn==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5115: pstamp(ficresp);
1.330 brouard 5116: if (cptcovn>0 && j!=0){
1.265 brouard 5117: pstamp(ficresp);
1.251 brouard 5118: printf( "\n#********** Variable ");
5119: fprintf(ficresp, "\n#********** Variable ");
5120: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5121: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5122: fprintf(ficlog, "\n#********** Variable ");
1.330 brouard 5123: for (z1=1; z1<=cptcovs; z1++){
1.251 brouard 5124: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5125: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5126: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5127: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5128: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5129: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5130: }else{
1.330 brouard 5131: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5132: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5133: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5134: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5135: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5136: }
5137: }
5138: printf( "**********\n#");
5139: fprintf(ficresp, "**********\n#");
5140: fprintf(ficresphtm, "**********</h3>\n");
5141: fprintf(ficresphtmfr, "**********</h3>\n");
5142: fprintf(ficlog, "**********\n");
5143: }
1.284 brouard 5144: /*
5145: Printing means of quantitative variables if any
5146: */
5147: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5148: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5149: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5150: if(weightopt==1){
5151: printf(" Weighted mean and standard deviation of");
5152: fprintf(ficlog," Weighted mean and standard deviation of");
5153: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5154: }
1.311 brouard 5155: /* mu = \frac{w x}{\sum w}
5156: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5157: */
5158: 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]));
5159: 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]));
5160: 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 5161: }
5162: /* for (z1=1; z1<= nqtveff; z1++) { */
5163: /* for(m=1;m<=lastpass;m++){ */
5164: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5165: /* } */
5166: /* } */
1.283 brouard 5167:
1.251 brouard 5168: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.330 brouard 5169: if((cptcovn==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5170: fprintf(ficresp, " Age");
1.332 ! brouard 5171: if(nj==2) for (z1=1; z1<=cptcovn; z1++) fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5172: for(i=1; i<=nlstate;i++) {
1.330 brouard 5173: if((cptcovn==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5174: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5175: }
1.330 brouard 5176: if((cptcovn==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5177: fprintf(ficresphtm, "\n");
5178:
5179: /* Header of frequency table by age */
5180: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5181: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5182: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5183: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5184: if(s2!=0 && m!=0)
5185: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5186: }
1.226 brouard 5187: }
1.251 brouard 5188: fprintf(ficresphtmfr, "\n");
5189:
5190: /* For each age */
5191: for(iage=iagemin; iage <= iagemax+3; iage++){
5192: fprintf(ficresphtm,"<tr>");
5193: if(iage==iagemax+1){
5194: fprintf(ficlog,"1");
5195: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5196: }else if(iage==iagemax+2){
5197: fprintf(ficlog,"0");
5198: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5199: }else if(iage==iagemax+3){
5200: fprintf(ficlog,"Total");
5201: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5202: }else{
1.240 brouard 5203: if(first==1){
1.251 brouard 5204: first=0;
5205: printf("See log file for details...\n");
5206: }
5207: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5208: fprintf(ficlog,"Age %d", iage);
5209: }
1.265 brouard 5210: for(s1=1; s1 <=nlstate ; s1++){
5211: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5212: pp[s1] += freq[s1][m][iage];
1.251 brouard 5213: }
1.265 brouard 5214: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5215: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5216: pos += freq[s1][m][iage];
5217: if(pp[s1]>=1.e-10){
1.251 brouard 5218: if(first==1){
1.265 brouard 5219: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5220: }
1.265 brouard 5221: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5222: }else{
5223: if(first==1)
1.265 brouard 5224: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5225: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5226: }
5227: }
5228:
1.265 brouard 5229: for(s1=1; s1 <=nlstate ; s1++){
5230: /* posprop[s1]=0; */
5231: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5232: pp[s1] += freq[s1][m][iage];
5233: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5234:
5235: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5236: pos += pp[s1]; /* pos is the total number of transitions until this age */
5237: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5238: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5239: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5240: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5241: }
5242:
5243: /* Writing ficresp */
1.330 brouard 5244: if(cptcovn==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5245: if( iage <= iagemax){
5246: fprintf(ficresp," %d",iage);
5247: }
5248: }else if( nj==2){
5249: if( iage <= iagemax){
5250: fprintf(ficresp," %d",iage);
1.332 ! brouard 5251: for (z1=1; z1<=cptcovn; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5252: }
1.240 brouard 5253: }
1.265 brouard 5254: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5255: if(pos>=1.e-5){
1.251 brouard 5256: if(first==1)
1.265 brouard 5257: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5258: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5259: }else{
5260: if(first==1)
1.265 brouard 5261: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5262: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5263: }
5264: if( iage <= iagemax){
5265: if(pos>=1.e-5){
1.330 brouard 5266: if(cptcovn==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5267: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5268: }else if( nj==2){
5269: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5270: }
5271: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5272: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5273: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5274: } else{
1.330 brouard 5275: if((cptcovn==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5276: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5277: }
1.240 brouard 5278: }
1.265 brouard 5279: pospropt[s1] +=posprop[s1];
5280: } /* end loop s1 */
1.251 brouard 5281: /* pospropt=0.; */
1.265 brouard 5282: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5283: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5284: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5285: if(first==1){
1.265 brouard 5286: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5287: }
1.265 brouard 5288: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5289: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5290: }
1.265 brouard 5291: if(s1!=0 && m!=0)
5292: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5293: }
1.265 brouard 5294: } /* end loop s1 */
1.251 brouard 5295: posproptt=0.;
1.265 brouard 5296: for(s1=1; s1 <=nlstate; s1++){
5297: posproptt += pospropt[s1];
1.251 brouard 5298: }
5299: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5300: fprintf(ficresphtm,"</tr>\n");
1.330 brouard 5301: if((cptcovn==0 && nj==1)|| nj==2 ) {
1.265 brouard 5302: if(iage <= iagemax)
5303: fprintf(ficresp,"\n");
1.240 brouard 5304: }
1.251 brouard 5305: if(first==1)
5306: printf("Others in log...\n");
5307: fprintf(ficlog,"\n");
5308: } /* end loop age iage */
1.265 brouard 5309:
1.251 brouard 5310: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5311: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5312: if(posproptt < 1.e-5){
1.265 brouard 5313: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5314: }else{
1.265 brouard 5315: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5316: }
1.226 brouard 5317: }
1.251 brouard 5318: fprintf(ficresphtm,"</tr>\n");
5319: fprintf(ficresphtm,"</table>\n");
5320: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5321: if(posproptt < 1.e-5){
1.251 brouard 5322: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5323: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5324: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5325: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5326: invalidvarcomb[j1]=1;
1.226 brouard 5327: }else{
1.251 brouard 5328: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
5329: invalidvarcomb[j1]=0;
1.226 brouard 5330: }
1.251 brouard 5331: fprintf(ficresphtmfr,"</table>\n");
5332: fprintf(ficlog,"\n");
5333: if(j!=0){
5334: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5335: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5336: for(k=1; k <=(nlstate+ndeath); k++){
5337: if (k != i) {
1.265 brouard 5338: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5339: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5340: if(j1==1){ /* All dummy covariates to zero */
5341: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5342: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5343: printf("%d%d ",i,k);
5344: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5345: 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]));
5346: 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]));
5347: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5348: }
1.253 brouard 5349: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5350: for(iage=iagemin; iage <= iagemax+3; iage++){
5351: x[iage]= (double)iage;
5352: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5353: /* 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 5354: }
1.268 brouard 5355: /* Some are not finite, but linreg will ignore these ages */
5356: no=0;
1.253 brouard 5357: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5358: pstart[s1]=b;
5359: pstart[s1-1]=a;
1.252 brouard 5360: }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 */
5361: 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]);
5362: 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 5363: 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 5364: printf("%d%d ",i,k);
5365: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5366: 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 5367: }else{ /* Other cases, like quantitative fixed or varying covariates */
5368: ;
5369: }
5370: /* printf("%12.7f )", param[i][jj][k]); */
5371: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5372: s1++;
1.251 brouard 5373: } /* end jj */
5374: } /* end k!= i */
5375: } /* end k */
1.265 brouard 5376: } /* end i, s1 */
1.251 brouard 5377: } /* end j !=0 */
5378: } /* end selected combination of covariate j1 */
5379: if(j==0){ /* We can estimate starting values from the occurences in each case */
5380: printf("#Freqsummary: Starting values for the constants:\n");
5381: fprintf(ficlog,"\n");
1.265 brouard 5382: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5383: for(k=1; k <=(nlstate+ndeath); k++){
5384: if (k != i) {
5385: printf("%d%d ",i,k);
5386: fprintf(ficlog,"%d%d ",i,k);
5387: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5388: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5389: if(jj==1){ /* Age has to be done */
1.265 brouard 5390: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5391: 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]));
5392: 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 5393: }
5394: /* printf("%12.7f )", param[i][jj][k]); */
5395: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5396: s1++;
1.250 brouard 5397: }
1.251 brouard 5398: printf("\n");
5399: fprintf(ficlog,"\n");
1.250 brouard 5400: }
5401: }
1.284 brouard 5402: } /* end of state i */
1.251 brouard 5403: printf("#Freqsummary\n");
5404: fprintf(ficlog,"\n");
1.265 brouard 5405: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5406: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5407: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5408: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5409: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5410: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5411: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5412: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5413: /* } */
5414: }
1.265 brouard 5415: } /* end loop s1 */
1.251 brouard 5416:
5417: printf("\n");
5418: fprintf(ficlog,"\n");
5419: } /* end j=0 */
1.249 brouard 5420: } /* end j */
1.252 brouard 5421:
1.253 brouard 5422: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5423: for(i=1, jk=1; i <=nlstate; i++){
5424: for(j=1; j <=nlstate+ndeath; j++){
5425: if(j!=i){
5426: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5427: printf("%1d%1d",i,j);
5428: fprintf(ficparo,"%1d%1d",i,j);
5429: for(k=1; k<=ncovmodel;k++){
5430: /* printf(" %lf",param[i][j][k]); */
5431: /* fprintf(ficparo," %lf",param[i][j][k]); */
5432: p[jk]=pstart[jk];
5433: printf(" %f ",pstart[jk]);
5434: fprintf(ficparo," %f ",pstart[jk]);
5435: jk++;
5436: }
5437: printf("\n");
5438: fprintf(ficparo,"\n");
5439: }
5440: }
5441: }
5442: } /* end mle=-2 */
1.226 brouard 5443: dateintmean=dateintsum/k2cpt;
1.296 brouard 5444: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5445:
1.226 brouard 5446: fclose(ficresp);
5447: fclose(ficresphtm);
5448: fclose(ficresphtmfr);
1.283 brouard 5449: free_vector(idq,1,nqfveff);
1.226 brouard 5450: free_vector(meanq,1,nqfveff);
1.284 brouard 5451: free_vector(stdq,1,nqfveff);
1.226 brouard 5452: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5453: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5454: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5455: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5456: free_vector(pospropt,1,nlstate);
5457: free_vector(posprop,1,nlstate);
1.251 brouard 5458: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5459: free_vector(pp,1,nlstate);
5460: /* End of freqsummary */
5461: }
1.126 brouard 5462:
1.268 brouard 5463: /* Simple linear regression */
5464: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5465:
5466: /* y=a+bx regression */
5467: double sumx = 0.0; /* sum of x */
5468: double sumx2 = 0.0; /* sum of x**2 */
5469: double sumxy = 0.0; /* sum of x * y */
5470: double sumy = 0.0; /* sum of y */
5471: double sumy2 = 0.0; /* sum of y**2 */
5472: double sume2 = 0.0; /* sum of square or residuals */
5473: double yhat;
5474:
5475: double denom=0;
5476: int i;
5477: int ne=*no;
5478:
5479: for ( i=ifi, ne=0;i<=ila;i++) {
5480: if(!isfinite(x[i]) || !isfinite(y[i])){
5481: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5482: continue;
5483: }
5484: ne=ne+1;
5485: sumx += x[i];
5486: sumx2 += x[i]*x[i];
5487: sumxy += x[i] * y[i];
5488: sumy += y[i];
5489: sumy2 += y[i]*y[i];
5490: denom = (ne * sumx2 - sumx*sumx);
5491: /* 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); */
5492: }
5493:
5494: denom = (ne * sumx2 - sumx*sumx);
5495: if (denom == 0) {
5496: // vertical, slope m is infinity
5497: *b = INFINITY;
5498: *a = 0;
5499: if (r) *r = 0;
5500: return 1;
5501: }
5502:
5503: *b = (ne * sumxy - sumx * sumy) / denom;
5504: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5505: if (r!=NULL) {
5506: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5507: sqrt((sumx2 - sumx*sumx/ne) *
5508: (sumy2 - sumy*sumy/ne));
5509: }
5510: *no=ne;
5511: for ( i=ifi, ne=0;i<=ila;i++) {
5512: if(!isfinite(x[i]) || !isfinite(y[i])){
5513: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5514: continue;
5515: }
5516: ne=ne+1;
5517: yhat = y[i] - *a -*b* x[i];
5518: sume2 += yhat * yhat ;
5519:
5520: denom = (ne * sumx2 - sumx*sumx);
5521: /* 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); */
5522: }
5523: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5524: *sa= *sb * sqrt(sumx2/ne);
5525:
5526: return 0;
5527: }
5528:
1.126 brouard 5529: /************ Prevalence ********************/
1.227 brouard 5530: 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)
5531: {
5532: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5533: in each health status at the date of interview (if between dateprev1 and dateprev2).
5534: We still use firstpass and lastpass as another selection.
5535: */
1.126 brouard 5536:
1.227 brouard 5537: int i, m, jk, j1, bool, z1,j, iv;
5538: int mi; /* Effective wave */
5539: int iage;
5540: double agebegin, ageend;
5541:
5542: double **prop;
5543: double posprop;
5544: double y2; /* in fractional years */
5545: int iagemin, iagemax;
5546: int first; /** to stop verbosity which is redirected to log file */
5547:
5548: iagemin= (int) agemin;
5549: iagemax= (int) agemax;
5550: /*pp=vector(1,nlstate);*/
1.251 brouard 5551: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5552: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5553: j1=0;
1.222 brouard 5554:
1.227 brouard 5555: /*j=cptcoveff;*/
5556: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5557:
1.288 brouard 5558: first=0;
1.227 brouard 5559: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5560: for (i=1; i<=nlstate; i++)
1.251 brouard 5561: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5562: prop[i][iage]=0.0;
5563: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5564: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5565: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5566:
5567: for (i=1; i<=imx; i++) { /* Each individual */
5568: bool=1;
5569: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5570: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5571: m=mw[mi][i];
5572: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5573: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5574: for (z1=1; z1<=cptcoveff; z1++){
5575: if( Fixed[Tmodelind[z1]]==1){
5576: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
1.332 ! brouard 5577: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 5578: bool=0;
5579: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 ! brouard 5580: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 5581: bool=0;
5582: }
5583: }
5584: if(bool==1){ /* Otherwise we skip that wave/person */
5585: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5586: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5587: if(m >=firstpass && m <=lastpass){
5588: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5589: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5590: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5591: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5592: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5593: 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);
5594: exit(1);
5595: }
5596: if (s[m][i]>0 && s[m][i]<=nlstate) {
5597: /*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]]);*/
5598: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5599: prop[s[m][i]][iagemax+3] += weight[i];
5600: } /* end valid statuses */
5601: } /* end selection of dates */
5602: } /* end selection of waves */
5603: } /* end bool */
5604: } /* end wave */
5605: } /* end individual */
5606: for(i=iagemin; i <= iagemax+3; i++){
5607: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5608: posprop += prop[jk][i];
5609: }
5610:
5611: for(jk=1; jk <=nlstate ; jk++){
5612: if( i <= iagemax){
5613: if(posprop>=1.e-5){
5614: probs[i][jk][j1]= prop[jk][i]/posprop;
5615: } else{
1.288 brouard 5616: if(!first){
5617: first=1;
1.266 brouard 5618: 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]);
5619: }else{
1.288 brouard 5620: 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 5621: }
5622: }
5623: }
5624: }/* end jk */
5625: }/* end i */
1.222 brouard 5626: /*} *//* end i1 */
1.227 brouard 5627: } /* end j1 */
1.222 brouard 5628:
1.227 brouard 5629: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5630: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5631: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5632: } /* End of prevalence */
1.126 brouard 5633:
5634: /************* Waves Concatenation ***************/
5635:
5636: 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)
5637: {
1.298 brouard 5638: /* 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 5639: Death is a valid wave (if date is known).
5640: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5641: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 5642: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 5643: */
1.126 brouard 5644:
1.224 brouard 5645: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5646: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5647: double sum=0., jmean=0.;*/
1.224 brouard 5648: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5649: int j, k=0,jk, ju, jl;
5650: double sum=0.;
5651: first=0;
1.214 brouard 5652: firstwo=0;
1.217 brouard 5653: firsthree=0;
1.218 brouard 5654: firstfour=0;
1.164 brouard 5655: jmin=100000;
1.126 brouard 5656: jmax=-1;
5657: jmean=0.;
1.224 brouard 5658:
5659: /* Treating live states */
1.214 brouard 5660: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5661: mi=0; /* First valid wave */
1.227 brouard 5662: mli=0; /* Last valid wave */
1.309 brouard 5663: m=firstpass; /* Loop on waves */
5664: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 5665: 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 */
5666: mli=m-1;/* mw[++mi][i]=m-1; */
5667: }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 5668: 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 5669: mli=m;
1.224 brouard 5670: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5671: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5672: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5673: }
1.309 brouard 5674: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 5675: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5676: break;
1.224 brouard 5677: #else
1.317 brouard 5678: 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 5679: if(firsthree == 0){
1.302 brouard 5680: 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 5681: firsthree=1;
1.317 brouard 5682: }else if(firsthree >=1 && firsthree < 10){
5683: 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);
5684: firsthree++;
5685: }else if(firsthree == 10){
5686: printf("Information, too many Information flags: no more reported to log either\n");
5687: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
5688: firsthree++;
5689: }else{
5690: firsthree++;
1.227 brouard 5691: }
1.309 brouard 5692: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 5693: mli=m;
5694: }
5695: if(s[m][i]==-2){ /* Vital status is really unknown */
5696: nbwarn++;
1.309 brouard 5697: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 5698: 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);
5699: 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);
5700: }
5701: break;
5702: }
5703: break;
1.224 brouard 5704: #endif
1.227 brouard 5705: }/* End m >= lastpass */
1.126 brouard 5706: }/* end while */
1.224 brouard 5707:
1.227 brouard 5708: /* 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 5709: /* After last pass */
1.224 brouard 5710: /* Treating death states */
1.214 brouard 5711: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5712: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5713: /* } */
1.126 brouard 5714: mi++; /* Death is another wave */
5715: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5716: /* Only death is a correct wave */
1.126 brouard 5717: mw[mi][i]=m;
1.257 brouard 5718: } /* else not in a death state */
1.224 brouard 5719: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5720: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5721: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 5722: 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 5723: nbwarn++;
5724: if(firstfiv==0){
1.309 brouard 5725: 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 5726: firstfiv=1;
5727: }else{
1.309 brouard 5728: 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 5729: }
1.309 brouard 5730: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
5731: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 5732: nberr++;
5733: if(firstwo==0){
1.309 brouard 5734: 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 5735: firstwo=1;
5736: }
1.309 brouard 5737: 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 5738: }
1.257 brouard 5739: }else{ /* if date of interview is unknown */
1.227 brouard 5740: /* death is known but not confirmed by death status at any wave */
5741: if(firstfour==0){
1.309 brouard 5742: 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 5743: firstfour=1;
5744: }
1.309 brouard 5745: 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 5746: }
1.224 brouard 5747: } /* end if date of death is known */
5748: #endif
1.309 brouard 5749: wav[i]=mi; /* mi should be the last effective wave (or mli), */
5750: /* wav[i]=mw[mi][i]; */
1.126 brouard 5751: if(mi==0){
5752: nbwarn++;
5753: if(first==0){
1.227 brouard 5754: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5755: first=1;
1.126 brouard 5756: }
5757: if(first==1){
1.227 brouard 5758: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5759: }
5760: } /* end mi==0 */
5761: } /* End individuals */
1.214 brouard 5762: /* wav and mw are no more changed */
1.223 brouard 5763:
1.317 brouard 5764: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
5765: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
5766:
5767:
1.126 brouard 5768: for(i=1; i<=imx; i++){
5769: for(mi=1; mi<wav[i];mi++){
5770: if (stepm <=0)
1.227 brouard 5771: dh[mi][i]=1;
1.126 brouard 5772: else{
1.260 brouard 5773: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5774: if (agedc[i] < 2*AGESUP) {
5775: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5776: if(j==0) j=1; /* Survives at least one month after exam */
5777: else if(j<0){
5778: nberr++;
5779: 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]);
5780: j=1; /* Temporary Dangerous patch */
5781: 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);
5782: 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]);
5783: 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);
5784: }
5785: k=k+1;
5786: if (j >= jmax){
5787: jmax=j;
5788: ijmax=i;
5789: }
5790: if (j <= jmin){
5791: jmin=j;
5792: ijmin=i;
5793: }
5794: sum=sum+j;
5795: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5796: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5797: }
5798: }
5799: else{
5800: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5801: /* 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 5802:
1.227 brouard 5803: k=k+1;
5804: if (j >= jmax) {
5805: jmax=j;
5806: ijmax=i;
5807: }
5808: else if (j <= jmin){
5809: jmin=j;
5810: ijmin=i;
5811: }
5812: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5813: /*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]);*/
5814: if(j<0){
5815: nberr++;
5816: 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]);
5817: 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]);
5818: }
5819: sum=sum+j;
5820: }
5821: jk= j/stepm;
5822: jl= j -jk*stepm;
5823: ju= j -(jk+1)*stepm;
5824: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5825: if(jl==0){
5826: dh[mi][i]=jk;
5827: bh[mi][i]=0;
5828: }else{ /* We want a negative bias in order to only have interpolation ie
5829: * to avoid the price of an extra matrix product in likelihood */
5830: dh[mi][i]=jk+1;
5831: bh[mi][i]=ju;
5832: }
5833: }else{
5834: if(jl <= -ju){
5835: dh[mi][i]=jk;
5836: bh[mi][i]=jl; /* bias is positive if real duration
5837: * is higher than the multiple of stepm and negative otherwise.
5838: */
5839: }
5840: else{
5841: dh[mi][i]=jk+1;
5842: bh[mi][i]=ju;
5843: }
5844: if(dh[mi][i]==0){
5845: dh[mi][i]=1; /* At least one step */
5846: bh[mi][i]=ju; /* At least one step */
5847: /* 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);*/
5848: }
5849: } /* end if mle */
1.126 brouard 5850: }
5851: } /* end wave */
5852: }
5853: jmean=sum/k;
5854: 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 5855: 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 5856: }
1.126 brouard 5857:
5858: /*********** Tricode ****************************/
1.220 brouard 5859: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5860: {
5861: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5862: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5863: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5864: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5865: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5866: */
1.130 brouard 5867:
1.242 brouard 5868: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5869: int modmaxcovj=0; /* Modality max of covariates j */
5870: int cptcode=0; /* Modality max of covariates j */
5871: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5872:
5873:
1.242 brouard 5874: /* cptcoveff=0; */
5875: /* *cptcov=0; */
1.126 brouard 5876:
1.242 brouard 5877: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5878: for (k=1; k <= maxncov; k++)
5879: for(j=1; j<=2; j++)
5880: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5881:
1.242 brouard 5882: /* Loop on covariates without age and products and no quantitative variable */
5883: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5884: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5885: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5886: switch(Fixed[k]) {
5887: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 5888: modmaxcovj=0;
5889: modmincovj=0;
1.242 brouard 5890: 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*/
5891: ij=(int)(covar[Tvar[k]][i]);
5892: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5893: * If product of Vn*Vm, still boolean *:
5894: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5895: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5896: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5897: modality of the nth covariate of individual i. */
5898: if (ij > modmaxcovj)
5899: modmaxcovj=ij;
5900: else if (ij < modmincovj)
5901: modmincovj=ij;
1.287 brouard 5902: if (ij <0 || ij >1 ){
1.311 brouard 5903: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5904: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5905: fflush(ficlog);
5906: exit(1);
1.287 brouard 5907: }
5908: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5909: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5910: exit(1);
5911: }else
5912: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5913: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5914: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5915: /* getting the maximum value of the modality of the covariate
5916: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5917: female ies 1, then modmaxcovj=1.
5918: */
5919: } /* end for loop on individuals i */
5920: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5921: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5922: cptcode=modmaxcovj;
5923: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5924: /*for (i=0; i<=cptcode; i++) {*/
5925: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5926: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5927: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5928: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5929: if( j != -1){
5930: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5931: covariate for which somebody answered excluding
5932: undefined. Usually 2: 0 and 1. */
5933: }
5934: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5935: covariate for which somebody answered including
5936: undefined. Usually 3: -1, 0 and 1. */
5937: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5938: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5939: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5940:
1.242 brouard 5941: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5942: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5943: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5944: /* modmincovj=3; modmaxcovj = 7; */
5945: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5946: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5947: /* defining two dummy variables: variables V1_1 and V1_2.*/
5948: /* nbcode[Tvar[j]][ij]=k; */
5949: /* nbcode[Tvar[j]][1]=0; */
5950: /* nbcode[Tvar[j]][2]=1; */
5951: /* nbcode[Tvar[j]][3]=2; */
5952: /* To be continued (not working yet). */
5953: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5954:
5955: /* 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*/
5956: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5957: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5958: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5959: /*, could be restored in the future */
5960: 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 5961: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5962: break;
5963: }
5964: ij++;
1.287 brouard 5965: 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 5966: cptcode = ij; /* New max modality for covar j */
5967: } /* end of loop on modality i=-1 to 1 or more */
5968: break;
5969: case 1: /* Testing on varying covariate, could be simple and
5970: * should look at waves or product of fixed *
5971: * varying. No time to test -1, assuming 0 and 1 only */
5972: ij=0;
5973: for(i=0; i<=1;i++){
5974: nbcode[Tvar[k]][++ij]=i;
5975: }
5976: break;
5977: default:
5978: break;
5979: } /* end switch */
5980: } /* end dummy test */
1.311 brouard 5981: if(Dummy[k]==1 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5982: 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*/
5983: if(isnan(covar[Tvar[k]][i])){
5984: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5985: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5986: fflush(ficlog);
5987: exit(1);
5988: }
5989: }
5990: }
1.287 brouard 5991: } /* 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 5992:
5993: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5994: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5995: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5996: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5997: 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 */
5998: 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 */
5999: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6000: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6001:
6002: ij=0;
6003: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
6004: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
6005: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6006: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
6007: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
6008: /* If product not in single variable we don't print results */
6009: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
6010: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
6011: 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*/
6012: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6013: 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 */
6014: if(Fixed[k]!=0)
6015: anyvaryingduminmodel=1;
6016: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6017: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6018: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6019: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6020: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6021: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6022: }
6023: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6024: /* ij--; */
6025: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.330 brouard 6026: *cptcov=ij; /* cptcov= Number of total real effective covariates: effective (used as cptcoveff in other functions)
1.242 brouard 6027: * because they can be excluded from the model and real
6028: * if in the model but excluded because missing values, but how to get k from ij?*/
6029: for(j=ij+1; j<= cptcovt; j++){
6030: Tvaraff[j]=0;
6031: Tmodelind[j]=0;
6032: }
6033: for(j=ntveff+1; j<= cptcovt; j++){
6034: TmodelInvind[j]=0;
6035: }
6036: /* To be sorted */
6037: ;
6038: }
1.126 brouard 6039:
1.145 brouard 6040:
1.126 brouard 6041: /*********** Health Expectancies ****************/
6042:
1.235 brouard 6043: 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 6044:
6045: {
6046: /* Health expectancies, no variances */
1.329 brouard 6047: /* cij is the combination in the list of combination of dummy covariates */
6048: /* strstart is a string of time at start of computing */
1.164 brouard 6049: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6050: int nhstepma, nstepma; /* Decreasing with age */
6051: double age, agelim, hf;
6052: double ***p3mat;
6053: double eip;
6054:
1.238 brouard 6055: /* pstamp(ficreseij); */
1.126 brouard 6056: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6057: fprintf(ficreseij,"# Age");
6058: for(i=1; i<=nlstate;i++){
6059: for(j=1; j<=nlstate;j++){
6060: fprintf(ficreseij," e%1d%1d ",i,j);
6061: }
6062: fprintf(ficreseij," e%1d. ",i);
6063: }
6064: fprintf(ficreseij,"\n");
6065:
6066:
6067: if(estepm < stepm){
6068: printf ("Problem %d lower than %d\n",estepm, stepm);
6069: }
6070: else hstepm=estepm;
6071: /* We compute the life expectancy from trapezoids spaced every estepm months
6072: * This is mainly to measure the difference between two models: for example
6073: * if stepm=24 months pijx are given only every 2 years and by summing them
6074: * we are calculating an estimate of the Life Expectancy assuming a linear
6075: * progression in between and thus overestimating or underestimating according
6076: * to the curvature of the survival function. If, for the same date, we
6077: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6078: * to compare the new estimate of Life expectancy with the same linear
6079: * hypothesis. A more precise result, taking into account a more precise
6080: * curvature will be obtained if estepm is as small as stepm. */
6081:
6082: /* For example we decided to compute the life expectancy with the smallest unit */
6083: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6084: nhstepm is the number of hstepm from age to agelim
6085: nstepm is the number of stepm from age to agelin.
1.270 brouard 6086: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6087: and note for a fixed period like estepm months */
6088: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6089: survival function given by stepm (the optimization length). Unfortunately it
6090: means that if the survival funtion is printed only each two years of age and if
6091: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6092: results. So we changed our mind and took the option of the best precision.
6093: */
6094: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6095:
6096: agelim=AGESUP;
6097: /* If stepm=6 months */
6098: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6099: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6100:
6101: /* nhstepm age range expressed in number of stepm */
6102: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6103: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6104: /* if (stepm >= YEARM) hstepm=1;*/
6105: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6106: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6107:
6108: for (age=bage; age<=fage; age ++){
6109: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6110: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6111: /* if (stepm >= YEARM) hstepm=1;*/
6112: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6113:
6114: /* If stepm=6 months */
6115: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6116: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6117: /* 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 6118: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6119:
6120: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6121:
6122: printf("%d|",(int)age);fflush(stdout);
6123: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6124:
6125: /* Computing expectancies */
6126: for(i=1; i<=nlstate;i++)
6127: for(j=1; j<=nlstate;j++)
6128: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6129: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6130:
6131: /* 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]);*/
6132:
6133: }
6134:
6135: fprintf(ficreseij,"%3.0f",age );
6136: for(i=1; i<=nlstate;i++){
6137: eip=0;
6138: for(j=1; j<=nlstate;j++){
6139: eip +=eij[i][j][(int)age];
6140: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6141: }
6142: fprintf(ficreseij,"%9.4f", eip );
6143: }
6144: fprintf(ficreseij,"\n");
6145:
6146: }
6147: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6148: printf("\n");
6149: fprintf(ficlog,"\n");
6150:
6151: }
6152:
1.235 brouard 6153: 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 6154:
6155: {
6156: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6157: to initial status i, ei. .
1.126 brouard 6158: */
6159: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6160: int nhstepma, nstepma; /* Decreasing with age */
6161: double age, agelim, hf;
6162: double ***p3matp, ***p3matm, ***varhe;
6163: double **dnewm,**doldm;
6164: double *xp, *xm;
6165: double **gp, **gm;
6166: double ***gradg, ***trgradg;
6167: int theta;
6168:
6169: double eip, vip;
6170:
6171: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6172: xp=vector(1,npar);
6173: xm=vector(1,npar);
6174: dnewm=matrix(1,nlstate*nlstate,1,npar);
6175: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6176:
6177: pstamp(ficresstdeij);
6178: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6179: fprintf(ficresstdeij,"# Age");
6180: for(i=1; i<=nlstate;i++){
6181: for(j=1; j<=nlstate;j++)
6182: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6183: fprintf(ficresstdeij," e%1d. ",i);
6184: }
6185: fprintf(ficresstdeij,"\n");
6186:
6187: pstamp(ficrescveij);
6188: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6189: fprintf(ficrescveij,"# Age");
6190: for(i=1; i<=nlstate;i++)
6191: for(j=1; j<=nlstate;j++){
6192: cptj= (j-1)*nlstate+i;
6193: for(i2=1; i2<=nlstate;i2++)
6194: for(j2=1; j2<=nlstate;j2++){
6195: cptj2= (j2-1)*nlstate+i2;
6196: if(cptj2 <= cptj)
6197: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6198: }
6199: }
6200: fprintf(ficrescveij,"\n");
6201:
6202: if(estepm < stepm){
6203: printf ("Problem %d lower than %d\n",estepm, stepm);
6204: }
6205: else hstepm=estepm;
6206: /* We compute the life expectancy from trapezoids spaced every estepm months
6207: * This is mainly to measure the difference between two models: for example
6208: * if stepm=24 months pijx are given only every 2 years and by summing them
6209: * we are calculating an estimate of the Life Expectancy assuming a linear
6210: * progression in between and thus overestimating or underestimating according
6211: * to the curvature of the survival function. If, for the same date, we
6212: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6213: * to compare the new estimate of Life expectancy with the same linear
6214: * hypothesis. A more precise result, taking into account a more precise
6215: * curvature will be obtained if estepm is as small as stepm. */
6216:
6217: /* For example we decided to compute the life expectancy with the smallest unit */
6218: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6219: nhstepm is the number of hstepm from age to agelim
6220: nstepm is the number of stepm from age to agelin.
6221: Look at hpijx to understand the reason of that which relies in memory size
6222: and note for a fixed period like estepm months */
6223: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6224: survival function given by stepm (the optimization length). Unfortunately it
6225: means that if the survival funtion is printed only each two years of age and if
6226: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6227: results. So we changed our mind and took the option of the best precision.
6228: */
6229: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6230:
6231: /* If stepm=6 months */
6232: /* nhstepm age range expressed in number of stepm */
6233: agelim=AGESUP;
6234: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6235: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6236: /* if (stepm >= YEARM) hstepm=1;*/
6237: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6238:
6239: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6240: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6241: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6242: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6243: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6244: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6245:
6246: for (age=bage; age<=fage; age ++){
6247: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6248: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6249: /* if (stepm >= YEARM) hstepm=1;*/
6250: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6251:
1.126 brouard 6252: /* If stepm=6 months */
6253: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6254: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6255:
6256: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6257:
1.126 brouard 6258: /* Computing Variances of health expectancies */
6259: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6260: decrease memory allocation */
6261: for(theta=1; theta <=npar; theta++){
6262: for(i=1; i<=npar; i++){
1.222 brouard 6263: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6264: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6265: }
1.235 brouard 6266: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6267: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6268:
1.126 brouard 6269: for(j=1; j<= nlstate; j++){
1.222 brouard 6270: for(i=1; i<=nlstate; i++){
6271: for(h=0; h<=nhstepm-1; h++){
6272: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6273: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6274: }
6275: }
1.126 brouard 6276: }
1.218 brouard 6277:
1.126 brouard 6278: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6279: for(h=0; h<=nhstepm-1; h++){
6280: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6281: }
1.126 brouard 6282: }/* End theta */
6283:
6284:
6285: for(h=0; h<=nhstepm-1; h++)
6286: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6287: for(theta=1; theta <=npar; theta++)
6288: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6289:
1.218 brouard 6290:
1.222 brouard 6291: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6292: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6293: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6294:
1.222 brouard 6295: printf("%d|",(int)age);fflush(stdout);
6296: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6297: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6298: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6299: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6300: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6301: for(ij=1;ij<=nlstate*nlstate;ij++)
6302: for(ji=1;ji<=nlstate*nlstate;ji++)
6303: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6304: }
6305: }
1.320 brouard 6306: /* if((int)age ==50){ */
6307: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6308: /* } */
1.126 brouard 6309: /* Computing expectancies */
1.235 brouard 6310: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6311: for(i=1; i<=nlstate;i++)
6312: for(j=1; j<=nlstate;j++)
1.222 brouard 6313: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6314: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6315:
1.222 brouard 6316: /* 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 6317:
1.222 brouard 6318: }
1.269 brouard 6319:
6320: /* Standard deviation of expectancies ij */
1.126 brouard 6321: fprintf(ficresstdeij,"%3.0f",age );
6322: for(i=1; i<=nlstate;i++){
6323: eip=0.;
6324: vip=0.;
6325: for(j=1; j<=nlstate;j++){
1.222 brouard 6326: eip += eij[i][j][(int)age];
6327: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6328: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6329: 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 6330: }
6331: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6332: }
6333: fprintf(ficresstdeij,"\n");
1.218 brouard 6334:
1.269 brouard 6335: /* Variance of expectancies ij */
1.126 brouard 6336: fprintf(ficrescveij,"%3.0f",age );
6337: for(i=1; i<=nlstate;i++)
6338: for(j=1; j<=nlstate;j++){
1.222 brouard 6339: cptj= (j-1)*nlstate+i;
6340: for(i2=1; i2<=nlstate;i2++)
6341: for(j2=1; j2<=nlstate;j2++){
6342: cptj2= (j2-1)*nlstate+i2;
6343: if(cptj2 <= cptj)
6344: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6345: }
1.126 brouard 6346: }
6347: fprintf(ficrescveij,"\n");
1.218 brouard 6348:
1.126 brouard 6349: }
6350: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6351: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6352: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6353: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6354: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6355: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6356: printf("\n");
6357: fprintf(ficlog,"\n");
1.218 brouard 6358:
1.126 brouard 6359: free_vector(xm,1,npar);
6360: free_vector(xp,1,npar);
6361: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6362: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6363: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6364: }
1.218 brouard 6365:
1.126 brouard 6366: /************ Variance ******************/
1.235 brouard 6367: 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 6368: {
1.279 brouard 6369: /** Variance of health expectancies
6370: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6371: * double **newm;
6372: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6373: */
1.218 brouard 6374:
6375: /* int movingaverage(); */
6376: double **dnewm,**doldm;
6377: double **dnewmp,**doldmp;
6378: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6379: int first=0;
1.218 brouard 6380: int k;
6381: double *xp;
1.279 brouard 6382: double **gp, **gm; /**< for var eij */
6383: double ***gradg, ***trgradg; /**< for var eij */
6384: double **gradgp, **trgradgp; /**< for var p point j */
6385: double *gpp, *gmp; /**< for var p point j */
6386: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6387: double ***p3mat;
6388: double age,agelim, hf;
6389: /* double ***mobaverage; */
6390: int theta;
6391: char digit[4];
6392: char digitp[25];
6393:
6394: char fileresprobmorprev[FILENAMELENGTH];
6395:
6396: if(popbased==1){
6397: if(mobilav!=0)
6398: strcpy(digitp,"-POPULBASED-MOBILAV_");
6399: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6400: }
6401: else
6402: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6403:
1.218 brouard 6404: /* if (mobilav!=0) { */
6405: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6406: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
6407: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
6408: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
6409: /* } */
6410: /* } */
6411:
6412: strcpy(fileresprobmorprev,"PRMORPREV-");
6413: sprintf(digit,"%-d",ij);
6414: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
6415: strcat(fileresprobmorprev,digit); /* Tvar to be done */
6416: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
6417: strcat(fileresprobmorprev,fileresu);
6418: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
6419: printf("Problem with resultfile: %s\n", fileresprobmorprev);
6420: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
6421: }
6422: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6423: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6424: pstamp(ficresprobmorprev);
6425: 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 6426: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
6427: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 ! brouard 6428: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
1.238 brouard 6429: }
6430: for(j=1;j<=cptcoveff;j++)
1.332 ! brouard 6431: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]);
1.238 brouard 6432: fprintf(ficresprobmorprev,"\n");
6433:
1.218 brouard 6434: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
6435: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6436: fprintf(ficresprobmorprev," p.%-d SE",j);
6437: for(i=1; i<=nlstate;i++)
6438: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
6439: }
6440: fprintf(ficresprobmorprev,"\n");
6441:
6442: fprintf(ficgp,"\n# Routine varevsij");
6443: fprintf(ficgp,"\nunset title \n");
6444: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
6445: 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");
6446: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 6447:
1.218 brouard 6448: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6449: pstamp(ficresvij);
6450: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
6451: if(popbased==1)
6452: 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);
6453: else
6454: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6455: fprintf(ficresvij,"# Age");
6456: for(i=1; i<=nlstate;i++)
6457: for(j=1; j<=nlstate;j++)
6458: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6459: fprintf(ficresvij,"\n");
6460:
6461: xp=vector(1,npar);
6462: dnewm=matrix(1,nlstate,1,npar);
6463: doldm=matrix(1,nlstate,1,nlstate);
6464: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6465: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6466:
6467: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6468: gpp=vector(nlstate+1,nlstate+ndeath);
6469: gmp=vector(nlstate+1,nlstate+ndeath);
6470: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6471:
1.218 brouard 6472: if(estepm < stepm){
6473: printf ("Problem %d lower than %d\n",estepm, stepm);
6474: }
6475: else hstepm=estepm;
6476: /* For example we decided to compute the life expectancy with the smallest unit */
6477: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6478: nhstepm is the number of hstepm from age to agelim
6479: nstepm is the number of stepm from age to agelim.
6480: Look at function hpijx to understand why because of memory size limitations,
6481: we decided (b) to get a life expectancy respecting the most precise curvature of the
6482: survival function given by stepm (the optimization length). Unfortunately it
6483: means that if the survival funtion is printed every two years of age and if
6484: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6485: results. So we changed our mind and took the option of the best precision.
6486: */
6487: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6488: agelim = AGESUP;
6489: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6490: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6491: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6492: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6493: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6494: gp=matrix(0,nhstepm,1,nlstate);
6495: gm=matrix(0,nhstepm,1,nlstate);
6496:
6497:
6498: for(theta=1; theta <=npar; theta++){
6499: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6500: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6501: }
1.279 brouard 6502: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6503: * returns into prlim .
1.288 brouard 6504: */
1.242 brouard 6505: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6506:
6507: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6508: if (popbased==1) {
6509: if(mobilav ==0){
6510: for(i=1; i<=nlstate;i++)
6511: prlim[i][i]=probs[(int)age][i][ij];
6512: }else{ /* mobilav */
6513: for(i=1; i<=nlstate;i++)
6514: prlim[i][i]=mobaverage[(int)age][i][ij];
6515: }
6516: }
1.295 brouard 6517: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6518: */
6519: 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 6520: /**< 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 6521: * at horizon h in state j including mortality.
6522: */
1.218 brouard 6523: for(j=1; j<= nlstate; j++){
6524: for(h=0; h<=nhstepm; h++){
6525: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6526: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6527: }
6528: }
1.279 brouard 6529: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6530: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6531: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6532: */
6533: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6534: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6535: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6536: }
6537:
6538: /* Again with minus shift */
1.218 brouard 6539:
6540: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6541: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6542:
1.242 brouard 6543: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6544:
6545: if (popbased==1) {
6546: if(mobilav ==0){
6547: for(i=1; i<=nlstate;i++)
6548: prlim[i][i]=probs[(int)age][i][ij];
6549: }else{ /* mobilav */
6550: for(i=1; i<=nlstate;i++)
6551: prlim[i][i]=mobaverage[(int)age][i][ij];
6552: }
6553: }
6554:
1.235 brouard 6555: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6556:
6557: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6558: for(h=0; h<=nhstepm; h++){
6559: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6560: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6561: }
6562: }
6563: /* This for computing probability of death (h=1 means
6564: computed over hstepm matrices product = hstepm*stepm months)
6565: as a weighted average of prlim.
6566: */
6567: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6568: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6569: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6570: }
1.279 brouard 6571: /* end shifting computations */
6572:
6573: /**< Computing gradient matrix at horizon h
6574: */
1.218 brouard 6575: for(j=1; j<= nlstate; j++) /* vareij */
6576: for(h=0; h<=nhstepm; h++){
6577: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6578: }
1.279 brouard 6579: /**< Gradient of overall mortality p.3 (or p.j)
6580: */
6581: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6582: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6583: }
6584:
6585: } /* End theta */
1.279 brouard 6586:
6587: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6588: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6589:
6590: for(h=0; h<=nhstepm; h++) /* veij */
6591: for(j=1; j<=nlstate;j++)
6592: for(theta=1; theta <=npar; theta++)
6593: trgradg[h][j][theta]=gradg[h][theta][j];
6594:
6595: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6596: for(theta=1; theta <=npar; theta++)
6597: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6598: /**< as well as its transposed matrix
6599: */
1.218 brouard 6600:
6601: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6602: for(i=1;i<=nlstate;i++)
6603: for(j=1;j<=nlstate;j++)
6604: vareij[i][j][(int)age] =0.;
1.279 brouard 6605:
6606: /* Computing trgradg by matcov by gradg at age and summing over h
6607: * and k (nhstepm) formula 15 of article
6608: * Lievre-Brouard-Heathcote
6609: */
6610:
1.218 brouard 6611: for(h=0;h<=nhstepm;h++){
6612: for(k=0;k<=nhstepm;k++){
6613: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6614: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6615: for(i=1;i<=nlstate;i++)
6616: for(j=1;j<=nlstate;j++)
6617: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6618: }
6619: }
6620:
1.279 brouard 6621: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6622: * p.j overall mortality formula 49 but computed directly because
6623: * we compute the grad (wix pijx) instead of grad (pijx),even if
6624: * wix is independent of theta.
6625: */
1.218 brouard 6626: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6627: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6628: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6629: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6630: varppt[j][i]=doldmp[j][i];
6631: /* end ppptj */
6632: /* x centered again */
6633:
1.242 brouard 6634: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6635:
6636: if (popbased==1) {
6637: if(mobilav ==0){
6638: for(i=1; i<=nlstate;i++)
6639: prlim[i][i]=probs[(int)age][i][ij];
6640: }else{ /* mobilav */
6641: for(i=1; i<=nlstate;i++)
6642: prlim[i][i]=mobaverage[(int)age][i][ij];
6643: }
6644: }
6645:
6646: /* This for computing probability of death (h=1 means
6647: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6648: as a weighted average of prlim.
6649: */
1.235 brouard 6650: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6651: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6652: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6653: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6654: }
6655: /* end probability of death */
6656:
6657: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6658: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6659: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6660: for(i=1; i<=nlstate;i++){
6661: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6662: }
6663: }
6664: fprintf(ficresprobmorprev,"\n");
6665:
6666: fprintf(ficresvij,"%.0f ",age );
6667: for(i=1; i<=nlstate;i++)
6668: for(j=1; j<=nlstate;j++){
6669: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6670: }
6671: fprintf(ficresvij,"\n");
6672: free_matrix(gp,0,nhstepm,1,nlstate);
6673: free_matrix(gm,0,nhstepm,1,nlstate);
6674: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6675: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6676: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6677: } /* End age */
6678: free_vector(gpp,nlstate+1,nlstate+ndeath);
6679: free_vector(gmp,nlstate+1,nlstate+ndeath);
6680: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6681: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6682: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6683: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6684: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6685: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6686: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6687: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6688: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6689: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6690: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6691: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6692: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6693: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6694: 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);
6695: /* 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 6696: */
1.218 brouard 6697: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6698: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6699:
1.218 brouard 6700: free_vector(xp,1,npar);
6701: free_matrix(doldm,1,nlstate,1,nlstate);
6702: free_matrix(dnewm,1,nlstate,1,npar);
6703: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6704: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6705: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6706: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6707: fclose(ficresprobmorprev);
6708: fflush(ficgp);
6709: fflush(fichtm);
6710: } /* end varevsij */
1.126 brouard 6711:
6712: /************ Variance of prevlim ******************/
1.269 brouard 6713: 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 6714: {
1.205 brouard 6715: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6716: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6717:
1.268 brouard 6718: double **dnewmpar,**doldm;
1.126 brouard 6719: int i, j, nhstepm, hstepm;
6720: double *xp;
6721: double *gp, *gm;
6722: double **gradg, **trgradg;
1.208 brouard 6723: double **mgm, **mgp;
1.126 brouard 6724: double age,agelim;
6725: int theta;
6726:
6727: pstamp(ficresvpl);
1.288 brouard 6728: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6729: fprintf(ficresvpl,"# Age ");
6730: if(nresult >=1)
6731: fprintf(ficresvpl," Result# ");
1.126 brouard 6732: for(i=1; i<=nlstate;i++)
6733: fprintf(ficresvpl," %1d-%1d",i,i);
6734: fprintf(ficresvpl,"\n");
6735:
6736: xp=vector(1,npar);
1.268 brouard 6737: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6738: doldm=matrix(1,nlstate,1,nlstate);
6739:
6740: hstepm=1*YEARM; /* Every year of age */
6741: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6742: agelim = AGESUP;
6743: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6744: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6745: if (stepm >= YEARM) hstepm=1;
6746: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6747: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6748: mgp=matrix(1,npar,1,nlstate);
6749: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6750: gp=vector(1,nlstate);
6751: gm=vector(1,nlstate);
6752:
6753: for(theta=1; theta <=npar; theta++){
6754: for(i=1; i<=npar; i++){ /* Computes gradient */
6755: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6756: }
1.288 brouard 6757: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6758: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6759: /* else */
6760: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6761: for(i=1;i<=nlstate;i++){
1.126 brouard 6762: gp[i] = prlim[i][i];
1.208 brouard 6763: mgp[theta][i] = prlim[i][i];
6764: }
1.126 brouard 6765: for(i=1; i<=npar; i++) /* Computes gradient */
6766: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6767: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6768: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6769: /* else */
6770: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6771: for(i=1;i<=nlstate;i++){
1.126 brouard 6772: gm[i] = prlim[i][i];
1.208 brouard 6773: mgm[theta][i] = prlim[i][i];
6774: }
1.126 brouard 6775: for(i=1;i<=nlstate;i++)
6776: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6777: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6778: } /* End theta */
6779:
6780: trgradg =matrix(1,nlstate,1,npar);
6781:
6782: for(j=1; j<=nlstate;j++)
6783: for(theta=1; theta <=npar; theta++)
6784: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6785: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6786: /* printf("\nmgm mgp %d ",(int)age); */
6787: /* for(j=1; j<=nlstate;j++){ */
6788: /* printf(" %d ",j); */
6789: /* for(theta=1; theta <=npar; theta++) */
6790: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6791: /* printf("\n "); */
6792: /* } */
6793: /* } */
6794: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6795: /* printf("\n gradg %d ",(int)age); */
6796: /* for(j=1; j<=nlstate;j++){ */
6797: /* printf("%d ",j); */
6798: /* for(theta=1; theta <=npar; theta++) */
6799: /* printf("%d %lf ",theta,gradg[theta][j]); */
6800: /* printf("\n "); */
6801: /* } */
6802: /* } */
1.126 brouard 6803:
6804: for(i=1;i<=nlstate;i++)
6805: varpl[i][(int)age] =0.;
1.209 brouard 6806: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6807: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6808: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6809: }else{
1.268 brouard 6810: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6811: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6812: }
1.126 brouard 6813: for(i=1;i<=nlstate;i++)
6814: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6815:
6816: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6817: if(nresult >=1)
6818: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6819: for(i=1; i<=nlstate;i++){
1.126 brouard 6820: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6821: /* for(j=1;j<=nlstate;j++) */
6822: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6823: }
1.126 brouard 6824: fprintf(ficresvpl,"\n");
6825: free_vector(gp,1,nlstate);
6826: free_vector(gm,1,nlstate);
1.208 brouard 6827: free_matrix(mgm,1,npar,1,nlstate);
6828: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6829: free_matrix(gradg,1,npar,1,nlstate);
6830: free_matrix(trgradg,1,nlstate,1,npar);
6831: } /* End age */
6832:
6833: free_vector(xp,1,npar);
6834: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6835: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6836:
6837: }
6838:
6839:
6840: /************ Variance of backprevalence limit ******************/
1.269 brouard 6841: 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 6842: {
6843: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6844: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6845:
6846: double **dnewmpar,**doldm;
6847: int i, j, nhstepm, hstepm;
6848: double *xp;
6849: double *gp, *gm;
6850: double **gradg, **trgradg;
6851: double **mgm, **mgp;
6852: double age,agelim;
6853: int theta;
6854:
6855: pstamp(ficresvbl);
6856: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6857: fprintf(ficresvbl,"# Age ");
6858: if(nresult >=1)
6859: fprintf(ficresvbl," Result# ");
6860: for(i=1; i<=nlstate;i++)
6861: fprintf(ficresvbl," %1d-%1d",i,i);
6862: fprintf(ficresvbl,"\n");
6863:
6864: xp=vector(1,npar);
6865: dnewmpar=matrix(1,nlstate,1,npar);
6866: doldm=matrix(1,nlstate,1,nlstate);
6867:
6868: hstepm=1*YEARM; /* Every year of age */
6869: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6870: agelim = AGEINF;
6871: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6872: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6873: if (stepm >= YEARM) hstepm=1;
6874: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6875: gradg=matrix(1,npar,1,nlstate);
6876: mgp=matrix(1,npar,1,nlstate);
6877: mgm=matrix(1,npar,1,nlstate);
6878: gp=vector(1,nlstate);
6879: gm=vector(1,nlstate);
6880:
6881: for(theta=1; theta <=npar; theta++){
6882: for(i=1; i<=npar; i++){ /* Computes gradient */
6883: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6884: }
6885: if(mobilavproj > 0 )
6886: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6887: else
6888: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6889: for(i=1;i<=nlstate;i++){
6890: gp[i] = bprlim[i][i];
6891: mgp[theta][i] = bprlim[i][i];
6892: }
6893: for(i=1; i<=npar; i++) /* Computes gradient */
6894: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6895: if(mobilavproj > 0 )
6896: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6897: else
6898: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6899: for(i=1;i<=nlstate;i++){
6900: gm[i] = bprlim[i][i];
6901: mgm[theta][i] = bprlim[i][i];
6902: }
6903: for(i=1;i<=nlstate;i++)
6904: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6905: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6906: } /* End theta */
6907:
6908: trgradg =matrix(1,nlstate,1,npar);
6909:
6910: for(j=1; j<=nlstate;j++)
6911: for(theta=1; theta <=npar; theta++)
6912: trgradg[j][theta]=gradg[theta][j];
6913: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6914: /* printf("\nmgm mgp %d ",(int)age); */
6915: /* for(j=1; j<=nlstate;j++){ */
6916: /* printf(" %d ",j); */
6917: /* for(theta=1; theta <=npar; theta++) */
6918: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6919: /* printf("\n "); */
6920: /* } */
6921: /* } */
6922: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6923: /* printf("\n gradg %d ",(int)age); */
6924: /* for(j=1; j<=nlstate;j++){ */
6925: /* printf("%d ",j); */
6926: /* for(theta=1; theta <=npar; theta++) */
6927: /* printf("%d %lf ",theta,gradg[theta][j]); */
6928: /* printf("\n "); */
6929: /* } */
6930: /* } */
6931:
6932: for(i=1;i<=nlstate;i++)
6933: varbpl[i][(int)age] =0.;
6934: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6935: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6936: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6937: }else{
6938: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6939: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6940: }
6941: for(i=1;i<=nlstate;i++)
6942: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6943:
6944: fprintf(ficresvbl,"%.0f ",age );
6945: if(nresult >=1)
6946: fprintf(ficresvbl,"%d ",nres );
6947: for(i=1; i<=nlstate;i++)
6948: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6949: fprintf(ficresvbl,"\n");
6950: free_vector(gp,1,nlstate);
6951: free_vector(gm,1,nlstate);
6952: free_matrix(mgm,1,npar,1,nlstate);
6953: free_matrix(mgp,1,npar,1,nlstate);
6954: free_matrix(gradg,1,npar,1,nlstate);
6955: free_matrix(trgradg,1,nlstate,1,npar);
6956: } /* End age */
6957:
6958: free_vector(xp,1,npar);
6959: free_matrix(doldm,1,nlstate,1,npar);
6960: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6961:
6962: }
6963:
6964: /************ Variance of one-step probabilities ******************/
6965: 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 6966: {
6967: int i, j=0, k1, l1, tj;
6968: int k2, l2, j1, z1;
6969: int k=0, l;
6970: int first=1, first1, first2;
1.326 brouard 6971: int nres=0; /* New */
1.222 brouard 6972: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6973: double **dnewm,**doldm;
6974: double *xp;
6975: double *gp, *gm;
6976: double **gradg, **trgradg;
6977: double **mu;
6978: double age, cov[NCOVMAX+1];
6979: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6980: int theta;
6981: char fileresprob[FILENAMELENGTH];
6982: char fileresprobcov[FILENAMELENGTH];
6983: char fileresprobcor[FILENAMELENGTH];
6984: double ***varpij;
6985:
6986: strcpy(fileresprob,"PROB_");
6987: strcat(fileresprob,fileres);
6988: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6989: printf("Problem with resultfile: %s\n", fileresprob);
6990: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6991: }
6992: strcpy(fileresprobcov,"PROBCOV_");
6993: strcat(fileresprobcov,fileresu);
6994: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6995: printf("Problem with resultfile: %s\n", fileresprobcov);
6996: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6997: }
6998: strcpy(fileresprobcor,"PROBCOR_");
6999: strcat(fileresprobcor,fileresu);
7000: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7001: printf("Problem with resultfile: %s\n", fileresprobcor);
7002: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7003: }
7004: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7005: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7006: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7007: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7008: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7009: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7010: pstamp(ficresprob);
7011: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7012: fprintf(ficresprob,"# Age");
7013: pstamp(ficresprobcov);
7014: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7015: fprintf(ficresprobcov,"# Age");
7016: pstamp(ficresprobcor);
7017: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7018: fprintf(ficresprobcor,"# Age");
1.126 brouard 7019:
7020:
1.222 brouard 7021: for(i=1; i<=nlstate;i++)
7022: for(j=1; j<=(nlstate+ndeath);j++){
7023: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7024: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7025: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7026: }
7027: /* fprintf(ficresprob,"\n");
7028: fprintf(ficresprobcov,"\n");
7029: fprintf(ficresprobcor,"\n");
7030: */
7031: xp=vector(1,npar);
7032: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7033: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7034: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7035: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7036: first=1;
7037: fprintf(ficgp,"\n# Routine varprob");
7038: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7039: fprintf(fichtm,"\n");
7040:
1.288 brouard 7041: 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 7042: 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);
7043: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7044: and drawn. It helps understanding how is the covariance between two incidences.\
7045: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7046: 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 7047: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7048: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7049: standard deviations wide on each axis. <br>\
7050: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7051: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7052: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7053:
1.222 brouard 7054: cov[1]=1;
7055: /* tj=cptcoveff; */
1.225 brouard 7056: tj = (int) pow(2,cptcoveff);
1.222 brouard 7057: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7058: j1=0;
1.332 ! brouard 7059:
! 7060: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
! 7061: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
! 7062: printf("Varprob TKresult[nres]=%d j1=%d, nres=%d, cptcovn=%d, cptcoveff=%d tj=%d \n", TKresult[nres], j1, nres, cptcovn, cptcoveff, tj);
! 7063: if(tj != 1 && TKresult[nres]!= j1)
! 7064: continue;
! 7065:
! 7066: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
! 7067: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
! 7068: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7069: if (cptcovn>0) {
7070: fprintf(ficresprob, "\n#********** Variable ");
1.332 ! brouard 7071: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.222 brouard 7072: fprintf(ficresprob, "**********\n#\n");
7073: fprintf(ficresprobcov, "\n#********** Variable ");
1.332 ! brouard 7074: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.222 brouard 7075: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 7076:
1.222 brouard 7077: fprintf(ficgp, "\n#********** Variable ");
1.332 ! brouard 7078: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.222 brouard 7079: fprintf(ficgp, "**********\n#\n");
1.220 brouard 7080:
7081:
1.222 brouard 7082: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.319 brouard 7083: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); */
1.332 ! brouard 7084: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtmcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.222 brouard 7085: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 7086:
1.222 brouard 7087: fprintf(ficresprobcor, "\n#********** Variable ");
1.332 ! brouard 7088: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.222 brouard 7089: fprintf(ficresprobcor, "**********\n#");
7090: if(invalidvarcomb[j1]){
7091: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7092: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7093: continue;
7094: }
7095: }
7096: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7097: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7098: gp=vector(1,(nlstate)*(nlstate+ndeath));
7099: gm=vector(1,(nlstate)*(nlstate+ndeath));
7100: for (age=bage; age<=fage; age ++){
7101: cov[2]=age;
7102: if(nagesqr==1)
7103: cov[3]= age*age;
1.326 brouard 7104: /* for (k=1; k<=cptcovn;k++) { */
7105: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; */
7106: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
7107: /* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates */
1.332 ! brouard 7108: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])];
1.222 brouard 7109: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
7110: * 1 1 1 1 1
7111: * 2 2 1 1 1
7112: * 3 1 2 1 1
7113: */
7114: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
7115: }
1.319 brouard 7116: /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 */
7117: /* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] */
7118: /*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
1.326 brouard 7119: for (k=1; k<=cptcovage;k++){ /* For product with age */
7120: if(Dummy[Tage[k]]==2){ /* dummy with age */
1.332 ! brouard 7121: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2];
1.326 brouard 7122: /* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
7123: } else if(Dummy[Tage[k]]==3){ /* quantitative with age */
1.327 brouard 7124: 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]);
1.332 ! brouard 7125: /* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\* Using the mean of quantitative variable Tvar[Tage[k]] /\* Tqresult[nres][k]; *\/ */
! 7126: /* exit(1); */
1.326 brouard 7127: /* cov[++k1]=Tqresult[nres][k]; */
7128: }
7129: /* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
7130: }
7131: for (k=1; k<=cptcovprod;k++){/* For product without age */
1.329 brouard 7132: if(Dummy[Tvard[k][1]]==0){
7133: if(Dummy[Tvard[k][2]]==0){
1.332 ! brouard 7134: 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]])];
1.326 brouard 7135: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
7136: }else{ /* Should we use the mean of the quantitative variables? */
1.332 ! brouard 7137: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]];
1.326 brouard 7138: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; */
7139: }
7140: }else{
1.329 brouard 7141: if(Dummy[Tvard[k][2]]==0){
1.332 ! brouard 7142: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]];
1.326 brouard 7143: /* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; */
7144: }else{
1.332 ! brouard 7145: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]];
1.326 brouard 7146: /* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
7147: }
7148: }
7149: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
7150: }
7151: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7152: for(theta=1; theta <=npar; theta++){
7153: for(i=1; i<=npar; i++)
7154: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7155:
1.222 brouard 7156: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7157:
1.222 brouard 7158: k=0;
7159: for(i=1; i<= (nlstate); i++){
7160: for(j=1; j<=(nlstate+ndeath);j++){
7161: k=k+1;
7162: gp[k]=pmmij[i][j];
7163: }
7164: }
1.220 brouard 7165:
1.222 brouard 7166: for(i=1; i<=npar; i++)
7167: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7168:
1.222 brouard 7169: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7170: k=0;
7171: for(i=1; i<=(nlstate); i++){
7172: for(j=1; j<=(nlstate+ndeath);j++){
7173: k=k+1;
7174: gm[k]=pmmij[i][j];
7175: }
7176: }
1.220 brouard 7177:
1.222 brouard 7178: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7179: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7180: }
1.126 brouard 7181:
1.222 brouard 7182: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7183: for(theta=1; theta <=npar; theta++)
7184: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7185:
1.222 brouard 7186: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7187: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7188:
1.222 brouard 7189: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7190:
1.222 brouard 7191: k=0;
7192: for(i=1; i<=(nlstate); i++){
7193: for(j=1; j<=(nlstate+ndeath);j++){
7194: k=k+1;
7195: mu[k][(int) age]=pmmij[i][j];
7196: }
7197: }
7198: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7199: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7200: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7201:
1.222 brouard 7202: /*printf("\n%d ",(int)age);
7203: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7204: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7205: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7206: }*/
1.220 brouard 7207:
1.222 brouard 7208: fprintf(ficresprob,"\n%d ",(int)age);
7209: fprintf(ficresprobcov,"\n%d ",(int)age);
7210: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7211:
1.222 brouard 7212: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7213: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7214: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7215: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7216: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7217: }
7218: i=0;
7219: for (k=1; k<=(nlstate);k++){
7220: for (l=1; l<=(nlstate+ndeath);l++){
7221: i++;
7222: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7223: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7224: for (j=1; j<=i;j++){
7225: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7226: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7227: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7228: }
7229: }
7230: }/* end of loop for state */
7231: } /* end of loop for age */
7232: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7233: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7234: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7235: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7236:
7237: /* Confidence intervalle of pij */
7238: /*
7239: fprintf(ficgp,"\nunset parametric;unset label");
7240: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7241: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7242: 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);
7243: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7244: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7245: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7246: */
7247:
7248: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7249: first1=1;first2=2;
7250: for (k2=1; k2<=(nlstate);k2++){
7251: for (l2=1; l2<=(nlstate+ndeath);l2++){
7252: if(l2==k2) continue;
7253: j=(k2-1)*(nlstate+ndeath)+l2;
7254: for (k1=1; k1<=(nlstate);k1++){
7255: for (l1=1; l1<=(nlstate+ndeath);l1++){
7256: if(l1==k1) continue;
7257: i=(k1-1)*(nlstate+ndeath)+l1;
7258: if(i<=j) continue;
7259: for (age=bage; age<=fage; age ++){
7260: if ((int)age %5==0){
7261: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7262: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7263: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7264: mu1=mu[i][(int) age]/stepm*YEARM ;
7265: mu2=mu[j][(int) age]/stepm*YEARM;
7266: c12=cv12/sqrt(v1*v2);
7267: /* Computing eigen value of matrix of covariance */
7268: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7269: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7270: if ((lc2 <0) || (lc1 <0) ){
7271: if(first2==1){
7272: first1=0;
7273: 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);
7274: }
7275: 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);
7276: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7277: /* lc2=fabs(lc2); */
7278: }
1.220 brouard 7279:
1.222 brouard 7280: /* Eigen vectors */
1.280 brouard 7281: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7282: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7283: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7284: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7285: }else
7286: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7287: /*v21=sqrt(1.-v11*v11); *//* error */
7288: v21=(lc1-v1)/cv12*v11;
7289: v12=-v21;
7290: v22=v11;
7291: tnalp=v21/v11;
7292: if(first1==1){
7293: first1=0;
7294: 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);
7295: }
7296: 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);
7297: /*printf(fignu*/
7298: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7299: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7300: if(first==1){
7301: first=0;
7302: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7303: fprintf(ficgp,"\nset parametric;unset label");
7304: 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);
7305: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7306: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7307: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7308: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7309: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7310: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7311: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7312: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7313: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7314: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7315: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7316: 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 7317: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7318: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7319: }else{
7320: first=0;
7321: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7322: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7323: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7324: 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 7325: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7326: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7327: }/* if first */
7328: } /* age mod 5 */
7329: } /* end loop age */
7330: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7331: first=1;
7332: } /*l12 */
7333: } /* k12 */
7334: } /*l1 */
7335: }/* k1 */
1.332 ! brouard 7336: } /* loop on combination of covariates j1 */
1.326 brouard 7337: } /* loop on nres */
1.222 brouard 7338: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
7339: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
7340: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7341: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
7342: free_vector(xp,1,npar);
7343: fclose(ficresprob);
7344: fclose(ficresprobcov);
7345: fclose(ficresprobcor);
7346: fflush(ficgp);
7347: fflush(fichtmcov);
7348: }
1.126 brouard 7349:
7350:
7351: /******************* Printing html file ***********/
1.201 brouard 7352: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 7353: int lastpass, int stepm, int weightopt, char model[],\
7354: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 7355: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
7356: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
7357: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 7358: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 7359: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 7360: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
7361: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
7362: </ul>");
1.319 brouard 7363: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
7364: /* </ul>", model); */
1.214 brouard 7365: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
7366: 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",
7367: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 ! brouard 7368: 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 7369: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
7370: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 7371: fprintf(fichtm,"\
7372: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 7373: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 7374: fprintf(fichtm,"\
1.217 brouard 7375: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
7376: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
7377: fprintf(fichtm,"\
1.288 brouard 7378: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7379: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 7380: fprintf(fichtm,"\
1.288 brouard 7381: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 7382: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
7383: fprintf(fichtm,"\
1.211 brouard 7384: - (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 7385: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7386: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 7387: if(prevfcast==1){
7388: fprintf(fichtm,"\
7389: - Prevalence projections by age and states: \
1.201 brouard 7390: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 7391: }
1.126 brouard 7392:
7393:
1.225 brouard 7394: m=pow(2,cptcoveff);
1.222 brouard 7395: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7396:
1.317 brouard 7397: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 7398:
7399: jj1=0;
7400:
7401: fprintf(fichtm," \n<ul>");
7402: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7403: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7404: if(m != 1 && TKresult[nres]!= k1)
7405: continue;
7406: jj1++;
7407: if (cptcovn > 0) {
7408: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
7409: for (cpt=1; cpt<=cptcoveff;cpt++){
7410: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7411: }
7412: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7413: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7414: }
7415: fprintf(fichtm,"\">");
7416:
7417: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7418: fprintf(fichtm,"************ Results for covariates");
7419: for (cpt=1; cpt<=cptcoveff;cpt++){
7420: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7421: }
7422: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7423: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7424: }
7425: if(invalidvarcomb[k1]){
7426: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7427: continue;
7428: }
7429: fprintf(fichtm,"</a></li>");
7430: } /* cptcovn >0 */
7431: }
1.317 brouard 7432: fprintf(fichtm," \n</ul>");
1.264 brouard 7433:
1.222 brouard 7434: jj1=0;
1.237 brouard 7435:
7436: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 7437: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 7438: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7439: continue;
1.220 brouard 7440:
1.222 brouard 7441: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7442: jj1++;
7443: if (cptcovn > 0) {
1.264 brouard 7444: fprintf(fichtm,"\n<p><a name=\"rescov");
7445: for (cpt=1; cpt<=cptcoveff;cpt++){
7446: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7447: }
7448: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7449: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7450: }
7451: fprintf(fichtm,"\"</a>");
7452:
1.222 brouard 7453: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7454: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 7455: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7456: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
7457: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7458: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 7459: }
1.237 brouard 7460: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7461: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7462: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
7463: }
7464:
1.230 brouard 7465: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.321 brouard 7466: fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 7467: if(invalidvarcomb[k1]){
7468: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
7469: printf("\nCombination (%d) ignored because no cases \n",k1);
7470: continue;
7471: }
7472: }
7473: /* aij, bij */
1.259 brouard 7474: 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 7475: <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 7476: /* Pij */
1.241 brouard 7477: 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> \
7478: <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 7479: /* Quasi-incidences */
7480: 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 7481: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 7482: 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 7483: 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> \
7484: <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 7485: /* Survival functions (period) in state j */
7486: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7487: 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);
7488: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7489: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 7490: }
7491: /* State specific survival functions (period) */
7492: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7493: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
7494: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 7495: <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);
7496: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7497: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 7498: }
1.288 brouard 7499: /* Period (forward stable) prevalence in each health state */
1.222 brouard 7500: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7501: 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);
7502: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"P_"),subdirf2(optionfilefiname,"P_"));
7503: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 7504: }
1.296 brouard 7505: if(prevbcast==1){
1.288 brouard 7506: /* Backward prevalence in each health state */
1.222 brouard 7507: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7508: 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> \
1.241 brouard 7509: <img src=\"%s_%d-%d-%d.svg\">", cpt, cpt, nlstate, subdirf2(optionfilefiname,"PB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 7510: }
1.217 brouard 7511: }
1.222 brouard 7512: if(prevfcast==1){
1.288 brouard 7513: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7514: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 7515: 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);
7516: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
7517: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
7518: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 7519: }
7520: }
1.296 brouard 7521: if(prevbcast==1){
1.268 brouard 7522: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
7523: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 7524: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
7525: 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 \
7526: 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 7527: 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);
7528: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
7529: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 7530: }
7531: }
1.220 brouard 7532:
1.222 brouard 7533: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 7534: 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);
7535: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
7536: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 7537: }
7538: /* } /\* end i1 *\/ */
7539: }/* End k1 */
7540: fprintf(fichtm,"</ul>");
1.126 brouard 7541:
1.222 brouard 7542: fprintf(fichtm,"\
1.126 brouard 7543: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 7544: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 7545: - 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 7546: But because parameters are usually highly correlated (a higher incidence of disability \
7547: and a higher incidence of recovery can give very close observed transition) it might \
7548: be very useful to look not only at linear confidence intervals estimated from the \
7549: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
7550: (parameters) of the logistic regression, it might be more meaningful to visualize the \
7551: covariance matrix of the one-step probabilities. \
7552: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7553:
1.222 brouard 7554: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7555: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7556: fprintf(fichtm,"\
1.126 brouard 7557: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7558: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7559:
1.222 brouard 7560: fprintf(fichtm,"\
1.126 brouard 7561: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7562: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7563: fprintf(fichtm,"\
1.126 brouard 7564: - 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): \
7565: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7566: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7567: fprintf(fichtm,"\
1.126 brouard 7568: - (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): \
7569: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7570: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7571: fprintf(fichtm,"\
1.288 brouard 7572: - 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 7573: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7574: fprintf(fichtm,"\
1.128 brouard 7575: - 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 7576: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7577: fprintf(fichtm,"\
1.288 brouard 7578: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7579: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7580:
7581: /* if(popforecast==1) fprintf(fichtm,"\n */
7582: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7583: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7584: /* <br>",fileres,fileres,fileres,fileres); */
7585: /* else */
7586: /* fprintf(fichtm,"\n No population forecast: popforecast = %d (instead of 1) or stepm = %d (instead of 1) or model=%s (instead of .)<br><br></li>\n",popforecast, stepm, model); */
1.222 brouard 7587: fflush(fichtm);
1.126 brouard 7588:
1.225 brouard 7589: m=pow(2,cptcoveff);
1.222 brouard 7590: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7591:
1.317 brouard 7592: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
7593:
7594: jj1=0;
7595:
7596: fprintf(fichtm," \n<ul>");
7597: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7598: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7599: if(m != 1 && TKresult[nres]!= k1)
7600: continue;
7601: jj1++;
7602: if (cptcovn > 0) {
7603: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
7604: for (cpt=1; cpt<=cptcoveff;cpt++){
7605: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7606: }
7607: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7608: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7609: }
7610: fprintf(fichtm,"\">");
7611:
7612: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7613: fprintf(fichtm,"************ Results for covariates");
7614: for (cpt=1; cpt<=cptcoveff;cpt++){
7615: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7616: }
7617: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7618: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7619: }
7620: if(invalidvarcomb[k1]){
7621: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7622: continue;
7623: }
7624: fprintf(fichtm,"</a></li>");
7625: } /* cptcovn >0 */
7626: }
7627: fprintf(fichtm," \n</ul>");
7628:
1.222 brouard 7629: jj1=0;
1.237 brouard 7630:
1.241 brouard 7631: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7632: for(k1=1; k1<=m;k1++){
1.253 brouard 7633: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7634: continue;
1.222 brouard 7635: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7636: jj1++;
1.126 brouard 7637: if (cptcovn > 0) {
1.317 brouard 7638: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
7639: for (cpt=1; cpt<=cptcoveff;cpt++){
7640: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7641: }
7642: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7643: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7644: }
7645: fprintf(fichtm,"\"</a>");
7646:
1.126 brouard 7647: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.317 brouard 7648: for (cpt=1; cpt<=cptcoveff;cpt++){ /**< cptcoveff number of variables */
1.237 brouard 7649: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
1.317 brouard 7650: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
1.237 brouard 7651: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 7652: }
1.237 brouard 7653: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7654: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7655: }
7656:
1.321 brouard 7657: fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 7658:
1.222 brouard 7659: if(invalidvarcomb[k1]){
7660: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7661: continue;
7662: }
1.126 brouard 7663: }
7664: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7665: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 7666: 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);
7667: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
7668: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 7669: }
7670: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 7671: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 7672: true period expectancies (those weighted with period prevalences are also\
7673: drawn in addition to the population based expectancies computed using\
1.314 brouard 7674: 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);
7675: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
7676: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7677: /* } /\* end i1 *\/ */
7678: }/* End k1 */
1.241 brouard 7679: }/* End nres */
1.222 brouard 7680: fprintf(fichtm,"</ul>");
7681: fflush(fichtm);
1.126 brouard 7682: }
7683:
7684: /******************* Gnuplot file **************/
1.296 brouard 7685: 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 7686:
7687: char dirfileres[132],optfileres[132];
1.264 brouard 7688: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7689: int cpt=0,k1=0,i=0,k=0,j=0,jk=0,k2=0,k3=0,k4=0,ij=0, ijp=0, l=0;
1.211 brouard 7690: int lv=0, vlv=0, kl=0;
1.130 brouard 7691: int ng=0;
1.201 brouard 7692: int vpopbased;
1.223 brouard 7693: int ioffset; /* variable offset for columns */
1.270 brouard 7694: int iyearc=1; /* variable column for year of projection */
7695: int iagec=1; /* variable column for age of projection */
1.235 brouard 7696: int nres=0; /* Index of resultline */
1.266 brouard 7697: int istart=1; /* For starting graphs in projections */
1.219 brouard 7698:
1.126 brouard 7699: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7700: /* printf("Problem with file %s",optionfilegnuplot); */
7701: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7702: /* } */
7703:
7704: /*#ifdef windows */
7705: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7706: /*#endif */
1.225 brouard 7707: m=pow(2,cptcoveff);
1.126 brouard 7708:
1.274 brouard 7709: /* diagram of the model */
7710: fprintf(ficgp,"\n#Diagram of the model \n");
7711: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7712: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7713: 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);
7714:
7715: fprintf(ficgp,"\n#Centripete arrows (turning in other direction (1-i) instead of (i-1)) \nset for [i=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);
7716: fprintf(ficgp,"\n#show arrow\nunset label\n");
7717: 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);
7718: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7719: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7720: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7721: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7722:
1.202 brouard 7723: /* Contribution to likelihood */
7724: /* Plot the probability implied in the likelihood */
1.223 brouard 7725: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7726: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7727: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7728: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7729: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7730: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7731: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7732: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7733: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7734: 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));
7735: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7736: 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));
7737: for (i=1; i<= nlstate ; i ++) {
7738: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7739: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7740: 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);
7741: for (j=2; j<= nlstate+ndeath ; j ++) {
7742: 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);
7743: }
7744: fprintf(ficgp,";\nset out; unset ylabel;\n");
7745: }
7746: /* 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 */
7747: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7748: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7749: fprintf(ficgp,"\nset out;unset log\n");
7750: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7751:
1.126 brouard 7752: strcpy(dirfileres,optionfilefiname);
7753: strcpy(optfileres,"vpl");
1.223 brouard 7754: /* 1eme*/
1.238 brouard 7755: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7756: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7757: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7758: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7759: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7760: continue;
7761: /* We are interested in selected combination by the resultline */
1.246 brouard 7762: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7763: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7764: strcpy(gplotlabel,"(");
1.238 brouard 7765: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
1.332 ! brouard 7766: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the value of the covariate corresponding to k1 combination *\/ */
! 7767: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 7768: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7769: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7770: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7771: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7772: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7773: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7774: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7775: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7776: }
7777: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7778: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7779: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7780: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7781: }
7782: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7783: /* printf("\n#\n"); */
1.238 brouard 7784: fprintf(ficgp,"\n#\n");
7785: if(invalidvarcomb[k1]){
1.260 brouard 7786: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7787: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7788: continue;
7789: }
1.235 brouard 7790:
1.241 brouard 7791: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7792: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7793: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
1.321 brouard 7794: fprintf(ficgp,"set title \"Alive state %d %s model=%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 7795: 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);
7796: /* 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); */
7797: /* k1-1 error should be nres-1*/
1.238 brouard 7798: for (i=1; i<= nlstate ; i ++) {
7799: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7800: else fprintf(ficgp," %%*lf (%%*lf)");
7801: }
1.288 brouard 7802: 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 7803: for (i=1; i<= nlstate ; i ++) {
7804: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7805: else fprintf(ficgp," %%*lf (%%*lf)");
7806: }
1.260 brouard 7807: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7808: for (i=1; i<= nlstate ; i ++) {
7809: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7810: else fprintf(ficgp," %%*lf (%%*lf)");
7811: }
1.265 brouard 7812: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7813:
7814: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7815: if(cptcoveff ==0){
1.271 brouard 7816: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7817: }else{
7818: kl=0;
7819: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 ! brouard 7820: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
! 7821: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 7822: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7823: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7824: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7825: vlv= nbcode[Tvaraff[k]][lv];
7826: kl++;
7827: /* 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 *\/ */
7828: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7829: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7830: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7831: if(k==cptcoveff){
7832: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7833: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7834: }else{
7835: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7836: kl++;
7837: }
7838: } /* end covariate */
7839: } /* end if no covariate */
7840:
1.296 brouard 7841: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 7842: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7843: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7844: if(cptcoveff ==0){
1.245 brouard 7845: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7846: }else{
7847: kl=0;
7848: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 ! brouard 7849: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
! 7850: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 7851: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7852: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7853: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 ! brouard 7854: /* vlv= nbcode[Tvaraff[k]][lv]; */
! 7855: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 7856: kl++;
1.238 brouard 7857: /* 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 *\/ */
7858: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7859: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7860: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7861: if(k==cptcoveff){
1.245 brouard 7862: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7863: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7864: }else{
1.332 ! brouard 7865: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 7866: kl++;
7867: }
7868: } /* end covariate */
7869: } /* end if no covariate */
1.296 brouard 7870: if(prevbcast == 1){
1.268 brouard 7871: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7872: /* k1-1 error should be nres-1*/
7873: for (i=1; i<= nlstate ; i ++) {
7874: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7875: else fprintf(ficgp," %%*lf (%%*lf)");
7876: }
1.271 brouard 7877: 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 7878: for (i=1; i<= nlstate ; i ++) {
7879: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7880: else fprintf(ficgp," %%*lf (%%*lf)");
7881: }
1.276 brouard 7882: 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 7883: for (i=1; i<= nlstate ; i ++) {
7884: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7885: else fprintf(ficgp," %%*lf (%%*lf)");
7886: }
1.274 brouard 7887: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7888: } /* end if backprojcast */
1.296 brouard 7889: } /* end if prevbcast */
1.276 brouard 7890: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7891: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7892: } /* nres */
1.201 brouard 7893: } /* k1 */
7894: } /* cpt */
1.235 brouard 7895:
7896:
1.126 brouard 7897: /*2 eme*/
1.238 brouard 7898: for (k1=1; k1<= m ; k1 ++){
7899: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7900: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7901: continue;
7902: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7903: strcpy(gplotlabel,"(");
1.238 brouard 7904: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.332 ! brouard 7905: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate number corresponding to k1 combination *\/ */
! 7906: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.223 brouard 7907: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7908: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7909: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 ! brouard 7910: /* vlv= nbcode[Tvaraff[k]][lv]; */
! 7911: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 7912: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7913: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7914: }
1.237 brouard 7915: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7916: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7917: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7918: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7919: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7920: }
1.264 brouard 7921: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7922: fprintf(ficgp,"\n#\n");
1.223 brouard 7923: if(invalidvarcomb[k1]){
7924: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7925: continue;
7926: }
1.219 brouard 7927:
1.241 brouard 7928: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7929: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7930: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7931: if(vpopbased==0){
1.238 brouard 7932: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7933: }else
1.238 brouard 7934: fprintf(ficgp,"\nreplot ");
7935: for (i=1; i<= nlstate+1 ; i ++) {
7936: k=2*i;
1.261 brouard 7937: 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 7938: for (j=1; j<= nlstate+1 ; j ++) {
7939: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7940: else fprintf(ficgp," %%*lf (%%*lf)");
7941: }
7942: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7943: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7944: 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 7945: for (j=1; j<= nlstate+1 ; j ++) {
7946: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7947: else fprintf(ficgp," %%*lf (%%*lf)");
7948: }
7949: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7950: 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 7951: for (j=1; j<= nlstate+1 ; j ++) {
7952: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7953: else fprintf(ficgp," %%*lf (%%*lf)");
7954: }
7955: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7956: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7957: } /* state */
7958: } /* vpopbased */
1.264 brouard 7959: 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 7960: } /* end nres */
7961: } /* k1 end 2 eme*/
7962:
7963:
7964: /*3eme*/
7965: for (k1=1; k1<= m ; k1 ++){
7966: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7967: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7968: continue;
7969:
1.332 ! brouard 7970: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 7971: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7972: strcpy(gplotlabel,"(");
1.238 brouard 7973: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.332 ! brouard 7974: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate number corresponding to k1 combination *\/ */
! 7975: lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /* Should be the covariate value corresponding to combination k1 and covariate k */
1.238 brouard 7976: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7977: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7978: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 ! brouard 7979: /* vlv= nbcode[Tvaraff[k]][lv]; */
! 7980: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.238 brouard 7981: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7982: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7983: }
7984: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.332 ! brouard 7985: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]);
! 7986: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]);
1.238 brouard 7987: }
1.264 brouard 7988: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7989: fprintf(ficgp,"\n#\n");
7990: if(invalidvarcomb[k1]){
7991: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7992: continue;
7993: }
7994:
7995: /* k=2+nlstate*(2*cpt-2); */
7996: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7997: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7998: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7999: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8000: 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 8001: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8002: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8003: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8004: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8005: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8006: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8007:
1.238 brouard 8008: */
8009: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8010: 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 8011: /* 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 8012:
1.238 brouard 8013: }
1.261 brouard 8014: 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 8015: }
1.264 brouard 8016: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8017: } /* end nres */
8018: } /* end kl 3eme */
1.126 brouard 8019:
1.223 brouard 8020: /* 4eme */
1.201 brouard 8021: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 8022: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
8023: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8024: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 8025: continue;
1.238 brouard 8026: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8027: strcpy(gplotlabel,"(");
1.238 brouard 8028: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
8029: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.332 ! brouard 8030: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
! 8031: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate number corresponding to k1 combination *\/ */
1.238 brouard 8032: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8033: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8034: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 ! brouard 8035: /* vlv= nbcode[Tvaraff[k]][lv]; */
! 8036: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.238 brouard 8037: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8038: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 8039: }
8040: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.332 ! brouard 8041: fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
! 8042: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
1.238 brouard 8043: }
1.264 brouard 8044: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8045: fprintf(ficgp,"\n#\n");
8046: if(invalidvarcomb[k1]){
8047: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8048: continue;
1.223 brouard 8049: }
1.238 brouard 8050:
1.241 brouard 8051: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8052: 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 8053: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8054: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8055: k=3;
8056: for (i=1; i<= nlstate ; i ++){
8057: if(i==1){
8058: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8059: }else{
8060: fprintf(ficgp,", '' ");
8061: }
8062: l=(nlstate+ndeath)*(i-1)+1;
8063: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8064: for (j=2; j<= nlstate+ndeath ; j ++)
8065: fprintf(ficgp,"+$%d",k+l+j-1);
8066: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8067: } /* nlstate */
1.264 brouard 8068: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8069: } /* end cpt state*/
8070: } /* end nres */
8071: } /* end covariate k1 */
8072:
1.220 brouard 8073: /* 5eme */
1.201 brouard 8074: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 8075: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
8076: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8077: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 8078: continue;
1.238 brouard 8079: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8080: strcpy(gplotlabel,"(");
1.238 brouard 8081: 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);
8082: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.332 ! brouard 8083: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
! 8084: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate number corresponding to k1 combination *\/ */
1.238 brouard 8085: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8086: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8087: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 ! brouard 8088: /* vlv= nbcode[Tvaraff[k]][lv]; */
! 8089: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.238 brouard 8090: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8091: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 8092: }
8093: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.332 ! brouard 8094: fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
! 8095: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
1.238 brouard 8096: }
1.264 brouard 8097: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8098: fprintf(ficgp,"\n#\n");
8099: if(invalidvarcomb[k1]){
8100: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8101: continue;
8102: }
1.227 brouard 8103:
1.241 brouard 8104: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8105: 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 8106: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8107: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8108: k=3;
8109: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8110: if(j==1)
8111: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8112: else
8113: fprintf(ficgp,", '' ");
8114: l=(nlstate+ndeath)*(cpt-1) +j;
8115: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8116: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8117: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8118: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8119: } /* nlstate */
8120: fprintf(ficgp,", '' ");
8121: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8122: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8123: l=(nlstate+ndeath)*(cpt-1) +j;
8124: if(j < nlstate)
8125: fprintf(ficgp,"$%d +",k+l);
8126: else
8127: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8128: }
1.264 brouard 8129: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8130: } /* end cpt state*/
8131: } /* end covariate */
8132: } /* end nres */
1.227 brouard 8133:
1.220 brouard 8134: /* 6eme */
1.202 brouard 8135: /* CV preval stable (period) for each covariate */
1.237 brouard 8136: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8137: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8138: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8139: continue;
1.255 brouard 8140: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8141: strcpy(gplotlabel,"(");
1.288 brouard 8142: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 8143: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.332 ! brouard 8144: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate number corresponding to k1 combination *\/ */
! 8145: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.227 brouard 8146: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8147: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8148: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 ! brouard 8149: /* vlv= nbcode[Tvaraff[k]][lv]; */
! 8150: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.227 brouard 8151: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8152: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 8153: }
1.237 brouard 8154: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.332 ! brouard 8155: fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
! 8156: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
1.237 brouard 8157: }
1.264 brouard 8158: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8159: fprintf(ficgp,"\n#\n");
1.223 brouard 8160: if(invalidvarcomb[k1]){
1.227 brouard 8161: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8162: continue;
1.223 brouard 8163: }
1.227 brouard 8164:
1.241 brouard 8165: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8166: 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 8167: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8168: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8169: k=3; /* Offset */
1.255 brouard 8170: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8171: if(i==1)
8172: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8173: else
8174: fprintf(ficgp,", '' ");
1.255 brouard 8175: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8176: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8177: for (j=2; j<= nlstate ; j ++)
8178: fprintf(ficgp,"+$%d",k+l+j-1);
8179: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8180: } /* nlstate */
1.264 brouard 8181: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8182: } /* end cpt state*/
8183: } /* end covariate */
1.227 brouard 8184:
8185:
1.220 brouard 8186: /* 7eme */
1.296 brouard 8187: if(prevbcast == 1){
1.288 brouard 8188: /* CV backward prevalence for each covariate */
1.237 brouard 8189: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8190: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8191: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8192: continue;
1.268 brouard 8193: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 8194: strcpy(gplotlabel,"(");
1.288 brouard 8195: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 8196: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.332 ! brouard 8197: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate number corresponding to k1 combination *\/ */
! 8198: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.227 brouard 8199: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8200: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 8201: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 ! brouard 8202: /* vlv= nbcode[Tvaraff[k]][lv]; */
! 8203: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.227 brouard 8204: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8205: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 8206: }
1.237 brouard 8207: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.332 ! brouard 8208: fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
! 8209: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
1.237 brouard 8210: }
1.264 brouard 8211: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8212: fprintf(ficgp,"\n#\n");
8213: if(invalidvarcomb[k1]){
8214: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8215: continue;
8216: }
8217:
1.241 brouard 8218: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 8219: 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 8220: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8221: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 8222: k=3; /* Offset */
1.268 brouard 8223: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 8224: if(i==1)
8225: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
8226: else
8227: fprintf(ficgp,", '' ");
8228: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 8229: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 8230: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
8231: /* 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 8232: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 8233: /* for (j=2; j<= nlstate ; j ++) */
8234: /* fprintf(ficgp,"+$%d",k+l+j-1); */
8235: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 8236: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 8237: } /* nlstate */
1.264 brouard 8238: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 8239: } /* end cpt state*/
8240: } /* end covariate */
1.296 brouard 8241: } /* End if prevbcast */
1.218 brouard 8242:
1.223 brouard 8243: /* 8eme */
1.218 brouard 8244: if(prevfcast==1){
1.288 brouard 8245: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 8246:
1.237 brouard 8247: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8248: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8249: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8250: continue;
1.211 brouard 8251: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 8252: strcpy(gplotlabel,"(");
1.288 brouard 8253: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 8254: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
1.332 ! brouard 8255: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
! 8256: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.227 brouard 8257: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8258: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8259: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 ! brouard 8260: /* vlv= nbcode[Tvaraff[k]][lv]; */
! 8261: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.227 brouard 8262: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8263: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 8264: }
1.237 brouard 8265: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.332 ! brouard 8266: fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
! 8267: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
1.237 brouard 8268: }
1.264 brouard 8269: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8270: fprintf(ficgp,"\n#\n");
8271: if(invalidvarcomb[k1]){
8272: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8273: continue;
8274: }
8275:
8276: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 8277: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 8278: 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 8279: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 8280: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 8281:
8282: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8283: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8284: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8285: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 8286: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8287: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8288: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8289: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 8290: if(i==istart){
1.227 brouard 8291: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
8292: }else{
8293: fprintf(ficgp,",\\\n '' ");
8294: }
8295: if(cptcoveff ==0){ /* No covariate */
8296: ioffset=2; /* Age is in 2 */
8297: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8298: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8299: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8300: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8301: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 8302: if(i==nlstate+1){
1.270 brouard 8303: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 8304: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8305: fprintf(ficgp,",\\\n '' ");
8306: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8307: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 8308: offyear, \
1.268 brouard 8309: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 8310: }else
1.227 brouard 8311: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
8312: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8313: }else{ /* more than 2 covariates */
1.270 brouard 8314: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8315: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8316: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8317: iyearc=ioffset-1;
8318: iagec=ioffset;
1.227 brouard 8319: fprintf(ficgp," u %d:(",ioffset);
8320: kl=0;
8321: strcpy(gplotcondition,"(");
8322: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
1.332 ! brouard 8323: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
! 8324: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.227 brouard 8325: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8326: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8327: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 ! brouard 8328: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
! 8329: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.227 brouard 8330: kl++;
8331: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8332: kl++;
8333: if(k <cptcoveff && cptcoveff>1)
8334: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8335: }
8336: strcpy(gplotcondition+strlen(gplotcondition),")");
8337: /* 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 *\/ */
8338: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8339: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8340: /* '' 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*/
8341: if(i==nlstate+1){
1.270 brouard 8342: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
8343: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 8344: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8345: fprintf(ficgp," u %d:(",iagec);
8346: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
8347: iyearc, iagec, offyear, \
8348: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 8349: /* '' 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 8350: }else{
8351: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
8352: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8353: }
8354: } /* end if covariate */
8355: } /* nlstate */
1.264 brouard 8356: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 8357: } /* end cpt state*/
8358: } /* end covariate */
8359: } /* End if prevfcast */
1.227 brouard 8360:
1.296 brouard 8361: if(prevbcast==1){
1.268 brouard 8362: /* Back projection from cross-sectional to stable (mixed) for each covariate */
8363:
8364: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8365: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8366: if(m != 1 && TKresult[nres]!= k1)
8367: continue;
8368: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
8369: strcpy(gplotlabel,"(");
8370: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
8371: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
1.332 ! brouard 8372: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
! 8373: lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /* Should be the covariate value corresponding to combination k1 and covariate k */
1.268 brouard 8374: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8375: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8376: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 ! brouard 8377: /* vlv= nbcode[Tvaraff[k]][lv]; */
! 8378: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.268 brouard 8379: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8380: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8381: }
8382: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.332 ! brouard 8383: fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
! 8384: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
1.268 brouard 8385: }
8386: strcpy(gplotlabel+strlen(gplotlabel),")");
8387: fprintf(ficgp,"\n#\n");
8388: if(invalidvarcomb[k1]){
8389: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8390: continue;
8391: }
8392:
8393: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
8394: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
8395: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
8396: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
8397: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8398:
8399: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8400: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8401: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8402: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
8403: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8404: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8405: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8406: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8407: if(i==istart){
8408: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
8409: }else{
8410: fprintf(ficgp,",\\\n '' ");
8411: }
8412: if(cptcoveff ==0){ /* No covariate */
8413: ioffset=2; /* Age is in 2 */
8414: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8415: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8416: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8417: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8418: fprintf(ficgp," u %d:(", ioffset);
8419: if(i==nlstate+1){
1.270 brouard 8420: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 8421: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8422: fprintf(ficgp,",\\\n '' ");
8423: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8424: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 8425: offbyear, \
8426: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
8427: }else
8428: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
8429: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
8430: }else{ /* more than 2 covariates */
1.270 brouard 8431: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8432: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8433: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8434: iyearc=ioffset-1;
8435: iagec=ioffset;
1.268 brouard 8436: fprintf(ficgp," u %d:(",ioffset);
8437: kl=0;
8438: strcpy(gplotcondition,"(");
8439: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
1.332 ! brouard 8440: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
! 8441: lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /* Should be the covariate value corresponding to combination k1 and covariate k */
1.268 brouard 8442: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8443: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8444: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 ! brouard 8445: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
! 8446: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.268 brouard 8447: kl++;
8448: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8449: kl++;
8450: if(k <cptcoveff && cptcoveff>1)
8451: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8452: }
8453: strcpy(gplotcondition+strlen(gplotcondition),")");
8454: /* 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 *\/ */
8455: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8456: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8457: /* '' 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*/
8458: if(i==nlstate+1){
1.270 brouard 8459: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
8460: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 8461: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8462: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 8463: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 8464: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
8465: iyearc,iagec,offbyear, \
8466: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 8467: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
8468: }else{
8469: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
8470: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
8471: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
8472: }
8473: } /* end if covariate */
8474: } /* nlstate */
8475: fprintf(ficgp,"\nset out; unset label;\n");
8476: } /* end cpt state*/
8477: } /* end covariate */
1.296 brouard 8478: } /* End if prevbcast */
1.268 brouard 8479:
1.227 brouard 8480:
1.238 brouard 8481: /* 9eme writing MLE parameters */
8482: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 8483: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 8484: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 8485: for(k=1; k <=(nlstate+ndeath); k++){
8486: if (k != i) {
1.227 brouard 8487: fprintf(ficgp,"# current state %d\n",k);
8488: for(j=1; j <=ncovmodel; j++){
8489: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
8490: jk++;
8491: }
8492: fprintf(ficgp,"\n");
1.126 brouard 8493: }
8494: }
1.223 brouard 8495: }
1.187 brouard 8496: fprintf(ficgp,"##############\n#\n");
1.227 brouard 8497:
1.145 brouard 8498: /*goto avoid;*/
1.238 brouard 8499: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
8500: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 8501: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
8502: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
8503: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
8504: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
8505: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8506: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8507: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8508: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8509: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
8510: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8511: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
8512: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
8513: fprintf(ficgp,"#\n");
1.223 brouard 8514: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 8515: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 8516: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 8517: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 8518: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
8519: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 8520: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 8521: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8522: continue;
1.264 brouard 8523: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
8524: strcpy(gplotlabel,"(");
1.276 brouard 8525: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 8526: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
1.332 ! brouard 8527: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
! 8528: lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /* Should be the covariate value corresponding to combination k1 and covariate k */
1.264 brouard 8529: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8530: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8531: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 ! brouard 8532: /* vlv= nbcode[Tvaraff[k]][lv]; */
! 8533: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.264 brouard 8534: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8535: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8536: }
1.237 brouard 8537: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.332 ! brouard 8538: fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
! 8539: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]);
1.237 brouard 8540: }
1.264 brouard 8541: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 8542: fprintf(ficgp,"\n#\n");
1.264 brouard 8543: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 8544: fprintf(ficgp,"\nset key outside ");
8545: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
8546: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 8547: fprintf(ficgp,"\nset ter svg size 640, 480 ");
8548: if (ng==1){
8549: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
8550: fprintf(ficgp,"\nunset log y");
8551: }else if (ng==2){
8552: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
8553: fprintf(ficgp,"\nset log y");
8554: }else if (ng==3){
8555: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
8556: fprintf(ficgp,"\nset log y");
8557: }else
8558: fprintf(ficgp,"\nunset title ");
8559: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
8560: i=1;
8561: for(k2=1; k2<=nlstate; k2++) {
8562: k3=i;
8563: for(k=1; k<=(nlstate+ndeath); k++) {
8564: if (k != k2){
8565: switch( ng) {
8566: case 1:
8567: if(nagesqr==0)
8568: fprintf(ficgp," p%d+p%d*x",i,i+1);
8569: else /* nagesqr =1 */
8570: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8571: break;
8572: case 2: /* ng=2 */
8573: if(nagesqr==0)
8574: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
8575: else /* nagesqr =1 */
8576: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8577: break;
8578: case 3:
8579: if(nagesqr==0)
8580: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
8581: else /* nagesqr =1 */
8582: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
8583: break;
8584: }
8585: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 8586: ijp=1; /* product no age */
8587: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
8588: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 8589: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 8590: switch(Typevar[j]){
8591: case 1:
8592: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8593: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
8594: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8595: if(DummyV[j]==0){/* Bug valgrind */
8596: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
8597: }else{ /* quantitative */
8598: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8599: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8600: }
8601: ij++;
1.268 brouard 8602: }
1.237 brouard 8603: }
1.329 brouard 8604: }
8605: break;
8606: case 2:
8607: if(cptcovprod >0){
8608: if(j==Tprod[ijp]) { /* */
8609: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8610: if(ijp <=cptcovprod) { /* Product */
8611: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8612: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8613: /* 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)]); */
8614: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8615: }else{ /* Vn is dummy and Vm is quanti */
8616: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8617: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8618: }
8619: }else{ /* Vn*Vm Vn is quanti */
8620: if(DummyV[Tvard[ijp][2]]==0){
8621: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8622: }else{ /* Both quanti */
8623: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8624: }
1.268 brouard 8625: }
1.329 brouard 8626: ijp++;
1.237 brouard 8627: }
1.329 brouard 8628: } /* end Tprod */
8629: }
8630: break;
8631: case 0:
8632: /* simple covariate */
1.264 brouard 8633: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 8634: if(Dummy[j]==0){
8635: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
8636: }else{ /* quantitative */
8637: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 8638: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 8639: }
1.329 brouard 8640: /* end simple */
8641: break;
8642: default:
8643: break;
8644: } /* end switch */
1.237 brouard 8645: } /* end j */
1.329 brouard 8646: }else{ /* k=k2 */
8647: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
8648: fprintf(ficgp," (1.");i=i-ncovmodel;
8649: }else
8650: i=i-ncovmodel;
1.223 brouard 8651: }
1.227 brouard 8652:
1.223 brouard 8653: if(ng != 1){
8654: fprintf(ficgp,")/(1");
1.227 brouard 8655:
1.264 brouard 8656: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8657: if(nagesqr==0)
1.264 brouard 8658: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8659: else /* nagesqr =1 */
1.264 brouard 8660: 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 8661:
1.223 brouard 8662: ij=1;
1.329 brouard 8663: ijp=1;
8664: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
8665: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
8666: switch(Typevar[j]){
8667: case 1:
8668: if(cptcovage >0){
8669: if(j==Tage[ij]) { /* Bug valgrind */
8670: if(ij <=cptcovage) { /* Bug valgrind */
8671: if(DummyV[j]==0){/* Bug valgrind */
8672: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
8673: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
8674: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
8675: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
8676: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8677: }else{ /* quantitative */
8678: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
8679: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8680: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
8681: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8682: }
8683: ij++;
8684: }
8685: }
8686: }
8687: break;
8688: case 2:
8689: if(cptcovprod >0){
8690: if(j==Tprod[ijp]) { /* */
8691: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8692: if(ijp <=cptcovprod) { /* Product */
8693: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8694: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8695: /* 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)]); */
8696: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8697: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
8698: }else{ /* Vn is dummy and Vm is quanti */
8699: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8700: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8701: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
8702: }
8703: }else{ /* Vn*Vm Vn is quanti */
8704: if(DummyV[Tvard[ijp][2]]==0){
8705: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8706: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
8707: }else{ /* Both quanti */
8708: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8709: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
8710: }
8711: }
8712: ijp++;
8713: }
8714: } /* end Tprod */
8715: } /* end if */
8716: break;
8717: case 0:
8718: /* simple covariate */
8719: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
8720: if(Dummy[j]==0){
8721: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
8722: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
8723: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
8724: }else{ /* quantitative */
8725: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
8726: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
8727: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8728: }
8729: /* end simple */
8730: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
8731: break;
8732: default:
8733: break;
8734: } /* end switch */
1.223 brouard 8735: }
8736: fprintf(ficgp,")");
8737: }
8738: fprintf(ficgp,")");
8739: if(ng ==2)
1.276 brouard 8740: 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 8741: else /* ng= 3 */
1.276 brouard 8742: 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 8743: }else{ /* end ng <> 1 */
1.223 brouard 8744: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8745: 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 8746: }
8747: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8748: fprintf(ficgp,",");
8749: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8750: fprintf(ficgp,",");
8751: i=i+ncovmodel;
8752: } /* end k */
8753: } /* end k2 */
1.276 brouard 8754: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8755: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8756: } /* end k1 */
1.223 brouard 8757: } /* end ng */
8758: /* avoid: */
8759: fflush(ficgp);
1.126 brouard 8760: } /* end gnuplot */
8761:
8762:
8763: /*************** Moving average **************/
1.219 brouard 8764: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8765: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8766:
1.222 brouard 8767: int i, cpt, cptcod;
8768: int modcovmax =1;
8769: int mobilavrange, mob;
8770: int iage=0;
1.288 brouard 8771: int firstA1=0, firstA2=0;
1.222 brouard 8772:
1.266 brouard 8773: double sum=0., sumr=0.;
1.222 brouard 8774: double age;
1.266 brouard 8775: double *sumnewp, *sumnewm, *sumnewmr;
8776: double *agemingood, *agemaxgood;
8777: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8778:
8779:
1.278 brouard 8780: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8781: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8782:
8783: sumnewp = vector(1,ncovcombmax);
8784: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8785: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8786: agemingood = vector(1,ncovcombmax);
1.266 brouard 8787: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8788: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8789: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8790:
8791: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8792: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8793: sumnewp[cptcod]=0.;
1.266 brouard 8794: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8795: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8796: }
8797: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8798:
1.266 brouard 8799: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8800: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8801: else mobilavrange=mobilav;
8802: for (age=bage; age<=fage; age++)
8803: for (i=1; i<=nlstate;i++)
8804: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8805: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8806: /* We keep the original values on the extreme ages bage, fage and for
8807: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8808: we use a 5 terms etc. until the borders are no more concerned.
8809: */
8810: for (mob=3;mob <=mobilavrange;mob=mob+2){
8811: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8812: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8813: sumnewm[cptcod]=0.;
8814: for (i=1; i<=nlstate;i++){
1.222 brouard 8815: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8816: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8817: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8818: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8819: }
8820: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8821: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8822: } /* end i */
8823: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8824: } /* end cptcod */
1.222 brouard 8825: }/* end age */
8826: }/* end mob */
1.266 brouard 8827: }else{
8828: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8829: return -1;
1.266 brouard 8830: }
8831:
8832: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8833: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8834: if(invalidvarcomb[cptcod]){
8835: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8836: continue;
8837: }
1.219 brouard 8838:
1.266 brouard 8839: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8840: sumnewm[cptcod]=0.;
8841: sumnewmr[cptcod]=0.;
8842: for (i=1; i<=nlstate;i++){
8843: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8844: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8845: }
8846: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8847: agemingoodr[cptcod]=age;
8848: }
8849: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8850: agemingood[cptcod]=age;
8851: }
8852: } /* age */
8853: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8854: sumnewm[cptcod]=0.;
1.266 brouard 8855: sumnewmr[cptcod]=0.;
1.222 brouard 8856: for (i=1; i<=nlstate;i++){
8857: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8858: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8859: }
8860: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8861: agemaxgoodr[cptcod]=age;
1.222 brouard 8862: }
8863: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8864: agemaxgood[cptcod]=age;
8865: }
8866: } /* age */
8867: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8868: /* but they will change */
1.288 brouard 8869: firstA1=0;firstA2=0;
1.266 brouard 8870: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8871: sumnewm[cptcod]=0.;
8872: sumnewmr[cptcod]=0.;
8873: for (i=1; i<=nlstate;i++){
8874: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8875: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8876: }
8877: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8878: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8879: agemaxgoodr[cptcod]=age; /* age min */
8880: for (i=1; i<=nlstate;i++)
8881: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8882: }else{ /* bad we change the value with the values of good ages */
8883: for (i=1; i<=nlstate;i++){
8884: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8885: } /* i */
8886: } /* end bad */
8887: }else{
8888: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8889: agemaxgood[cptcod]=age;
8890: }else{ /* bad we change the value with the values of good ages */
8891: for (i=1; i<=nlstate;i++){
8892: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8893: } /* i */
8894: } /* end bad */
8895: }/* end else */
8896: sum=0.;sumr=0.;
8897: for (i=1; i<=nlstate;i++){
8898: sum+=mobaverage[(int)age][i][cptcod];
8899: sumr+=probs[(int)age][i][cptcod];
8900: }
8901: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8902: if(!firstA1){
8903: firstA1=1;
8904: 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);
8905: }
8906: 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 8907: } /* end bad */
8908: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8909: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 8910: if(!firstA2){
8911: firstA2=1;
8912: 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);
8913: }
8914: 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 8915: } /* end bad */
8916: }/* age */
1.266 brouard 8917:
8918: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8919: sumnewm[cptcod]=0.;
1.266 brouard 8920: sumnewmr[cptcod]=0.;
1.222 brouard 8921: for (i=1; i<=nlstate;i++){
8922: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8923: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8924: }
8925: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8926: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8927: agemingoodr[cptcod]=age;
8928: for (i=1; i<=nlstate;i++)
8929: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8930: }else{ /* bad we change the value with the values of good ages */
8931: for (i=1; i<=nlstate;i++){
8932: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8933: } /* i */
8934: } /* end bad */
8935: }else{
8936: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8937: agemingood[cptcod]=age;
8938: }else{ /* bad */
8939: for (i=1; i<=nlstate;i++){
8940: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8941: } /* i */
8942: } /* end bad */
8943: }/* end else */
8944: sum=0.;sumr=0.;
8945: for (i=1; i<=nlstate;i++){
8946: sum+=mobaverage[(int)age][i][cptcod];
8947: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8948: }
1.266 brouard 8949: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8950: 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 8951: } /* end bad */
8952: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8953: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8954: 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 8955: } /* end bad */
8956: }/* age */
1.266 brouard 8957:
1.222 brouard 8958:
8959: for (age=bage; age<=fage; age++){
1.235 brouard 8960: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8961: sumnewp[cptcod]=0.;
8962: sumnewm[cptcod]=0.;
8963: for (i=1; i<=nlstate;i++){
8964: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8965: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8966: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8967: }
8968: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8969: }
8970: /* printf("\n"); */
8971: /* } */
1.266 brouard 8972:
1.222 brouard 8973: /* brutal averaging */
1.266 brouard 8974: /* for (i=1; i<=nlstate;i++){ */
8975: /* for (age=1; age<=bage; age++){ */
8976: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8977: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8978: /* } */
8979: /* for (age=fage; age<=AGESUP; age++){ */
8980: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8981: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8982: /* } */
8983: /* } /\* end i status *\/ */
8984: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8985: /* for (age=1; age<=AGESUP; age++){ */
8986: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8987: /* mobaverage[(int)age][i][cptcod]=0.; */
8988: /* } */
8989: /* } */
1.222 brouard 8990: }/* end cptcod */
1.266 brouard 8991: free_vector(agemaxgoodr,1, ncovcombmax);
8992: free_vector(agemaxgood,1, ncovcombmax);
8993: free_vector(agemingood,1, ncovcombmax);
8994: free_vector(agemingoodr,1, ncovcombmax);
8995: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8996: free_vector(sumnewm,1, ncovcombmax);
8997: free_vector(sumnewp,1, ncovcombmax);
8998: return 0;
8999: }/* End movingaverage */
1.218 brouard 9000:
1.126 brouard 9001:
1.296 brouard 9002:
1.126 brouard 9003: /************** Forecasting ******************/
1.296 brouard 9004: /* 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)*/
9005: 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){
9006: /* dateintemean, mean date of interviews
9007: dateprojd, year, month, day of starting projection
9008: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9009: agemin, agemax range of age
9010: dateprev1 dateprev2 range of dates during which prevalence is computed
9011: */
1.296 brouard 9012: /* double anprojd, mprojd, jprojd; */
9013: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9014: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9015: double agec; /* generic age */
1.296 brouard 9016: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9017: double *popeffectif,*popcount;
9018: double ***p3mat;
1.218 brouard 9019: /* double ***mobaverage; */
1.126 brouard 9020: char fileresf[FILENAMELENGTH];
9021:
9022: agelim=AGESUP;
1.211 brouard 9023: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9024: in each health status at the date of interview (if between dateprev1 and dateprev2).
9025: We still use firstpass and lastpass as another selection.
9026: */
1.214 brouard 9027: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9028: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9029:
1.201 brouard 9030: strcpy(fileresf,"F_");
9031: strcat(fileresf,fileresu);
1.126 brouard 9032: if((ficresf=fopen(fileresf,"w"))==NULL) {
9033: printf("Problem with forecast resultfile: %s\n", fileresf);
9034: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9035: }
1.235 brouard 9036: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9037: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9038:
1.225 brouard 9039: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9040:
9041:
9042: stepsize=(int) (stepm+YEARM-1)/YEARM;
9043: if (stepm<=12) stepsize=1;
9044: if(estepm < stepm){
9045: printf ("Problem %d lower than %d\n",estepm, stepm);
9046: }
1.270 brouard 9047: else{
9048: hstepm=estepm;
9049: }
9050: if(estepm > stepm){ /* Yes every two year */
9051: stepsize=2;
9052: }
1.296 brouard 9053: hstepm=hstepm/stepm;
1.126 brouard 9054:
1.296 brouard 9055:
9056: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9057: /* fractional in yp1 *\/ */
9058: /* aintmean=yp; */
9059: /* yp2=modf((yp1*12),&yp); */
9060: /* mintmean=yp; */
9061: /* yp1=modf((yp2*30.5),&yp); */
9062: /* jintmean=yp; */
9063: /* if(jintmean==0) jintmean=1; */
9064: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9065:
1.296 brouard 9066:
9067: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9068: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9069: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 9070: i1=pow(2,cptcoveff);
1.126 brouard 9071: if (cptcovn < 1){i1=1;}
9072:
1.296 brouard 9073: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 9074:
9075: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 9076:
1.126 brouard 9077: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 9078: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.332 ! brouard 9079: 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 9080: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 9081: continue;
1.227 brouard 9082: if(invalidvarcomb[k]){
9083: printf("\nCombination (%d) projection ignored because no cases \n",k);
9084: continue;
9085: }
9086: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
9087: for(j=1;j<=cptcoveff;j++) {
1.332 ! brouard 9088: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); */
! 9089: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.227 brouard 9090: }
1.235 brouard 9091: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 9092: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 9093: }
1.227 brouard 9094: fprintf(ficresf," yearproj age");
9095: for(j=1; j<=nlstate+ndeath;j++){
9096: for(i=1; i<=nlstate;i++)
9097: fprintf(ficresf," p%d%d",i,j);
9098: fprintf(ficresf," wp.%d",j);
9099: }
1.296 brouard 9100: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 9101: fprintf(ficresf,"\n");
1.296 brouard 9102: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 9103: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
9104: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 9105: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
9106: nhstepm = nhstepm/hstepm;
9107: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9108: oldm=oldms;savm=savms;
1.268 brouard 9109: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 9110: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 9111: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 9112: for (h=0; h<=nhstepm; h++){
9113: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 9114: break;
9115: }
9116: }
9117: fprintf(ficresf,"\n");
9118: for(j=1;j<=cptcoveff;j++)
1.332 ! brouard 9119: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
! 9120: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /* TnsdVar[Tvaraff] correct */
1.296 brouard 9121: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 9122:
9123: for(j=1; j<=nlstate+ndeath;j++) {
9124: ppij=0.;
9125: for(i=1; i<=nlstate;i++) {
1.278 brouard 9126: if (mobilav>=1)
9127: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
9128: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
9129: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
9130: }
1.268 brouard 9131: fprintf(ficresf," %.3f", p3mat[i][j][h]);
9132: } /* end i */
9133: fprintf(ficresf," %.3f", ppij);
9134: }/* end j */
1.227 brouard 9135: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9136: } /* end agec */
1.266 brouard 9137: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
9138: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 9139: } /* end yearp */
9140: } /* end k */
1.219 brouard 9141:
1.126 brouard 9142: fclose(ficresf);
1.215 brouard 9143: printf("End of Computing forecasting \n");
9144: fprintf(ficlog,"End of Computing forecasting\n");
9145:
1.126 brouard 9146: }
9147:
1.269 brouard 9148: /************** Back Forecasting ******************/
1.296 brouard 9149: /* 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){ */
9150: 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){
9151: /* back1, year, month, day of starting backprojection
1.267 brouard 9152: agemin, agemax range of age
9153: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 9154: anback2 year of end of backprojection (same day and month as back1).
9155: prevacurrent and prev are prevalences.
1.267 brouard 9156: */
9157: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
9158: double agec; /* generic age */
1.302 brouard 9159: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 9160: double *popeffectif,*popcount;
9161: double ***p3mat;
9162: /* double ***mobaverage; */
9163: char fileresfb[FILENAMELENGTH];
9164:
1.268 brouard 9165: agelim=AGEINF;
1.267 brouard 9166: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9167: in each health status at the date of interview (if between dateprev1 and dateprev2).
9168: We still use firstpass and lastpass as another selection.
9169: */
9170: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9171: /* firstpass, lastpass, stepm, weightopt, model); */
9172:
9173: /*Do we need to compute prevalence again?*/
9174:
9175: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
9176:
9177: strcpy(fileresfb,"FB_");
9178: strcat(fileresfb,fileresu);
9179: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
9180: printf("Problem with back forecast resultfile: %s\n", fileresfb);
9181: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
9182: }
9183: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9184: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9185:
9186: if (cptcoveff==0) ncodemax[cptcoveff]=1;
9187:
9188:
9189: stepsize=(int) (stepm+YEARM-1)/YEARM;
9190: if (stepm<=12) stepsize=1;
9191: if(estepm < stepm){
9192: printf ("Problem %d lower than %d\n",estepm, stepm);
9193: }
1.270 brouard 9194: else{
9195: hstepm=estepm;
9196: }
9197: if(estepm >= stepm){ /* Yes every two year */
9198: stepsize=2;
9199: }
1.267 brouard 9200:
9201: hstepm=hstepm/stepm;
1.296 brouard 9202: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9203: /* fractional in yp1 *\/ */
9204: /* aintmean=yp; */
9205: /* yp2=modf((yp1*12),&yp); */
9206: /* mintmean=yp; */
9207: /* yp1=modf((yp2*30.5),&yp); */
9208: /* jintmean=yp; */
9209: /* if(jintmean==0) jintmean=1; */
9210: /* if(mintmean==0) jintmean=1; */
1.267 brouard 9211:
9212: i1=pow(2,cptcoveff);
9213: if (cptcovn < 1){i1=1;}
9214:
1.296 brouard 9215: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
9216: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 9217:
9218: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
9219:
9220: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9221: for(k=1; k<=i1;k++){
9222: if(i1 != 1 && TKresult[nres]!= k)
9223: continue;
9224: if(invalidvarcomb[k]){
9225: printf("\nCombination (%d) projection ignored because no cases \n",k);
9226: continue;
9227: }
1.268 brouard 9228: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 9229: for(j=1;j<=cptcoveff;j++) {
1.332 ! brouard 9230: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.267 brouard 9231: }
9232: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
9233: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9234: }
9235: fprintf(ficresfb," yearbproj age");
9236: for(j=1; j<=nlstate+ndeath;j++){
9237: for(i=1; i<=nlstate;i++)
1.268 brouard 9238: fprintf(ficresfb," b%d%d",i,j);
9239: fprintf(ficresfb," b.%d",j);
1.267 brouard 9240: }
1.296 brouard 9241: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 9242: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
9243: fprintf(ficresfb,"\n");
1.296 brouard 9244: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 9245: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 9246: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
9247: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 9248: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 9249: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 9250: nhstepm = nhstepm/hstepm;
9251: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9252: oldm=oldms;savm=savms;
1.268 brouard 9253: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 9254: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 9255: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 9256: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
9257: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
9258: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 9259: for (h=0; h<=nhstepm; h++){
1.268 brouard 9260: if (h*hstepm/YEARM*stepm ==-yearp) {
9261: break;
9262: }
9263: }
9264: fprintf(ficresfb,"\n");
9265: for(j=1;j<=cptcoveff;j++)
1.332 ! brouard 9266: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.296 brouard 9267: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 9268: for(i=1; i<=nlstate+ndeath;i++) {
9269: ppij=0.;ppi=0.;
9270: for(j=1; j<=nlstate;j++) {
9271: /* if (mobilav==1) */
1.269 brouard 9272: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
9273: ppi=ppi+prevacurrent[(int)agec][j][k];
9274: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
9275: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 9276: /* else { */
9277: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
9278: /* } */
1.268 brouard 9279: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
9280: } /* end j */
9281: if(ppi <0.99){
9282: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9283: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9284: }
9285: fprintf(ficresfb," %.3f", ppij);
9286: }/* end j */
1.267 brouard 9287: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9288: } /* end agec */
9289: } /* end yearp */
9290: } /* end k */
1.217 brouard 9291:
1.267 brouard 9292: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 9293:
1.267 brouard 9294: fclose(ficresfb);
9295: printf("End of Computing Back forecasting \n");
9296: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 9297:
1.267 brouard 9298: }
1.217 brouard 9299:
1.269 brouard 9300: /* Variance of prevalence limit: varprlim */
9301: 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 9302: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 9303:
9304: char fileresvpl[FILENAMELENGTH];
9305: FILE *ficresvpl;
9306: double **oldm, **savm;
9307: double **varpl; /* Variances of prevalence limits by age */
9308: int i1, k, nres, j ;
9309:
9310: strcpy(fileresvpl,"VPL_");
9311: strcat(fileresvpl,fileresu);
9312: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 9313: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 9314: exit(0);
9315: }
1.288 brouard 9316: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
9317: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 9318:
9319: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
9320: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
9321:
9322: i1=pow(2,cptcoveff);
9323: if (cptcovn < 1){i1=1;}
9324:
9325: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.332 ! brouard 9326: for(k=1; k<=i1;k++){ /* We find the combination equivalent to result line values of dummies */
1.269 brouard 9327: if(i1 != 1 && TKresult[nres]!= k)
9328: continue;
9329: fprintf(ficresvpl,"\n#****** ");
9330: printf("\n#****** ");
9331: fprintf(ficlog,"\n#****** ");
9332: for(j=1;j<=cptcoveff;j++) {
1.332 ! brouard 9333: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
! 9334: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
! 9335: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.269 brouard 9336: }
9337: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 ! brouard 9338: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
! 9339: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
! 9340: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
1.269 brouard 9341: }
9342: fprintf(ficresvpl,"******\n");
9343: printf("******\n");
9344: fprintf(ficlog,"******\n");
9345:
9346: varpl=matrix(1,nlstate,(int) bage, (int) fage);
9347: oldm=oldms;savm=savms;
9348: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
9349: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
9350: /*}*/
9351: }
9352:
9353: fclose(ficresvpl);
1.288 brouard 9354: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
9355: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 9356:
9357: }
9358: /* Variance of back prevalence: varbprlim */
9359: 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){
9360: /*------- Variance of back (stable) prevalence------*/
9361:
9362: char fileresvbl[FILENAMELENGTH];
9363: FILE *ficresvbl;
9364:
9365: double **oldm, **savm;
9366: double **varbpl; /* Variances of back prevalence limits by age */
9367: int i1, k, nres, j ;
9368:
9369: strcpy(fileresvbl,"VBL_");
9370: strcat(fileresvbl,fileresu);
9371: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
9372: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
9373: exit(0);
9374: }
9375: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
9376: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
9377:
9378:
9379: i1=pow(2,cptcoveff);
9380: if (cptcovn < 1){i1=1;}
9381:
9382: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9383: for(k=1; k<=i1;k++){
9384: if(i1 != 1 && TKresult[nres]!= k)
9385: continue;
9386: fprintf(ficresvbl,"\n#****** ");
9387: printf("\n#****** ");
9388: fprintf(ficlog,"\n#****** ");
9389: for(j=1;j<=cptcoveff;j++) {
1.332 ! brouard 9390: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
! 9391: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
! 9392: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.269 brouard 9393: }
9394: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 ! brouard 9395: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
! 9396: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
! 9397: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
1.269 brouard 9398: }
9399: fprintf(ficresvbl,"******\n");
9400: printf("******\n");
9401: fprintf(ficlog,"******\n");
9402:
9403: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
9404: oldm=oldms;savm=savms;
9405:
9406: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
9407: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
9408: /*}*/
9409: }
9410:
9411: fclose(ficresvbl);
9412: printf("done variance-covariance of back prevalence\n");fflush(stdout);
9413: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
9414:
9415: } /* End of varbprlim */
9416:
1.126 brouard 9417: /************** Forecasting *****not tested NB*************/
1.227 brouard 9418: /* 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 9419:
1.227 brouard 9420: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
9421: /* int *popage; */
9422: /* double calagedatem, agelim, kk1, kk2; */
9423: /* double *popeffectif,*popcount; */
9424: /* double ***p3mat,***tabpop,***tabpopprev; */
9425: /* /\* double ***mobaverage; *\/ */
9426: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 9427:
1.227 brouard 9428: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9429: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9430: /* agelim=AGESUP; */
9431: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 9432:
1.227 brouard 9433: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 9434:
9435:
1.227 brouard 9436: /* strcpy(filerespop,"POP_"); */
9437: /* strcat(filerespop,fileresu); */
9438: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
9439: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
9440: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
9441: /* } */
9442: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
9443: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 9444:
1.227 brouard 9445: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 9446:
1.227 brouard 9447: /* /\* if (mobilav!=0) { *\/ */
9448: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
9449: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
9450: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9451: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9452: /* /\* } *\/ */
9453: /* /\* } *\/ */
1.126 brouard 9454:
1.227 brouard 9455: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
9456: /* if (stepm<=12) stepsize=1; */
1.126 brouard 9457:
1.227 brouard 9458: /* agelim=AGESUP; */
1.126 brouard 9459:
1.227 brouard 9460: /* hstepm=1; */
9461: /* hstepm=hstepm/stepm; */
1.218 brouard 9462:
1.227 brouard 9463: /* if (popforecast==1) { */
9464: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
9465: /* printf("Problem with population file : %s\n",popfile);exit(0); */
9466: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
9467: /* } */
9468: /* popage=ivector(0,AGESUP); */
9469: /* popeffectif=vector(0,AGESUP); */
9470: /* popcount=vector(0,AGESUP); */
1.126 brouard 9471:
1.227 brouard 9472: /* i=1; */
9473: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 9474:
1.227 brouard 9475: /* imx=i; */
9476: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
9477: /* } */
1.218 brouard 9478:
1.227 brouard 9479: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
9480: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
9481: /* k=k+1; */
9482: /* fprintf(ficrespop,"\n#******"); */
9483: /* for(j=1;j<=cptcoveff;j++) { */
9484: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
9485: /* } */
9486: /* fprintf(ficrespop,"******\n"); */
9487: /* fprintf(ficrespop,"# Age"); */
9488: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
9489: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 9490:
1.227 brouard 9491: /* for (cpt=0; cpt<=0;cpt++) { */
9492: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 9493:
1.227 brouard 9494: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9495: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9496: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9497:
1.227 brouard 9498: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9499: /* oldm=oldms;savm=savms; */
9500: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 9501:
1.227 brouard 9502: /* for (h=0; h<=nhstepm; h++){ */
9503: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9504: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9505: /* } */
9506: /* for(j=1; j<=nlstate+ndeath;j++) { */
9507: /* kk1=0.;kk2=0; */
9508: /* for(i=1; i<=nlstate;i++) { */
9509: /* if (mobilav==1) */
9510: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
9511: /* else { */
9512: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
9513: /* } */
9514: /* } */
9515: /* if (h==(int)(calagedatem+12*cpt)){ */
9516: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
9517: /* /\*fprintf(ficrespop," %.3f", kk1); */
9518: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
9519: /* } */
9520: /* } */
9521: /* for(i=1; i<=nlstate;i++){ */
9522: /* kk1=0.; */
9523: /* for(j=1; j<=nlstate;j++){ */
9524: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
9525: /* } */
9526: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
9527: /* } */
1.218 brouard 9528:
1.227 brouard 9529: /* if (h==(int)(calagedatem+12*cpt)) */
9530: /* for(j=1; j<=nlstate;j++) */
9531: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
9532: /* } */
9533: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9534: /* } */
9535: /* } */
1.218 brouard 9536:
1.227 brouard 9537: /* /\******\/ */
1.218 brouard 9538:
1.227 brouard 9539: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
9540: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
9541: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9542: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9543: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9544:
1.227 brouard 9545: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9546: /* oldm=oldms;savm=savms; */
9547: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
9548: /* for (h=0; h<=nhstepm; h++){ */
9549: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9550: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9551: /* } */
9552: /* for(j=1; j<=nlstate+ndeath;j++) { */
9553: /* kk1=0.;kk2=0; */
9554: /* for(i=1; i<=nlstate;i++) { */
9555: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
9556: /* } */
9557: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
9558: /* } */
9559: /* } */
9560: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9561: /* } */
9562: /* } */
9563: /* } */
9564: /* } */
1.218 brouard 9565:
1.227 brouard 9566: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 9567:
1.227 brouard 9568: /* if (popforecast==1) { */
9569: /* free_ivector(popage,0,AGESUP); */
9570: /* free_vector(popeffectif,0,AGESUP); */
9571: /* free_vector(popcount,0,AGESUP); */
9572: /* } */
9573: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9574: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9575: /* fclose(ficrespop); */
9576: /* } /\* End of popforecast *\/ */
1.218 brouard 9577:
1.126 brouard 9578: int fileappend(FILE *fichier, char *optionfich)
9579: {
9580: if((fichier=fopen(optionfich,"a"))==NULL) {
9581: printf("Problem with file: %s\n", optionfich);
9582: fprintf(ficlog,"Problem with file: %s\n", optionfich);
9583: return (0);
9584: }
9585: fflush(fichier);
9586: return (1);
9587: }
9588:
9589:
9590: /**************** function prwizard **********************/
9591: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
9592: {
9593:
9594: /* Wizard to print covariance matrix template */
9595:
1.164 brouard 9596: char ca[32], cb[32];
9597: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 9598: int numlinepar;
9599:
9600: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9601: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9602: for(i=1; i <=nlstate; i++){
9603: jj=0;
9604: for(j=1; j <=nlstate+ndeath; j++){
9605: if(j==i) continue;
9606: jj++;
9607: /*ca[0]= k+'a'-1;ca[1]='\0';*/
9608: printf("%1d%1d",i,j);
9609: fprintf(ficparo,"%1d%1d",i,j);
9610: for(k=1; k<=ncovmodel;k++){
9611: /* printf(" %lf",param[i][j][k]); */
9612: /* fprintf(ficparo," %lf",param[i][j][k]); */
9613: printf(" 0.");
9614: fprintf(ficparo," 0.");
9615: }
9616: printf("\n");
9617: fprintf(ficparo,"\n");
9618: }
9619: }
9620: printf("# Scales (for hessian or gradient estimation)\n");
9621: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
9622: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
9623: for(i=1; i <=nlstate; i++){
9624: jj=0;
9625: for(j=1; j <=nlstate+ndeath; j++){
9626: if(j==i) continue;
9627: jj++;
9628: fprintf(ficparo,"%1d%1d",i,j);
9629: printf("%1d%1d",i,j);
9630: fflush(stdout);
9631: for(k=1; k<=ncovmodel;k++){
9632: /* printf(" %le",delti3[i][j][k]); */
9633: /* fprintf(ficparo," %le",delti3[i][j][k]); */
9634: printf(" 0.");
9635: fprintf(ficparo," 0.");
9636: }
9637: numlinepar++;
9638: printf("\n");
9639: fprintf(ficparo,"\n");
9640: }
9641: }
9642: printf("# Covariance matrix\n");
9643: /* # 121 Var(a12)\n\ */
9644: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9645: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
9646: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
9647: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
9648: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
9649: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
9650: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9651: fflush(stdout);
9652: fprintf(ficparo,"# Covariance matrix\n");
9653: /* # 121 Var(a12)\n\ */
9654: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9655: /* # ...\n\ */
9656: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9657:
9658: for(itimes=1;itimes<=2;itimes++){
9659: jj=0;
9660: for(i=1; i <=nlstate; i++){
9661: for(j=1; j <=nlstate+ndeath; j++){
9662: if(j==i) continue;
9663: for(k=1; k<=ncovmodel;k++){
9664: jj++;
9665: ca[0]= k+'a'-1;ca[1]='\0';
9666: if(itimes==1){
9667: printf("#%1d%1d%d",i,j,k);
9668: fprintf(ficparo,"#%1d%1d%d",i,j,k);
9669: }else{
9670: printf("%1d%1d%d",i,j,k);
9671: fprintf(ficparo,"%1d%1d%d",i,j,k);
9672: /* printf(" %.5le",matcov[i][j]); */
9673: }
9674: ll=0;
9675: for(li=1;li <=nlstate; li++){
9676: for(lj=1;lj <=nlstate+ndeath; lj++){
9677: if(lj==li) continue;
9678: for(lk=1;lk<=ncovmodel;lk++){
9679: ll++;
9680: if(ll<=jj){
9681: cb[0]= lk +'a'-1;cb[1]='\0';
9682: if(ll<jj){
9683: if(itimes==1){
9684: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9685: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9686: }else{
9687: printf(" 0.");
9688: fprintf(ficparo," 0.");
9689: }
9690: }else{
9691: if(itimes==1){
9692: printf(" Var(%s%1d%1d)",ca,i,j);
9693: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
9694: }else{
9695: printf(" 0.");
9696: fprintf(ficparo," 0.");
9697: }
9698: }
9699: }
9700: } /* end lk */
9701: } /* end lj */
9702: } /* end li */
9703: printf("\n");
9704: fprintf(ficparo,"\n");
9705: numlinepar++;
9706: } /* end k*/
9707: } /*end j */
9708: } /* end i */
9709: } /* end itimes */
9710:
9711: } /* end of prwizard */
9712: /******************* Gompertz Likelihood ******************************/
9713: double gompertz(double x[])
9714: {
1.302 brouard 9715: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 9716: int i,n=0; /* n is the size of the sample */
9717:
1.220 brouard 9718: for (i=1;i<=imx ; i++) {
1.126 brouard 9719: sump=sump+weight[i];
9720: /* sump=sump+1;*/
9721: num=num+1;
9722: }
1.302 brouard 9723: L=0.0;
9724: /* agegomp=AGEGOMP; */
1.126 brouard 9725: /* for (i=0; i<=imx; i++)
9726: 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]);*/
9727:
1.302 brouard 9728: for (i=1;i<=imx ; i++) {
9729: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
9730: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
9731: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
9732: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
9733: * +
9734: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
9735: */
9736: if (wav[i] > 1 || agedc[i] < AGESUP) {
9737: if (cens[i] == 1){
9738: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9739: } else if (cens[i] == 0){
1.126 brouard 9740: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 9741: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
9742: } else
9743: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 9744: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 9745: L=L+A*weight[i];
1.126 brouard 9746: /* 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 9747: }
9748: }
1.126 brouard 9749:
1.302 brouard 9750: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 9751:
9752: return -2*L*num/sump;
9753: }
9754:
1.136 brouard 9755: #ifdef GSL
9756: /******************* Gompertz_f Likelihood ******************************/
9757: double gompertz_f(const gsl_vector *v, void *params)
9758: {
1.302 brouard 9759: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 9760: double *x= (double *) v->data;
9761: int i,n=0; /* n is the size of the sample */
9762:
9763: for (i=0;i<=imx-1 ; i++) {
9764: sump=sump+weight[i];
9765: /* sump=sump+1;*/
9766: num=num+1;
9767: }
9768:
9769:
9770: /* for (i=0; i<=imx; i++)
9771: 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]);*/
9772: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9773: for (i=1;i<=imx ; i++)
9774: {
9775: if (cens[i] == 1 && wav[i]>1)
9776: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9777:
9778: if (cens[i] == 0 && wav[i]>1)
9779: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9780: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9781:
9782: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9783: if (wav[i] > 1 ) { /* ??? */
9784: LL=LL+A*weight[i];
9785: /* 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]);*/
9786: }
9787: }
9788:
9789: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9790: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9791:
9792: return -2*LL*num/sump;
9793: }
9794: #endif
9795:
1.126 brouard 9796: /******************* Printing html file ***********/
1.201 brouard 9797: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9798: int lastpass, int stepm, int weightopt, char model[],\
9799: int imx, double p[],double **matcov,double agemortsup){
9800: int i,k;
9801:
9802: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9803: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9804: for (i=1;i<=2;i++)
9805: 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 9806: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9807: fprintf(fichtm,"</ul>");
9808:
9809: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9810:
9811: 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>");
9812:
9813: for (k=agegomp;k<(agemortsup-2);k++)
9814: 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]);
9815:
9816:
9817: fflush(fichtm);
9818: }
9819:
9820: /******************* Gnuplot file **************/
1.201 brouard 9821: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9822:
9823: char dirfileres[132],optfileres[132];
1.164 brouard 9824:
1.126 brouard 9825: int ng;
9826:
9827:
9828: /*#ifdef windows */
9829: fprintf(ficgp,"cd \"%s\" \n",pathc);
9830: /*#endif */
9831:
9832:
9833: strcpy(dirfileres,optionfilefiname);
9834: strcpy(optfileres,"vpl");
1.199 brouard 9835: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9836: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9837: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9838: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9839: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9840:
9841: }
9842:
1.136 brouard 9843: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9844: {
1.126 brouard 9845:
1.136 brouard 9846: /*-------- data file ----------*/
9847: FILE *fic;
9848: char dummy[]=" ";
1.240 brouard 9849: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9850: int lstra;
1.136 brouard 9851: int linei, month, year,iout;
1.302 brouard 9852: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 9853: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9854: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9855: char *stratrunc;
1.223 brouard 9856:
1.240 brouard 9857: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9858: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.328 brouard 9859: for(v=1;v<NCOVMAX;v++){
9860: DummyV[v]=0;
9861: FixedV[v]=0;
9862: }
1.126 brouard 9863:
1.240 brouard 9864: for(v=1; v <=ncovcol;v++){
9865: DummyV[v]=0;
9866: FixedV[v]=0;
9867: }
9868: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9869: DummyV[v]=1;
9870: FixedV[v]=0;
9871: }
9872: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9873: DummyV[v]=0;
9874: FixedV[v]=1;
9875: }
9876: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9877: DummyV[v]=1;
9878: FixedV[v]=1;
9879: }
9880: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9881: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9882: fprintf(ficlog,"Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9883: }
1.126 brouard 9884:
1.136 brouard 9885: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9886: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9887: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9888: }
1.126 brouard 9889:
1.302 brouard 9890: /* Is it a BOM UTF-8 Windows file? */
9891: /* First data line */
9892: linei=0;
9893: while(fgets(line, MAXLINE, fic)) {
9894: noffset=0;
9895: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
9896: {
9897: noffset=noffset+3;
9898: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
9899: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
9900: fflush(ficlog); return 1;
9901: }
9902: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
9903: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
9904: {
9905: noffset=noffset+2;
1.304 brouard 9906: 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);
9907: 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 9908: fflush(ficlog); return 1;
9909: }
9910: else if( line[0] == 0 && line[1] == 0)
9911: {
9912: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
9913: noffset=noffset+4;
1.304 brouard 9914: 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);
9915: 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 9916: fflush(ficlog); return 1;
9917: }
9918: } else{
9919: ;/*printf(" Not a BOM file\n");*/
9920: }
9921: /* If line starts with a # it is a comment */
9922: if (line[noffset] == '#') {
9923: linei=linei+1;
9924: break;
9925: }else{
9926: break;
9927: }
9928: }
9929: fclose(fic);
9930: if((fic=fopen(datafile,"r"))==NULL) {
9931: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9932: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
9933: }
9934: /* Not a Bom file */
9935:
1.136 brouard 9936: i=1;
9937: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9938: linei=linei+1;
9939: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9940: if(line[j] == '\t')
9941: line[j] = ' ';
9942: }
9943: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9944: ;
9945: };
9946: line[j+1]=0; /* Trims blanks at end of line */
9947: if(line[0]=='#'){
9948: fprintf(ficlog,"Comment line\n%s\n",line);
9949: printf("Comment line\n%s\n",line);
9950: continue;
9951: }
9952: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9953: strcpy(line, linetmp);
1.223 brouard 9954:
9955: /* Loops on waves */
9956: for (j=maxwav;j>=1;j--){
9957: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9958: cutv(stra, strb, line, ' ');
9959: if(strb[0]=='.') { /* Missing value */
9960: lval=-1;
9961: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9962: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9963: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9964: 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);
9965: 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);
9966: return 1;
9967: }
9968: }else{
9969: errno=0;
9970: /* what_kind_of_number(strb); */
9971: dval=strtod(strb,&endptr);
9972: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9973: /* if(strb != endptr && *endptr == '\0') */
9974: /* dval=dlval; */
9975: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9976: if( strb[0]=='\0' || (*endptr != '\0')){
9977: 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);
9978: 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);
9979: return 1;
9980: }
9981: cotqvar[j][iv][i]=dval;
9982: cotvar[j][ntv+iv][i]=dval;
9983: }
9984: strcpy(line,stra);
1.223 brouard 9985: }/* end loop ntqv */
1.225 brouard 9986:
1.223 brouard 9987: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9988: cutv(stra, strb, line, ' ');
9989: if(strb[0]=='.') { /* Missing value */
9990: lval=-1;
9991: }else{
9992: errno=0;
9993: lval=strtol(strb,&endptr,10);
9994: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9995: if( strb[0]=='\0' || (*endptr != '\0')){
9996: 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);
9997: 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);
9998: return 1;
9999: }
10000: }
10001: if(lval <-1 || lval >1){
10002: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10003: 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 10004: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10005: For example, for multinomial values like 1, 2 and 3,\n \
10006: build V1=0 V2=0 for the reference value (1),\n \
10007: V1=1 V2=0 for (2) \n \
1.223 brouard 10008: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10009: output of IMaCh is often meaningless.\n \
1.319 brouard 10010: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10011: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10012: 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 10013: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10014: For example, for multinomial values like 1, 2 and 3,\n \
10015: build V1=0 V2=0 for the reference value (1),\n \
10016: V1=1 V2=0 for (2) \n \
1.223 brouard 10017: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10018: output of IMaCh is often meaningless.\n \
1.319 brouard 10019: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10020: return 1;
10021: }
10022: cotvar[j][iv][i]=(double)(lval);
10023: strcpy(line,stra);
1.223 brouard 10024: }/* end loop ntv */
1.225 brouard 10025:
1.223 brouard 10026: /* Statuses at wave */
1.137 brouard 10027: cutv(stra, strb, line, ' ');
1.223 brouard 10028: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10029: lval=-1;
1.136 brouard 10030: }else{
1.238 brouard 10031: errno=0;
10032: lval=strtol(strb,&endptr,10);
10033: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10034: if( strb[0]=='\0' || (*endptr != '\0')){
10035: 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);
10036: 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);
10037: return 1;
10038: }
1.136 brouard 10039: }
1.225 brouard 10040:
1.136 brouard 10041: s[j][i]=lval;
1.225 brouard 10042:
1.223 brouard 10043: /* Date of Interview */
1.136 brouard 10044: strcpy(line,stra);
10045: cutv(stra, strb,line,' ');
1.169 brouard 10046: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10047: }
1.169 brouard 10048: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10049: month=99;
10050: year=9999;
1.136 brouard 10051: }else{
1.225 brouard 10052: 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);
10053: 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);
10054: return 1;
1.136 brouard 10055: }
10056: anint[j][i]= (double) year;
1.302 brouard 10057: mint[j][i]= (double)month;
10058: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10059: /* 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]); */
10060: /* 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]); */
10061: /* } */
1.136 brouard 10062: strcpy(line,stra);
1.223 brouard 10063: } /* End loop on waves */
1.225 brouard 10064:
1.223 brouard 10065: /* Date of death */
1.136 brouard 10066: cutv(stra, strb,line,' ');
1.169 brouard 10067: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10068: }
1.169 brouard 10069: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 10070: month=99;
10071: year=9999;
10072: }else{
1.141 brouard 10073: 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 10074: 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);
10075: return 1;
1.136 brouard 10076: }
10077: andc[i]=(double) year;
10078: moisdc[i]=(double) month;
10079: strcpy(line,stra);
10080:
1.223 brouard 10081: /* Date of birth */
1.136 brouard 10082: cutv(stra, strb,line,' ');
1.169 brouard 10083: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10084: }
1.169 brouard 10085: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 10086: month=99;
10087: year=9999;
10088: }else{
1.141 brouard 10089: 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);
10090: 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 10091: return 1;
1.136 brouard 10092: }
10093: if (year==9999) {
1.141 brouard 10094: 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);
10095: 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 10096: return 1;
10097:
1.136 brouard 10098: }
10099: annais[i]=(double)(year);
1.302 brouard 10100: moisnais[i]=(double)(month);
10101: for (j=1;j<=maxwav;j++){
10102: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
10103: 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]);
10104: 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]);
10105: }
10106: }
10107:
1.136 brouard 10108: strcpy(line,stra);
1.225 brouard 10109:
1.223 brouard 10110: /* Sample weight */
1.136 brouard 10111: cutv(stra, strb,line,' ');
10112: errno=0;
10113: dval=strtod(strb,&endptr);
10114: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 10115: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
10116: 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 10117: fflush(ficlog);
10118: return 1;
10119: }
10120: weight[i]=dval;
10121: strcpy(line,stra);
1.225 brouard 10122:
1.223 brouard 10123: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
10124: cutv(stra, strb, line, ' ');
10125: if(strb[0]=='.') { /* Missing value */
1.225 brouard 10126: lval=-1;
1.311 brouard 10127: coqvar[iv][i]=NAN;
10128: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 10129: }else{
1.225 brouard 10130: errno=0;
10131: /* what_kind_of_number(strb); */
10132: dval=strtod(strb,&endptr);
10133: /* if(strb != endptr && *endptr == '\0') */
10134: /* dval=dlval; */
10135: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10136: if( strb[0]=='\0' || (*endptr != '\0')){
10137: 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);
10138: 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);
10139: return 1;
10140: }
10141: coqvar[iv][i]=dval;
1.226 brouard 10142: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 10143: }
10144: strcpy(line,stra);
10145: }/* end loop nqv */
1.136 brouard 10146:
1.223 brouard 10147: /* Covariate values */
1.136 brouard 10148: for (j=ncovcol;j>=1;j--){
10149: cutv(stra, strb,line,' ');
1.223 brouard 10150: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 10151: lval=-1;
1.136 brouard 10152: }else{
1.225 brouard 10153: errno=0;
10154: lval=strtol(strb,&endptr,10);
10155: if( strb[0]=='\0' || (*endptr != '\0')){
10156: 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);
10157: 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);
10158: return 1;
10159: }
1.136 brouard 10160: }
10161: if(lval <-1 || lval >1){
1.225 brouard 10162: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10163: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10164: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10165: For example, for multinomial values like 1, 2 and 3,\n \
10166: build V1=0 V2=0 for the reference value (1),\n \
10167: V1=1 V2=0 for (2) \n \
1.136 brouard 10168: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10169: output of IMaCh is often meaningless.\n \
1.136 brouard 10170: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 10171: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10172: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10173: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10174: For example, for multinomial values like 1, 2 and 3,\n \
10175: build V1=0 V2=0 for the reference value (1),\n \
10176: V1=1 V2=0 for (2) \n \
1.136 brouard 10177: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10178: output of IMaCh is often meaningless.\n \
1.136 brouard 10179: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 10180: return 1;
1.136 brouard 10181: }
10182: covar[j][i]=(double)(lval);
10183: strcpy(line,stra);
10184: }
10185: lstra=strlen(stra);
1.225 brouard 10186:
1.136 brouard 10187: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
10188: stratrunc = &(stra[lstra-9]);
10189: num[i]=atol(stratrunc);
10190: }
10191: else
10192: num[i]=atol(stra);
10193: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
10194: 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;}*/
10195:
10196: i=i+1;
10197: } /* End loop reading data */
1.225 brouard 10198:
1.136 brouard 10199: *imax=i-1; /* Number of individuals */
10200: fclose(fic);
1.225 brouard 10201:
1.136 brouard 10202: return (0);
1.164 brouard 10203: /* endread: */
1.225 brouard 10204: printf("Exiting readdata: ");
10205: fclose(fic);
10206: return (1);
1.223 brouard 10207: }
1.126 brouard 10208:
1.234 brouard 10209: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 10210: char *p1 = *stri, *p2 = *stri;
1.235 brouard 10211: while (*p2 == ' ')
1.234 brouard 10212: p2++;
10213: /* while ((*p1++ = *p2++) !=0) */
10214: /* ; */
10215: /* do */
10216: /* while (*p2 == ' ') */
10217: /* p2++; */
10218: /* while (*p1++ == *p2++); */
10219: *stri=p2;
1.145 brouard 10220: }
10221:
1.330 brouard 10222: int decoderesult( char resultline[], int nres)
1.230 brouard 10223: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
10224: {
1.235 brouard 10225: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 10226: char resultsav[MAXLINE];
1.330 brouard 10227: /* int resultmodel[MAXLINE]; */
1.234 brouard 10228: int modelresult[MAXLINE];
1.230 brouard 10229: char stra[80], strb[80], strc[80], strd[80],stre[80];
10230:
1.234 brouard 10231: removefirstspace(&resultline);
1.332 ! brouard 10232: printf("decoderesult:%s\n",resultline);
1.230 brouard 10233:
1.332 ! brouard 10234: strcpy(resultsav,resultline);
! 10235: printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline);
1.230 brouard 10236: if (strlen(resultsav) >1){
10237: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
10238: }
1.253 brouard 10239: if(j == 0){ /* Resultline but no = */
10240: TKresult[nres]=0; /* Combination for the nresult and the model */
10241: return (0);
10242: }
1.234 brouard 10243: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.332 ! brouard 10244: printf("ERROR: the number of variables in the resultline which is %d, differs from the number %d of variables used in the model line, %s.\n",j, cptcovs, model);
! 10245: fprintf(ficlog,"ERROR: the number of variables in the resultline which is %d, differs from the number %d of variables used in the model line, %s.\n",j, cptcovs, model);
! 10246: /* return 1;*/
1.234 brouard 10247: }
10248: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
10249: if(nbocc(resultsav,'=') >1){
1.318 brouard 10250: 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 10251: /* 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 10252: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 ! brouard 10253: /* If a blank, then strc="V4=" and strd='\0' */
! 10254: if(strc[0]=='\0'){
! 10255: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
! 10256: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
! 10257: return 1;
! 10258: }
1.234 brouard 10259: }else
10260: cutl(strc,strd,resultsav,'=');
1.318 brouard 10261: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 10262:
1.230 brouard 10263: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 10264: 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 10265: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
10266: /* cptcovsel++; */
10267: if (nbocc(stra,'=') >0)
10268: strcpy(resultsav,stra); /* and analyzes it */
10269: }
1.235 brouard 10270: /* Checking for missing or useless values in comparison of current model needs */
1.332 ! brouard 10271: /* Feeds resultmodel[nres][k1]=k2 for k1th product covariate with age in the model equation fed by the index k2 of the resutline*/
1.318 brouard 10272: 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 10273: if(Typevar[k1]==0){ /* Single covariate in model */
! 10274: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 10275: match=0;
1.318 brouard 10276: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10277: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 10278: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 10279: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 10280: break;
10281: }
10282: }
10283: if(match == 0){
1.332 ! brouard 10284: printf("Error in result line (Dummy single): V%d is missing in result: %s according to model=%s. Tvar[k1=%d]=%d is different from Tvarsel[k2=%d]=%d.\n",Tvar[k1], resultline, model,k1, Tvar[k1], k2, Tvarsel[k2]);
! 10285: fprintf(ficlog,"Error in result line (Dummy single): V%d is missing in result: %s according to model=%s\n",Tvar[k1], resultline, model);
1.310 brouard 10286: return 1;
1.234 brouard 10287: }
1.332 ! brouard 10288: }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*/
! 10289: /* We feed resultmodel[k1]=k2; */
! 10290: match=0;
! 10291: 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 */
! 10292: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
! 10293: modelresult[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 */
! 10294: resultmodel[nres][k1]=k2; /* Added here */
! 10295: printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]);
! 10296: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
! 10297: break;
! 10298: }
! 10299: }
! 10300: if(match == 0){
! 10301: printf("Error in result line (Product with age): V%d is missing in result: %s according to model=%s (Tvarsel[k2=%d]=%d)\n",Tvar[k1], resultline, model, k2, Tvarsel[k2]);
! 10302: fprintf(ficlog,"Error in result line (Product with age): V%d is missing in result: %s according to model=%s\n",Tvar[k1], resultline, model, k2, Tvarsel[k2]);
! 10303: return 1;
! 10304: }
! 10305: }else if(Typevar[k1]==2){ /* Product No age We want to get the position in the resultline of the product in the model line*/
! 10306: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
! 10307: match=0;
! 10308: 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]);
! 10309: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
! 10310: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
! 10311: /* modelresult[k2]=k1; */
! 10312: printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]);
! 10313: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
! 10314: }
! 10315: }
! 10316: if(match == 0){
! 10317: printf("Error in result line (Product without age first variable): V%d is missing in result: %s according to model=%s\n",Tvardk[k1][1], resultline, model);
! 10318: fprintf(ficlog,"Error in result line (Product without age first variable): V%d is missing in result: %s according to model=%s\n",k1,Tvardk[k1][1], resultline, model);
! 10319: return 1;
! 10320: }
! 10321: match=0;
! 10322: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
! 10323: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
! 10324: /* modelresult[k2]=k1;*/
! 10325: printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]);
! 10326: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
! 10327: break;
! 10328: }
! 10329: }
! 10330: if(match == 0){
! 10331: printf("Error in result line (Product without age second variable): V%d is missing in result: %s according to model=%s\n",Tvardk[k1][2], resultline, model);
! 10332: fprintf(ficlog,"Error in result line (Product without age second variable): V%d is missing in result : %s according to model=%s\n",k1,Tvardk[k1][2], resultline, model);
! 10333: return 1;
! 10334: }
! 10335: }/* End of testing */
! 10336: }/* End loop cptcovt
1.235 brouard 10337: /* Checking for missing or useless values in comparison of current model needs */
1.332 ! brouard 10338: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.318 brouard 10339: for(k2=1; k2 <=j;k2++){ /* Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 10340: match=0;
1.318 brouard 10341: 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 10342: if(Typevar[k1]==0){ /* Single only */
1.237 brouard 10343: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.330 brouard 10344: 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 */
1.234 brouard 10345: ++match;
10346: }
10347: }
10348: }
10349: if(match == 0){
1.332 ! brouard 10350: printf("Error in result line: variable V%d is missing in model; result: %s, model=%s\n",Tvarsel[k2], resultline, model);
! 10351: fprintf(ficlog,"Error in result line: variable V%d is missing in model; result: %s, model=%s\n",Tvarsel[k2], resultline, model);
1.310 brouard 10352: return 1;
1.234 brouard 10353: }else if(match > 1){
10354: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
1.310 brouard 10355: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
10356: return 1;
1.234 brouard 10357: }
10358: }
1.235 brouard 10359:
1.234 brouard 10360: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 10361: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 10362: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
10363: /* 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*/
10364: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 10365: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
10366: /* 1 0 0 0 */
10367: /* 2 1 0 0 */
10368: /* 3 0 1 0 */
1.330 brouard 10369: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 10370: /* 5 0 0 1 */
1.330 brouard 10371: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 10372: /* 7 0 1 1 */
10373: /* 8 1 1 1 */
1.237 brouard 10374: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
10375: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
10376: /* V5*age V5 known which value for nres? */
10377: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.330 brouard 10378: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* loop k1 on position in the model line (excluding product) */
1.331 brouard 10379: /* k counting number of combination of single dummies in the equation model */
10380: /* k4 counting single dummies in the equation model */
10381: /* k4q counting single quantitatives in the equation model */
10382: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Dummy and Single */
10383: /* k4+1= position in the resultline V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) */
1.332 ! brouard 10384: /* 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 10385: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 ! brouard 10386: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
! 10387: /* k3 is the position in the nres result line of the k1th variable of the model equation */
! 10388: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
! 10389: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
! 10390: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
! 10391: /* Tvresult[nres][result_position]= id of the dummy variable at the result_position in the nres resultline */
! 10392: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 10393: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 ! brouard 10394: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
! 10395: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
! 10396: 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 10397: k+=Tvalsel[k3]*pow(2,k4); /* nres=1 k1=2 Tvalsel[1]=1 (V4=1); k1=3 k3=2 Tvalsel[2]=0 (V3=0) */
1.332 ! brouard 10398: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Stores the value into the name of the variable. */
! 10399: /* Tinvresult[nres][4]=1 */
1.330 brouard 10400: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
1.237 brouard 10401: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
10402: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.332 ! brouard 10403: precov[nres][k1]=Tvalsel[k3];
! 10404: 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 10405: k4++;;
1.331 brouard 10406: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 10407: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 ! brouard 10408: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 10409: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 ! brouard 10410: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
! 10411: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
! 10412: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.237 brouard 10413: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
10414: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
10415: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 10416: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 ! brouard 10417: precov[nres][k1]=Tvalsel[k3q];
! 10418: 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 10419: k4q++;;
1.331 brouard 10420: }else if( Dummy[k1]==2 ){ /* For dummy with age product */
10421: /* Tvar[k1]; */ /* Age variable */
1.332 ! brouard 10422: /* Wrong we want the value of variable name Tvar[k1] */
! 10423:
! 10424: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
1.331 brouard 10425: 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)*/
10426: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.332 ! brouard 10427: precov[nres][k1]=Tvalsel[k3];
! 10428: 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 10429: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.332 ! brouard 10430: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
1.331 brouard 10431: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
10432: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 ! brouard 10433: precov[nres][k1]=Tvalsel[k3q];
! 10434: printf("Decoderesult Quantitative with age nres=%d, k1=%d, precov[nres=%d][k1=%d]=%.f Tvar[%d]=V%d V(k2q=%d)= Tvarsel[%d]=%d, Tvalsel[%d]=%f\n",nres, k1, nres, k1,precov[nres][k1], k1, Tvar[k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
1.331 brouard 10435: }else if(Typevar[k1]==2 ){ /* For product quant or dummy (not with age) */
1.332 ! brouard 10436: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
! 10437: 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 10438: }else{
1.332 ! brouard 10439: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
! 10440: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 10441: }
10442: }
1.234 brouard 10443:
1.235 brouard 10444: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 10445: return (0);
10446: }
1.235 brouard 10447:
1.230 brouard 10448: int decodemodel( char model[], int lastobs)
10449: /**< This routine decodes the model and returns:
1.224 brouard 10450: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
10451: * - nagesqr = 1 if age*age in the model, otherwise 0.
10452: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
10453: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
10454: * - cptcovage number of covariates with age*products =2
10455: * - cptcovs number of simple covariates
10456: * - 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
10457: * which is a new column after the 9 (ncovcol) variables.
1.319 brouard 10458: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 10459: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
10460: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
10461: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
10462: */
1.319 brouard 10463: /* 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 10464: {
1.238 brouard 10465: int i, j, k, ks, v;
1.227 brouard 10466: int j1, k1, k2, k3, k4;
1.136 brouard 10467: char modelsav[80];
1.145 brouard 10468: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 10469: char *strpt;
1.136 brouard 10470:
1.145 brouard 10471: /*removespace(model);*/
1.136 brouard 10472: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 10473: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 10474: if (strstr(model,"AGE") !=0){
1.192 brouard 10475: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
10476: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 10477: return 1;
10478: }
1.141 brouard 10479: if (strstr(model,"v") !=0){
10480: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
10481: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
10482: return 1;
10483: }
1.187 brouard 10484: strcpy(modelsav,model);
10485: if ((strpt=strstr(model,"age*age")) !=0){
10486: printf(" strpt=%s, model=%s\n",strpt, model);
10487: if(strpt != model){
1.234 brouard 10488: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10489: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10490: corresponding column of parameters.\n",model);
1.234 brouard 10491: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10492: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10493: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 10494: return 1;
1.225 brouard 10495: }
1.187 brouard 10496: nagesqr=1;
10497: if (strstr(model,"+age*age") !=0)
1.234 brouard 10498: substrchaine(modelsav, model, "+age*age");
1.187 brouard 10499: else if (strstr(model,"age*age+") !=0)
1.234 brouard 10500: substrchaine(modelsav, model, "age*age+");
1.187 brouard 10501: else
1.234 brouard 10502: substrchaine(modelsav, model, "age*age");
1.187 brouard 10503: }else
10504: nagesqr=0;
10505: if (strlen(modelsav) >1){
10506: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
10507: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 10508: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 10509: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 10510: * cst, age and age*age
10511: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
10512: /* including age products which are counted in cptcovage.
10513: * but the covariates which are products must be treated
10514: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 10515: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
10516: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 10517:
10518:
1.187 brouard 10519: /* Design
10520: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
10521: * < ncovcol=8 >
10522: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
10523: * k= 1 2 3 4 5 6 7 8
10524: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
10525: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 10526: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
10527: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 10528: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
10529: * Tage[++cptcovage]=k
10530: * if products, new covar are created after ncovcol with k1
10531: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
10532: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
10533: * 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
10534: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
10535: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
10536: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
10537: * < ncovcol=8 >
10538: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
10539: * k= 1 2 3 4 5 6 7 8 9 10 11 12
10540: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
1.319 brouard 10541: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
1.187 brouard 10542: * p Tprod[1]@2={ 6, 5}
10543: *p Tvard[1][1]@4= {7, 8, 5, 6}
10544: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
10545: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 10546: *How to reorganize? Tvars(orted)
1.187 brouard 10547: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
10548: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
10549: * {2, 1, 4, 8, 5, 6, 3, 7}
10550: * Struct []
10551: */
1.225 brouard 10552:
1.187 brouard 10553: /* This loop fills the array Tvar from the string 'model'.*/
10554: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
10555: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
10556: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
10557: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
10558: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
10559: /* k=1 Tvar[1]=2 (from V2) */
10560: /* k=5 Tvar[5] */
10561: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 10562: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 10563: /* } */
1.198 brouard 10564: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 10565: /*
10566: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 10567: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
10568: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
10569: }
1.187 brouard 10570: cptcovage=0;
1.319 brouard 10571: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
10572: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
10573: 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" */
10574: if (nbocc(modelsav,'+')==0)
10575: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 10576: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
10577: /*scanf("%d",i);*/
1.319 brouard 10578: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age */
10579: cutl(strc,strd,strb,'*'); /**< k=1 strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
1.234 brouard 10580: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
10581: /* covar is not filled and then is empty */
10582: cptcovprod--;
10583: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
1.319 brouard 10584: Tvar[k]=atoi(stre); /* V2+V1+V5*age+V4+V3*age Tvar[5]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
1.234 brouard 10585: Typevar[k]=1; /* 1 for age product */
1.319 brouard 10586: cptcovage++; /* Counts the number of covariates which include age as a product */
10587: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
1.234 brouard 10588: /*printf("stre=%s ", stre);*/
10589: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
10590: cptcovprod--;
10591: cutl(stre,strb,strc,'V');
10592: Tvar[k]=atoi(stre);
10593: Typevar[k]=1; /* 1 for age product */
10594: cptcovage++;
10595: Tage[cptcovage]=k;
10596: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
10597: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
10598: cptcovn++;
10599: cptcovprodnoage++;k1++;
10600: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
10601: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
10602: because this model-covariate is a construction we invent a new column
10603: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
1.319 brouard 10604: If already ncovcol=4 and model=V2 + V1 +V1*V4 +age*V3 +V3*V2
10605: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
10606: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=4 etc */
1.234 brouard 10607: Typevar[k]=2; /* 2 for double fixed dummy covariates */
10608: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
10609: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
1.319 brouard 10610: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
1.234 brouard 10611: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
1.330 brouard 10612: Tvardk[k][1] =atoi(strc); /* m 1 for V1*/
1.234 brouard 10613: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
1.330 brouard 10614: Tvardk[k][2] =atoi(stre); /* n 4 for V4*/
1.234 brouard 10615: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
10616: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
10617: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 10618: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 10619: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
10620: for (i=1; i<=lastobs;i++){
10621: /* Computes the new covariate which is a product of
10622: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
10623: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
10624: }
10625: } /* End age is not in the model */
10626: } /* End if model includes a product */
1.319 brouard 10627: else { /* not a product */
1.234 brouard 10628: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
10629: /* scanf("%d",i);*/
10630: cutl(strd,strc,strb,'V');
10631: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
10632: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
10633: Tvar[k]=atoi(strd);
10634: Typevar[k]=0; /* 0 for simple covariates */
10635: }
10636: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 10637: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 10638: scanf("%d",i);*/
1.187 brouard 10639: } /* end of loop + on total covariates */
10640: } /* end if strlen(modelsave == 0) age*age might exist */
10641: } /* end if strlen(model == 0) */
1.136 brouard 10642:
10643: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
10644: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 10645:
1.136 brouard 10646: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 10647: printf("cptcovprod=%d ", cptcovprod);
10648: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
10649: scanf("%d ",i);*/
10650:
10651:
1.230 brouard 10652: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
10653: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 10654: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
10655: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
10656: k = 1 2 3 4 5 6 7 8 9
10657: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 10658: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 10659: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
10660: Dummy[k] 1 0 0 0 3 1 1 2 3
10661: Tmodelind[combination of covar]=k;
1.225 brouard 10662: */
10663: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 10664: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 10665: /* 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 10666: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 10667: printf("Model=1+age+%s\n\
1.227 brouard 10668: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10669: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10670: 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 10671: fprintf(ficlog,"Model=1+age+%s\n\
1.227 brouard 10672: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10673: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10674: 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);
1.285 brouard 10675: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 10676: for(k=1, ncovf=0, nsd=0, nsq=0, ncovv=0, ncova=0, ncoveff=0, nqfveff=0, ntveff=0, nqtveff=0;k<=cptcovt; k++){ /* or cptocvt */
10677: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 10678: Fixed[k]= 0;
10679: Dummy[k]= 0;
1.225 brouard 10680: ncoveff++;
1.232 brouard 10681: ncovf++;
1.234 brouard 10682: nsd++;
10683: modell[k].maintype= FTYPE;
10684: TvarsD[nsd]=Tvar[k];
10685: TvarsDind[nsd]=k;
1.330 brouard 10686: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 10687: TvarF[ncovf]=Tvar[k];
10688: TvarFind[ncovf]=k;
10689: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10690: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10691: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
10692: Fixed[k]= 0;
10693: Dummy[k]= 0;
10694: ncoveff++;
10695: ncovf++;
10696: modell[k].maintype= FTYPE;
10697: TvarF[ncovf]=Tvar[k];
1.330 brouard 10698: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
1.234 brouard 10699: TvarFind[ncovf]=k;
1.230 brouard 10700: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 10701: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 10702: }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 10703: Fixed[k]= 0;
10704: Dummy[k]= 1;
1.230 brouard 10705: nqfveff++;
1.234 brouard 10706: modell[k].maintype= FTYPE;
10707: modell[k].subtype= FQ;
10708: nsq++;
10709: TvarsQ[nsq]=Tvar[k];
10710: TvarsQind[nsq]=k;
1.232 brouard 10711: ncovf++;
1.234 brouard 10712: TvarF[ncovf]=Tvar[k];
10713: TvarFind[ncovf]=k;
1.231 brouard 10714: 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 10715: 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 10716: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 10717: Fixed[k]= 1;
10718: Dummy[k]= 0;
1.225 brouard 10719: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 10720: modell[k].maintype= VTYPE;
10721: modell[k].subtype= VD;
10722: nsd++;
10723: TvarsD[nsd]=Tvar[k];
10724: TvarsDind[nsd]=k;
1.330 brouard 10725: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 10726: ncovv++; /* Only simple time varying variables */
10727: TvarV[ncovv]=Tvar[k];
1.242 brouard 10728: 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 10729: 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 */
10730: 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 10731: 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);
10732: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 10733: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 10734: Fixed[k]= 1;
10735: Dummy[k]= 1;
10736: nqtveff++;
10737: modell[k].maintype= VTYPE;
10738: modell[k].subtype= VQ;
10739: ncovv++; /* Only simple time varying variables */
10740: nsq++;
1.319 brouard 10741: TvarsQ[nsq]=Tvar[k]; /* k=1 Tvar=5 nsq=1 TvarsQ[1]=5 */
1.332 ! brouard 10742: TvarsQind[nsq]=k; /* For single quantitative covariate gives the model position of each single quantitative covariate */
1.234 brouard 10743: TvarV[ncovv]=Tvar[k];
1.242 brouard 10744: 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 10745: 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 */
10746: 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 10747: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
10748: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
10749: printf("Quasi TmodelQind[%d]=%d,Tvar[TmodelQind[%d]]=V%d, ncovcol=%d, nqv=%d, ntv=%d,Tvar[k]- ncovcol-nqv-ntv=%d\n",nqtveff,k,nqtveff,Tvar[k], ncovcol, nqv, ntv, Tvar[k]- ncovcol-nqv-ntv);
1.228 brouard 10750: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 10751: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 10752: ncova++;
10753: TvarA[ncova]=Tvar[k];
10754: TvarAind[ncova]=k;
1.231 brouard 10755: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 10756: Fixed[k]= 2;
10757: Dummy[k]= 2;
10758: modell[k].maintype= ATYPE;
10759: modell[k].subtype= APFD;
10760: /* ncoveff++; */
1.227 brouard 10761: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 10762: Fixed[k]= 2;
10763: Dummy[k]= 3;
10764: modell[k].maintype= ATYPE;
10765: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
10766: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 10767: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 10768: Fixed[k]= 3;
10769: Dummy[k]= 2;
10770: modell[k].maintype= ATYPE;
10771: modell[k].subtype= APVD; /* Product age * varying dummy */
10772: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 10773: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10774: Fixed[k]= 3;
10775: Dummy[k]= 3;
10776: modell[k].maintype= ATYPE;
10777: modell[k].subtype= APVQ; /* Product age * varying quantitative */
10778: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 10779: }
10780: }else if (Typevar[k] == 2) { /* product without age */
10781: k1=Tposprod[k];
10782: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 10783: if(Tvard[k1][2] <=ncovcol){
10784: Fixed[k]= 1;
10785: Dummy[k]= 0;
10786: modell[k].maintype= FTYPE;
10787: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
10788: ncovf++; /* Fixed variables without age */
10789: TvarF[ncovf]=Tvar[k];
10790: TvarFind[ncovf]=k;
10791: }else if(Tvard[k1][2] <=ncovcol+nqv){
10792: Fixed[k]= 0; /* or 2 ?*/
10793: Dummy[k]= 1;
10794: modell[k].maintype= FTYPE;
10795: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
10796: ncovf++; /* Varying variables without age */
10797: TvarF[ncovf]=Tvar[k];
10798: TvarFind[ncovf]=k;
10799: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10800: Fixed[k]= 1;
10801: Dummy[k]= 0;
10802: modell[k].maintype= VTYPE;
10803: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
10804: ncovv++; /* Varying variables without age */
10805: TvarV[ncovv]=Tvar[k];
10806: TvarVind[ncovv]=k;
10807: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10808: Fixed[k]= 1;
10809: Dummy[k]= 1;
10810: modell[k].maintype= VTYPE;
10811: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
10812: ncovv++; /* Varying variables without age */
10813: TvarV[ncovv]=Tvar[k];
10814: TvarVind[ncovv]=k;
10815: }
1.227 brouard 10816: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 10817: if(Tvard[k1][2] <=ncovcol){
10818: Fixed[k]= 0; /* or 2 ?*/
10819: Dummy[k]= 1;
10820: modell[k].maintype= FTYPE;
10821: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
10822: ncovf++; /* Fixed variables without age */
10823: TvarF[ncovf]=Tvar[k];
10824: TvarFind[ncovf]=k;
10825: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10826: Fixed[k]= 1;
10827: Dummy[k]= 1;
10828: modell[k].maintype= VTYPE;
10829: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
10830: ncovv++; /* Varying variables without age */
10831: TvarV[ncovv]=Tvar[k];
10832: TvarVind[ncovv]=k;
10833: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10834: Fixed[k]= 1;
10835: Dummy[k]= 1;
10836: modell[k].maintype= VTYPE;
10837: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
10838: ncovv++; /* Varying variables without age */
10839: TvarV[ncovv]=Tvar[k];
10840: TvarVind[ncovv]=k;
10841: ncovv++; /* Varying variables without age */
10842: TvarV[ncovv]=Tvar[k];
10843: TvarVind[ncovv]=k;
10844: }
1.227 brouard 10845: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 10846: if(Tvard[k1][2] <=ncovcol){
10847: Fixed[k]= 1;
10848: Dummy[k]= 1;
10849: modell[k].maintype= VTYPE;
10850: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
10851: ncovv++; /* Varying variables without age */
10852: TvarV[ncovv]=Tvar[k];
10853: TvarVind[ncovv]=k;
10854: }else if(Tvard[k1][2] <=ncovcol+nqv){
10855: Fixed[k]= 1;
10856: Dummy[k]= 1;
10857: modell[k].maintype= VTYPE;
10858: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
10859: ncovv++; /* Varying variables without age */
10860: TvarV[ncovv]=Tvar[k];
10861: TvarVind[ncovv]=k;
10862: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10863: Fixed[k]= 1;
10864: Dummy[k]= 0;
10865: modell[k].maintype= VTYPE;
10866: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
10867: ncovv++; /* Varying variables without age */
10868: TvarV[ncovv]=Tvar[k];
10869: TvarVind[ncovv]=k;
10870: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10871: Fixed[k]= 1;
10872: Dummy[k]= 1;
10873: modell[k].maintype= VTYPE;
10874: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
10875: ncovv++; /* Varying variables without age */
10876: TvarV[ncovv]=Tvar[k];
10877: TvarVind[ncovv]=k;
10878: }
1.227 brouard 10879: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10880: if(Tvard[k1][2] <=ncovcol){
10881: Fixed[k]= 1;
10882: Dummy[k]= 1;
10883: modell[k].maintype= VTYPE;
10884: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
10885: ncovv++; /* Varying variables without age */
10886: TvarV[ncovv]=Tvar[k];
10887: TvarVind[ncovv]=k;
10888: }else if(Tvard[k1][2] <=ncovcol+nqv){
10889: Fixed[k]= 1;
10890: Dummy[k]= 1;
10891: modell[k].maintype= VTYPE;
10892: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
10893: ncovv++; /* Varying variables without age */
10894: TvarV[ncovv]=Tvar[k];
10895: TvarVind[ncovv]=k;
10896: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10897: Fixed[k]= 1;
10898: Dummy[k]= 1;
10899: modell[k].maintype= VTYPE;
10900: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
10901: ncovv++; /* Varying variables without age */
10902: TvarV[ncovv]=Tvar[k];
10903: TvarVind[ncovv]=k;
10904: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10905: Fixed[k]= 1;
10906: Dummy[k]= 1;
10907: modell[k].maintype= VTYPE;
10908: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
10909: ncovv++; /* Varying variables without age */
10910: TvarV[ncovv]=Tvar[k];
10911: TvarVind[ncovv]=k;
10912: }
1.227 brouard 10913: }else{
1.240 brouard 10914: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10915: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10916: } /*end k1*/
1.225 brouard 10917: }else{
1.226 brouard 10918: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10919: 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 10920: }
1.227 brouard 10921: 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]);
1.231 brouard 10922: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10923: 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]);
10924: }
10925: /* Searching for doublons in the model */
10926: for(k1=1; k1<= cptcovt;k1++){
10927: for(k2=1; k2 <k1;k2++){
1.285 brouard 10928: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10929: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10930: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10931: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10932: printf("Error duplication in the model=%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]);
10933: fprintf(ficlog,"Error duplication in the model=%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 10934: return(1);
10935: }
10936: }else if (Typevar[k1] ==2){
10937: k3=Tposprod[k1];
10938: k4=Tposprod[k2];
10939: 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])) ){
10940: printf("Error duplication in the model=%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]]);
10941: fprintf(ficlog,"Error duplication in the model=%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);
10942: return(1);
10943: }
10944: }
1.227 brouard 10945: }
10946: }
1.225 brouard 10947: }
10948: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10949: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10950: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10951: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10952: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10953: /*endread:*/
1.225 brouard 10954: printf("Exiting decodemodel: ");
10955: return (1);
1.136 brouard 10956: }
10957:
1.169 brouard 10958: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10959: {/* Check ages at death */
1.136 brouard 10960: int i, m;
1.218 brouard 10961: int firstone=0;
10962:
1.136 brouard 10963: for (i=1; i<=imx; i++) {
10964: for(m=2; (m<= maxwav); m++) {
10965: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10966: anint[m][i]=9999;
1.216 brouard 10967: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10968: s[m][i]=-1;
1.136 brouard 10969: }
10970: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10971: *nberr = *nberr + 1;
1.218 brouard 10972: if(firstone == 0){
10973: firstone=1;
1.260 brouard 10974: 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 10975: }
1.262 brouard 10976: 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 10977: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10978: }
10979: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10980: (*nberr)++;
1.259 brouard 10981: 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 10982: 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 10983: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10984: }
10985: }
10986: }
10987:
10988: for (i=1; i<=imx; i++) {
10989: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10990: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10991: 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 10992: if (s[m][i] >= nlstate+1) {
1.169 brouard 10993: if(agedc[i]>0){
10994: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10995: agev[m][i]=agedc[i];
1.214 brouard 10996: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10997: }else {
1.136 brouard 10998: if ((int)andc[i]!=9999){
10999: nbwarn++;
11000: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
11001: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
11002: agev[m][i]=-1;
11003: }
11004: }
1.169 brouard 11005: } /* agedc > 0 */
1.214 brouard 11006: } /* end if */
1.136 brouard 11007: else if(s[m][i] !=9){ /* Standard case, age in fractional
11008: years but with the precision of a month */
11009: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
11010: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
11011: agev[m][i]=1;
11012: else if(agev[m][i] < *agemin){
11013: *agemin=agev[m][i];
11014: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
11015: }
11016: else if(agev[m][i] >*agemax){
11017: *agemax=agev[m][i];
1.156 brouard 11018: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 11019: }
11020: /*agev[m][i]=anint[m][i]-annais[i];*/
11021: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 11022: } /* en if 9*/
1.136 brouard 11023: else { /* =9 */
1.214 brouard 11024: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 11025: agev[m][i]=1;
11026: s[m][i]=-1;
11027: }
11028: }
1.214 brouard 11029: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 11030: agev[m][i]=1;
1.214 brouard 11031: else{
11032: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
11033: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
11034: agev[m][i]=0;
11035: }
11036: } /* End for lastpass */
11037: }
1.136 brouard 11038:
11039: for (i=1; i<=imx; i++) {
11040: for(m=firstpass; (m<=lastpass); m++){
11041: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 11042: (*nberr)++;
1.136 brouard 11043: 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);
11044: 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);
11045: return 1;
11046: }
11047: }
11048: }
11049:
11050: /*for (i=1; i<=imx; i++){
11051: for (m=firstpass; (m<lastpass); m++){
11052: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
11053: }
11054:
11055: }*/
11056:
11057:
1.139 brouard 11058: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
11059: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 11060:
11061: return (0);
1.164 brouard 11062: /* endread:*/
1.136 brouard 11063: printf("Exiting calandcheckages: ");
11064: return (1);
11065: }
11066:
1.172 brouard 11067: #if defined(_MSC_VER)
11068: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
11069: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
11070: //#include "stdafx.h"
11071: //#include <stdio.h>
11072: //#include <tchar.h>
11073: //#include <windows.h>
11074: //#include <iostream>
11075: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
11076:
11077: LPFN_ISWOW64PROCESS fnIsWow64Process;
11078:
11079: BOOL IsWow64()
11080: {
11081: BOOL bIsWow64 = FALSE;
11082:
11083: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
11084: // (HANDLE, PBOOL);
11085:
11086: //LPFN_ISWOW64PROCESS fnIsWow64Process;
11087:
11088: HMODULE module = GetModuleHandle(_T("kernel32"));
11089: const char funcName[] = "IsWow64Process";
11090: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
11091: GetProcAddress(module, funcName);
11092:
11093: if (NULL != fnIsWow64Process)
11094: {
11095: if (!fnIsWow64Process(GetCurrentProcess(),
11096: &bIsWow64))
11097: //throw std::exception("Unknown error");
11098: printf("Unknown error\n");
11099: }
11100: return bIsWow64 != FALSE;
11101: }
11102: #endif
1.177 brouard 11103:
1.191 brouard 11104: void syscompilerinfo(int logged)
1.292 brouard 11105: {
11106: #include <stdint.h>
11107:
11108: /* #include "syscompilerinfo.h"*/
1.185 brouard 11109: /* command line Intel compiler 32bit windows, XP compatible:*/
11110: /* /GS /W3 /Gy
11111: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
11112: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
11113: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 11114: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
11115: */
11116: /* 64 bits */
1.185 brouard 11117: /*
11118: /GS /W3 /Gy
11119: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
11120: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
11121: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
11122: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
11123: /* Optimization are useless and O3 is slower than O2 */
11124: /*
11125: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
11126: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
11127: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
11128: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
11129: */
1.186 brouard 11130: /* Link is */ /* /OUT:"visual studio
1.185 brouard 11131: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
11132: /PDB:"visual studio
11133: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
11134: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
11135: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
11136: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
11137: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
11138: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
11139: uiAccess='false'"
11140: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
11141: /NOLOGO /TLBID:1
11142: */
1.292 brouard 11143:
11144:
1.177 brouard 11145: #if defined __INTEL_COMPILER
1.178 brouard 11146: #if defined(__GNUC__)
11147: struct utsname sysInfo; /* For Intel on Linux and OS/X */
11148: #endif
1.177 brouard 11149: #elif defined(__GNUC__)
1.179 brouard 11150: #ifndef __APPLE__
1.174 brouard 11151: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 11152: #endif
1.177 brouard 11153: struct utsname sysInfo;
1.178 brouard 11154: int cross = CROSS;
11155: if (cross){
11156: printf("Cross-");
1.191 brouard 11157: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 11158: }
1.174 brouard 11159: #endif
11160:
1.191 brouard 11161: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 11162: #if defined(__clang__)
1.191 brouard 11163: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 11164: #endif
11165: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 11166: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 11167: #endif
11168: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 11169: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 11170: #endif
11171: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 11172: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 11173: #endif
11174: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 11175: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 11176: #endif
11177: #if defined(_MSC_VER)
1.191 brouard 11178: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 11179: #endif
11180: #if defined(__PGI)
1.191 brouard 11181: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 11182: #endif
11183: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 11184: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 11185: #endif
1.191 brouard 11186: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 11187:
1.167 brouard 11188: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
11189: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
11190: // Windows (x64 and x86)
1.191 brouard 11191: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 11192: #elif __unix__ // all unices, not all compilers
11193: // Unix
1.191 brouard 11194: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 11195: #elif __linux__
11196: // linux
1.191 brouard 11197: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 11198: #elif __APPLE__
1.174 brouard 11199: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 11200: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 11201: #endif
11202:
11203: /* __MINGW32__ */
11204: /* __CYGWIN__ */
11205: /* __MINGW64__ */
11206: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
11207: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
11208: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
11209: /* _WIN64 // Defined for applications for Win64. */
11210: /* _M_X64 // Defined for compilations that target x64 processors. */
11211: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 11212:
1.167 brouard 11213: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 11214: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 11215: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 11216: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 11217: #else
1.191 brouard 11218: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 11219: #endif
11220:
1.169 brouard 11221: #if defined(__GNUC__)
11222: # if defined(__GNUC_PATCHLEVEL__)
11223: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11224: + __GNUC_MINOR__ * 100 \
11225: + __GNUC_PATCHLEVEL__)
11226: # else
11227: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11228: + __GNUC_MINOR__ * 100)
11229: # endif
1.174 brouard 11230: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 11231: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 11232:
11233: if (uname(&sysInfo) != -1) {
11234: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 11235: 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 11236: }
11237: else
11238: perror("uname() error");
1.179 brouard 11239: //#ifndef __INTEL_COMPILER
11240: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 11241: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 11242: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 11243: #endif
1.169 brouard 11244: #endif
1.172 brouard 11245:
1.286 brouard 11246: // void main ()
1.172 brouard 11247: // {
1.169 brouard 11248: #if defined(_MSC_VER)
1.174 brouard 11249: if (IsWow64()){
1.191 brouard 11250: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
11251: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 11252: }
11253: else{
1.191 brouard 11254: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
11255: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 11256: }
1.172 brouard 11257: // printf("\nPress Enter to continue...");
11258: // getchar();
11259: // }
11260:
1.169 brouard 11261: #endif
11262:
1.167 brouard 11263:
1.219 brouard 11264: }
1.136 brouard 11265:
1.219 brouard 11266: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 11267: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 ! brouard 11268: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 11269: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 11270: /* double ftolpl = 1.e-10; */
1.180 brouard 11271: double age, agebase, agelim;
1.203 brouard 11272: double tot;
1.180 brouard 11273:
1.202 brouard 11274: strcpy(filerespl,"PL_");
11275: strcat(filerespl,fileresu);
11276: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 11277: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
11278: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 11279: }
1.288 brouard 11280: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
11281: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 11282: pstamp(ficrespl);
1.288 brouard 11283: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 11284: fprintf(ficrespl,"#Age ");
11285: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
11286: fprintf(ficrespl,"\n");
1.180 brouard 11287:
1.219 brouard 11288: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 11289:
1.219 brouard 11290: agebase=ageminpar;
11291: agelim=agemaxpar;
1.180 brouard 11292:
1.227 brouard 11293: /* i1=pow(2,ncoveff); */
1.234 brouard 11294: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 11295: if (cptcovn < 1){i1=1;}
1.180 brouard 11296:
1.238 brouard 11297: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
11298: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 11299: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 11300: continue;
1.235 brouard 11301:
1.238 brouard 11302: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11303: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
11304: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
11305: /* k=k+1; */
11306: /* to clean */
1.332 ! brouard 11307: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 11308: fprintf(ficrespl,"#******");
11309: printf("#******");
11310: fprintf(ficlog,"#******");
11311: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
1.332 ! brouard 11312: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
! 11313: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /* Here problem for varying dummy*/
! 11314: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
! 11315: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.238 brouard 11316: }
11317: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
11318: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11319: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11320: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11321: }
11322: fprintf(ficrespl,"******\n");
11323: printf("******\n");
11324: fprintf(ficlog,"******\n");
11325: if(invalidvarcomb[k]){
11326: printf("\nCombination (%d) ignored because no case \n",k);
11327: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
11328: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
11329: continue;
11330: }
1.219 brouard 11331:
1.238 brouard 11332: fprintf(ficrespl,"#Age ");
11333: for(j=1;j<=cptcoveff;j++) {
1.332 ! brouard 11334: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.238 brouard 11335: }
11336: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
11337: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 11338:
1.238 brouard 11339: for (age=agebase; age<=agelim; age++){
11340: /* for (age=agebase; age<=agebase; age++){ */
11341: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
11342: fprintf(ficrespl,"%.0f ",age );
11343: for(j=1;j<=cptcoveff;j++)
1.332 ! brouard 11344: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.238 brouard 11345: tot=0.;
11346: for(i=1; i<=nlstate;i++){
11347: tot += prlim[i][i];
11348: fprintf(ficrespl," %.5f", prlim[i][i]);
11349: }
11350: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
11351: } /* Age */
11352: /* was end of cptcod */
11353: } /* cptcov */
11354: } /* nres */
1.219 brouard 11355: return 0;
1.180 brouard 11356: }
11357:
1.218 brouard 11358: 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 11359: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 11360:
11361: /* Computes the back prevalence limit for any combination of covariate values
11362: * at any age between ageminpar and agemaxpar
11363: */
1.235 brouard 11364: int i, j, k, i1, nres=0 ;
1.217 brouard 11365: /* double ftolpl = 1.e-10; */
11366: double age, agebase, agelim;
11367: double tot;
1.218 brouard 11368: /* double ***mobaverage; */
11369: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 11370:
11371: strcpy(fileresplb,"PLB_");
11372: strcat(fileresplb,fileresu);
11373: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 11374: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
11375: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 11376: }
1.288 brouard 11377: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
11378: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 11379: pstamp(ficresplb);
1.288 brouard 11380: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 11381: fprintf(ficresplb,"#Age ");
11382: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
11383: fprintf(ficresplb,"\n");
11384:
1.218 brouard 11385:
11386: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
11387:
11388: agebase=ageminpar;
11389: agelim=agemaxpar;
11390:
11391:
1.227 brouard 11392: i1=pow(2,cptcoveff);
1.218 brouard 11393: if (cptcovn < 1){i1=1;}
1.227 brouard 11394:
1.238 brouard 11395: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11396: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 11397: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 11398: continue;
1.332 ! brouard 11399: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 11400: fprintf(ficresplb,"#******");
11401: printf("#******");
11402: fprintf(ficlog,"#******");
11403: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
1.332 ! brouard 11404: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
! 11405: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
! 11406: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.238 brouard 11407: }
11408: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 ! brouard 11409: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
! 11410: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
! 11411: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
1.238 brouard 11412: }
11413: fprintf(ficresplb,"******\n");
11414: printf("******\n");
11415: fprintf(ficlog,"******\n");
11416: if(invalidvarcomb[k]){
11417: printf("\nCombination (%d) ignored because no cases \n",k);
11418: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
11419: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
11420: continue;
11421: }
1.218 brouard 11422:
1.238 brouard 11423: fprintf(ficresplb,"#Age ");
11424: for(j=1;j<=cptcoveff;j++) {
1.332 ! brouard 11425: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.238 brouard 11426: }
11427: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
11428: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 11429:
11430:
1.238 brouard 11431: for (age=agebase; age<=agelim; age++){
11432: /* for (age=agebase; age<=agebase; age++){ */
11433: if(mobilavproj > 0){
11434: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
11435: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11436: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 11437: }else if (mobilavproj == 0){
11438: 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);
11439: 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);
11440: exit(1);
11441: }else{
11442: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11443: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 11444: /* printf("TOTOT\n"); */
11445: /* exit(1); */
1.238 brouard 11446: }
11447: fprintf(ficresplb,"%.0f ",age );
11448: for(j=1;j<=cptcoveff;j++)
1.332 ! brouard 11449: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.238 brouard 11450: tot=0.;
11451: for(i=1; i<=nlstate;i++){
11452: tot += bprlim[i][i];
11453: fprintf(ficresplb," %.5f", bprlim[i][i]);
11454: }
11455: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
11456: } /* Age */
11457: /* was end of cptcod */
1.255 brouard 11458: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 11459: } /* end of any combination */
11460: } /* end of nres */
1.218 brouard 11461: /* hBijx(p, bage, fage); */
11462: /* fclose(ficrespijb); */
11463:
11464: return 0;
1.217 brouard 11465: }
1.218 brouard 11466:
1.180 brouard 11467: int hPijx(double *p, int bage, int fage){
11468: /*------------- h Pij x at various ages ------------*/
11469:
11470: int stepsize;
11471: int agelim;
11472: int hstepm;
11473: int nhstepm;
1.235 brouard 11474: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 11475:
11476: double agedeb;
11477: double ***p3mat;
11478:
1.201 brouard 11479: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 11480: if((ficrespij=fopen(filerespij,"w"))==NULL) {
11481: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
11482: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
11483: }
11484: printf("Computing pij: result on file '%s' \n", filerespij);
11485: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
11486:
11487: stepsize=(int) (stepm+YEARM-1)/YEARM;
11488: /*if (stepm<=24) stepsize=2;*/
11489:
11490: agelim=AGESUP;
11491: hstepm=stepsize*YEARM; /* Every year of age */
11492: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 11493:
1.180 brouard 11494: /* hstepm=1; aff par mois*/
11495: pstamp(ficrespij);
11496: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 11497: i1= pow(2,cptcoveff);
1.218 brouard 11498: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11499: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11500: /* k=k+1; */
1.235 brouard 11501: for(nres=1; nres <= nresult; nres++) /* For each resultline */
11502: for(k=1; k<=i1;k++){
1.253 brouard 11503: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 11504: continue;
1.183 brouard 11505: fprintf(ficrespij,"\n#****** ");
1.227 brouard 11506: for(j=1;j<=cptcoveff;j++)
1.332 ! brouard 11507: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.235 brouard 11508: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
11509: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11510: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11511: }
1.183 brouard 11512: fprintf(ficrespij,"******\n");
11513:
11514: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
11515: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
11516: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
11517:
11518: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 11519:
1.183 brouard 11520: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11521: oldm=oldms;savm=savms;
1.235 brouard 11522: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 11523: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
11524: for(i=1; i<=nlstate;i++)
11525: for(j=1; j<=nlstate+ndeath;j++)
11526: fprintf(ficrespij," %1d-%1d",i,j);
11527: fprintf(ficrespij,"\n");
11528: for (h=0; h<=nhstepm; h++){
11529: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11530: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 11531: for(i=1; i<=nlstate;i++)
11532: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 11533: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 11534: fprintf(ficrespij,"\n");
11535: }
1.183 brouard 11536: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11537: fprintf(ficrespij,"\n");
11538: }
1.180 brouard 11539: /*}*/
11540: }
1.218 brouard 11541: return 0;
1.180 brouard 11542: }
1.218 brouard 11543:
11544: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 11545: /*------------- h Bij x at various ages ------------*/
11546:
11547: int stepsize;
1.218 brouard 11548: /* int agelim; */
11549: int ageminl;
1.217 brouard 11550: int hstepm;
11551: int nhstepm;
1.238 brouard 11552: int h, i, i1, j, k, nres;
1.218 brouard 11553:
1.217 brouard 11554: double agedeb;
11555: double ***p3mat;
1.218 brouard 11556:
11557: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
11558: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
11559: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11560: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11561: }
11562: printf("Computing pij back: result on file '%s' \n", filerespijb);
11563: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
11564:
11565: stepsize=(int) (stepm+YEARM-1)/YEARM;
11566: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 11567:
1.218 brouard 11568: /* agelim=AGESUP; */
1.289 brouard 11569: ageminl=AGEINF; /* was 30 */
1.218 brouard 11570: hstepm=stepsize*YEARM; /* Every year of age */
11571: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
11572:
11573: /* hstepm=1; aff par mois*/
11574: pstamp(ficrespijb);
1.255 brouard 11575: 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 11576: i1= pow(2,cptcoveff);
1.218 brouard 11577: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11578: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11579: /* k=k+1; */
1.238 brouard 11580: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11581: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 11582: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 11583: continue;
11584: fprintf(ficrespijb,"\n#****** ");
11585: for(j=1;j<=cptcoveff;j++)
1.332 ! brouard 11586: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.238 brouard 11587: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 ! brouard 11588: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
1.238 brouard 11589: }
11590: fprintf(ficrespijb,"******\n");
1.264 brouard 11591: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 11592: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
11593: continue;
11594: }
11595:
11596: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
11597: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
11598: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
1.297 brouard 11599: 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 */
11600: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
1.238 brouard 11601:
11602: /* nhstepm=nhstepm*YEARM; aff par mois*/
11603:
1.266 brouard 11604: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
11605: /* and memory limitations if stepm is small */
11606:
1.238 brouard 11607: /* oldm=oldms;savm=savms; */
11608: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.325 brouard 11609: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
1.238 brouard 11610: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 11611: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 11612: for(i=1; i<=nlstate;i++)
11613: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 11614: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 11615: fprintf(ficrespijb,"\n");
1.238 brouard 11616: for (h=0; h<=nhstepm; h++){
11617: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11618: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
11619: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
11620: for(i=1; i<=nlstate;i++)
11621: for(j=1; j<=nlstate+ndeath;j++)
1.325 brouard 11622: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.238 brouard 11623: fprintf(ficrespijb,"\n");
11624: }
11625: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11626: fprintf(ficrespijb,"\n");
11627: } /* end age deb */
11628: } /* end combination */
11629: } /* end nres */
1.218 brouard 11630: return 0;
11631: } /* hBijx */
1.217 brouard 11632:
1.180 brouard 11633:
1.136 brouard 11634: /***********************************************/
11635: /**************** Main Program *****************/
11636: /***********************************************/
11637:
11638: int main(int argc, char *argv[])
11639: {
11640: #ifdef GSL
11641: const gsl_multimin_fminimizer_type *T;
11642: size_t iteri = 0, it;
11643: int rval = GSL_CONTINUE;
11644: int status = GSL_SUCCESS;
11645: double ssval;
11646: #endif
11647: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 11648: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
11649: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 11650: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 11651: int jj, ll, li, lj, lk;
1.136 brouard 11652: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 11653: int num_filled;
1.136 brouard 11654: int itimes;
11655: int NDIM=2;
11656: int vpopbased=0;
1.235 brouard 11657: int nres=0;
1.258 brouard 11658: int endishere=0;
1.277 brouard 11659: int noffset=0;
1.274 brouard 11660: int ncurrv=0; /* Temporary variable */
11661:
1.164 brouard 11662: char ca[32], cb[32];
1.136 brouard 11663: /* FILE *fichtm; *//* Html File */
11664: /* FILE *ficgp;*/ /*Gnuplot File */
11665: struct stat info;
1.191 brouard 11666: double agedeb=0.;
1.194 brouard 11667:
11668: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 11669: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 11670:
1.165 brouard 11671: double fret;
1.191 brouard 11672: double dum=0.; /* Dummy variable */
1.136 brouard 11673: double ***p3mat;
1.218 brouard 11674: /* double ***mobaverage; */
1.319 brouard 11675: double wald;
1.164 brouard 11676:
11677: char line[MAXLINE];
1.197 brouard 11678: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
11679:
1.234 brouard 11680: char modeltemp[MAXLINE];
1.332 ! brouard 11681: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 11682:
1.136 brouard 11683: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 11684: char *tok, *val; /* pathtot */
1.290 brouard 11685: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs declared globally ;*/
1.195 brouard 11686: int c, h , cpt, c2;
1.191 brouard 11687: int jl=0;
11688: int i1, j1, jk, stepsize=0;
1.194 brouard 11689: int count=0;
11690:
1.164 brouard 11691: int *tab;
1.136 brouard 11692: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 11693: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
11694: /* double anprojf, mprojf, jprojf; */
11695: /* double jintmean,mintmean,aintmean; */
11696: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11697: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11698: double yrfproj= 10.0; /* Number of years of forward projections */
11699: double yrbproj= 10.0; /* Number of years of backward projections */
11700: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 11701: int mobilav=0,popforecast=0;
1.191 brouard 11702: int hstepm=0, nhstepm=0;
1.136 brouard 11703: int agemortsup;
11704: float sumlpop=0.;
11705: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
11706: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
11707:
1.191 brouard 11708: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 11709: double ftolpl=FTOL;
11710: double **prlim;
1.217 brouard 11711: double **bprlim;
1.317 brouard 11712: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
11713: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 11714: double ***paramstart; /* Matrix of starting parameter values */
11715: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 11716: double **matcov; /* Matrix of covariance */
1.203 brouard 11717: double **hess; /* Hessian matrix */
1.136 brouard 11718: double ***delti3; /* Scale */
11719: double *delti; /* Scale */
11720: double ***eij, ***vareij;
11721: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 11722:
1.136 brouard 11723: double *epj, vepp;
1.164 brouard 11724:
1.273 brouard 11725: double dateprev1, dateprev2;
1.296 brouard 11726: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
11727: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
11728:
1.217 brouard 11729:
1.136 brouard 11730: double **ximort;
1.145 brouard 11731: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 11732: int *dcwave;
11733:
1.164 brouard 11734: char z[1]="c";
1.136 brouard 11735:
11736: /*char *strt;*/
11737: char strtend[80];
1.126 brouard 11738:
1.164 brouard 11739:
1.126 brouard 11740: /* setlocale (LC_ALL, ""); */
11741: /* bindtextdomain (PACKAGE, LOCALEDIR); */
11742: /* textdomain (PACKAGE); */
11743: /* setlocale (LC_CTYPE, ""); */
11744: /* setlocale (LC_MESSAGES, ""); */
11745:
11746: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 11747: rstart_time = time(NULL);
11748: /* (void) gettimeofday(&start_time,&tzp);*/
11749: start_time = *localtime(&rstart_time);
1.126 brouard 11750: curr_time=start_time;
1.157 brouard 11751: /*tml = *localtime(&start_time.tm_sec);*/
11752: /* strcpy(strstart,asctime(&tml)); */
11753: strcpy(strstart,asctime(&start_time));
1.126 brouard 11754:
11755: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 11756: /* tp.tm_sec = tp.tm_sec +86400; */
11757: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 11758: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
11759: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
11760: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 11761: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 11762: /* strt=asctime(&tmg); */
11763: /* printf("Time(after) =%s",strstart); */
11764: /* (void) time (&time_value);
11765: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
11766: * tm = *localtime(&time_value);
11767: * strstart=asctime(&tm);
11768: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
11769: */
11770:
11771: nberr=0; /* Number of errors and warnings */
11772: nbwarn=0;
1.184 brouard 11773: #ifdef WIN32
11774: _getcwd(pathcd, size);
11775: #else
1.126 brouard 11776: getcwd(pathcd, size);
1.184 brouard 11777: #endif
1.191 brouard 11778: syscompilerinfo(0);
1.196 brouard 11779: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 11780: if(argc <=1){
11781: printf("\nEnter the parameter file name: ");
1.205 brouard 11782: if(!fgets(pathr,FILENAMELENGTH,stdin)){
11783: printf("ERROR Empty parameter file name\n");
11784: goto end;
11785: }
1.126 brouard 11786: i=strlen(pathr);
11787: if(pathr[i-1]=='\n')
11788: pathr[i-1]='\0';
1.156 brouard 11789: i=strlen(pathr);
1.205 brouard 11790: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 11791: pathr[i-1]='\0';
1.205 brouard 11792: }
11793: i=strlen(pathr);
11794: if( i==0 ){
11795: printf("ERROR Empty parameter file name\n");
11796: goto end;
11797: }
11798: for (tok = pathr; tok != NULL; ){
1.126 brouard 11799: printf("Pathr |%s|\n",pathr);
11800: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
11801: printf("val= |%s| pathr=%s\n",val,pathr);
11802: strcpy (pathtot, val);
11803: if(pathr[0] == '\0') break; /* Dirty */
11804: }
11805: }
1.281 brouard 11806: else if (argc<=2){
11807: strcpy(pathtot,argv[1]);
11808: }
1.126 brouard 11809: else{
11810: strcpy(pathtot,argv[1]);
1.281 brouard 11811: strcpy(z,argv[2]);
11812: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 11813: }
11814: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
11815: /*cygwin_split_path(pathtot,path,optionfile);
11816: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
11817: /* cutv(path,optionfile,pathtot,'\\');*/
11818:
11819: /* Split argv[0], imach program to get pathimach */
11820: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
11821: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11822: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11823: /* strcpy(pathimach,argv[0]); */
11824: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
11825: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
11826: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 11827: #ifdef WIN32
11828: _chdir(path); /* Can be a relative path */
11829: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
11830: #else
1.126 brouard 11831: chdir(path); /* Can be a relative path */
1.184 brouard 11832: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
11833: #endif
11834: printf("Current directory %s!\n",pathcd);
1.126 brouard 11835: strcpy(command,"mkdir ");
11836: strcat(command,optionfilefiname);
11837: if((outcmd=system(command)) != 0){
1.169 brouard 11838: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 11839: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
11840: /* fclose(ficlog); */
11841: /* exit(1); */
11842: }
11843: /* if((imk=mkdir(optionfilefiname))<0){ */
11844: /* perror("mkdir"); */
11845: /* } */
11846:
11847: /*-------- arguments in the command line --------*/
11848:
1.186 brouard 11849: /* Main Log file */
1.126 brouard 11850: strcat(filelog, optionfilefiname);
11851: strcat(filelog,".log"); /* */
11852: if((ficlog=fopen(filelog,"w"))==NULL) {
11853: printf("Problem with logfile %s\n",filelog);
11854: goto end;
11855: }
11856: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 11857: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 11858: fprintf(ficlog,"\nEnter the parameter file name: \n");
11859: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
11860: path=%s \n\
11861: optionfile=%s\n\
11862: optionfilext=%s\n\
1.156 brouard 11863: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 11864:
1.197 brouard 11865: syscompilerinfo(1);
1.167 brouard 11866:
1.126 brouard 11867: printf("Local time (at start):%s",strstart);
11868: fprintf(ficlog,"Local time (at start): %s",strstart);
11869: fflush(ficlog);
11870: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 11871: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 11872:
11873: /* */
11874: strcpy(fileres,"r");
11875: strcat(fileres, optionfilefiname);
1.201 brouard 11876: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 11877: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 11878: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 11879:
1.186 brouard 11880: /* Main ---------arguments file --------*/
1.126 brouard 11881:
11882: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 11883: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
11884: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 11885: fflush(ficlog);
1.149 brouard 11886: /* goto end; */
11887: exit(70);
1.126 brouard 11888: }
11889:
11890: strcpy(filereso,"o");
1.201 brouard 11891: strcat(filereso,fileresu);
1.126 brouard 11892: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
11893: printf("Problem with Output resultfile: %s\n", filereso);
11894: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
11895: fflush(ficlog);
11896: goto end;
11897: }
1.278 brouard 11898: /*-------- Rewriting parameter file ----------*/
11899: strcpy(rfileres,"r"); /* "Rparameterfile */
11900: strcat(rfileres,optionfilefiname); /* Parameter file first name */
11901: strcat(rfileres,"."); /* */
11902: strcat(rfileres,optionfilext); /* Other files have txt extension */
11903: if((ficres =fopen(rfileres,"w"))==NULL) {
11904: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
11905: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
11906: fflush(ficlog);
11907: goto end;
11908: }
11909: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 11910:
1.278 brouard 11911:
1.126 brouard 11912: /* Reads comments: lines beginning with '#' */
11913: numlinepar=0;
1.277 brouard 11914: /* Is it a BOM UTF-8 Windows file? */
11915: /* First parameter line */
1.197 brouard 11916: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 11917: noffset=0;
11918: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
11919: {
11920: noffset=noffset+3;
11921: printf("# File is an UTF8 Bom.\n"); // 0xBF
11922: }
1.302 brouard 11923: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
11924: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 11925: {
11926: noffset=noffset+2;
11927: printf("# File is an UTF16BE BOM file\n");
11928: }
11929: else if( line[0] == 0 && line[1] == 0)
11930: {
11931: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
11932: noffset=noffset+4;
11933: printf("# File is an UTF16BE BOM file\n");
11934: }
11935: } else{
11936: ;/*printf(" Not a BOM file\n");*/
11937: }
11938:
1.197 brouard 11939: /* If line starts with a # it is a comment */
1.277 brouard 11940: if (line[noffset] == '#') {
1.197 brouard 11941: numlinepar++;
11942: fputs(line,stdout);
11943: fputs(line,ficparo);
1.278 brouard 11944: fputs(line,ficres);
1.197 brouard 11945: fputs(line,ficlog);
11946: continue;
11947: }else
11948: break;
11949: }
11950: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11951: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11952: if (num_filled != 5) {
11953: printf("Should be 5 parameters\n");
1.283 brouard 11954: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11955: }
1.126 brouard 11956: numlinepar++;
1.197 brouard 11957: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11958: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11959: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11960: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11961: }
11962: /* Second parameter line */
11963: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11964: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11965: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11966: if (line[0] == '#') {
11967: numlinepar++;
1.283 brouard 11968: printf("%s",line);
11969: fprintf(ficres,"%s",line);
11970: fprintf(ficparo,"%s",line);
11971: fprintf(ficlog,"%s",line);
1.197 brouard 11972: continue;
11973: }else
11974: break;
11975: }
1.223 brouard 11976: 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", \
11977: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11978: if (num_filled != 11) {
11979: 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 11980: printf("but line=%s\n",line);
1.283 brouard 11981: 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");
11982: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11983: }
1.286 brouard 11984: if( lastpass > maxwav){
11985: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11986: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11987: fflush(ficlog);
11988: goto end;
11989: }
11990: 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 11991: 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 11992: 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 11993: 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 11994: }
1.203 brouard 11995: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11996: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11997: /* Third parameter line */
11998: while(fgets(line, MAXLINE, ficpar)) {
11999: /* If line starts with a # it is a comment */
12000: if (line[0] == '#') {
12001: numlinepar++;
1.283 brouard 12002: printf("%s",line);
12003: fprintf(ficres,"%s",line);
12004: fprintf(ficparo,"%s",line);
12005: fprintf(ficlog,"%s",line);
1.197 brouard 12006: continue;
12007: }else
12008: break;
12009: }
1.201 brouard 12010: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 12011: if (num_filled != 1){
1.302 brouard 12012: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
12013: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 12014: model[0]='\0';
12015: goto end;
12016: }
12017: else{
12018: if (model[0]=='+'){
12019: for(i=1; i<=strlen(model);i++)
12020: modeltemp[i-1]=model[i];
1.201 brouard 12021: strcpy(model,modeltemp);
1.197 brouard 12022: }
12023: }
1.199 brouard 12024: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 12025: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 12026: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
12027: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
12028: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 12029: }
12030: /* 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); */
12031: /* numlinepar=numlinepar+3; /\* In general *\/ */
12032: /* 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 12033: /* 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); */
12034: /* 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 12035: fflush(ficlog);
1.190 brouard 12036: /* if(model[0]=='#'|| model[0]== '\0'){ */
12037: if(model[0]=='#'){
1.279 brouard 12038: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
12039: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
12040: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 12041: if(mle != -1){
1.279 brouard 12042: 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 12043: exit(1);
12044: }
12045: }
1.126 brouard 12046: while((c=getc(ficpar))=='#' && c!= EOF){
12047: ungetc(c,ficpar);
12048: fgets(line, MAXLINE, ficpar);
12049: numlinepar++;
1.195 brouard 12050: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
12051: z[0]=line[1];
12052: }
12053: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 12054: fputs(line, stdout);
12055: //puts(line);
1.126 brouard 12056: fputs(line,ficparo);
12057: fputs(line,ficlog);
12058: }
12059: ungetc(c,ficpar);
12060:
12061:
1.290 brouard 12062: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
12063: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
12064: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
12065: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 12066: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
12067: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
12068: v1+v2*age+v2*v3 makes cptcovn = 3
12069: */
12070: if (strlen(model)>1)
1.187 brouard 12071: 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 12072: else
1.187 brouard 12073: ncovmodel=2; /* Constant and age */
1.133 brouard 12074: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
12075: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 12076: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
12077: 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);
12078: 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);
12079: fflush(stdout);
12080: fclose (ficlog);
12081: goto end;
12082: }
1.126 brouard 12083: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
12084: delti=delti3[1][1];
12085: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
12086: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 12087: /* We could also provide initial parameters values giving by simple logistic regression
12088: * only one way, that is without matrix product. We will have nlstate maximizations */
12089: /* for(i=1;i<nlstate;i++){ */
12090: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12091: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12092: /* } */
1.126 brouard 12093: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 12094: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
12095: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 12096: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12097: fclose (ficparo);
12098: fclose (ficlog);
12099: goto end;
12100: exit(0);
1.220 brouard 12101: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 12102: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 12103: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
12104: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 12105: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
12106: matcov=matrix(1,npar,1,npar);
1.203 brouard 12107: hess=matrix(1,npar,1,npar);
1.220 brouard 12108: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 12109: /* Read guessed parameters */
1.126 brouard 12110: /* Reads comments: lines beginning with '#' */
12111: while((c=getc(ficpar))=='#' && c!= EOF){
12112: ungetc(c,ficpar);
12113: fgets(line, MAXLINE, ficpar);
12114: numlinepar++;
1.141 brouard 12115: fputs(line,stdout);
1.126 brouard 12116: fputs(line,ficparo);
12117: fputs(line,ficlog);
12118: }
12119: ungetc(c,ficpar);
12120:
12121: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 12122: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 12123: for(i=1; i <=nlstate; i++){
1.234 brouard 12124: j=0;
1.126 brouard 12125: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 12126: if(jj==i) continue;
12127: j++;
1.292 brouard 12128: while((c=getc(ficpar))=='#' && c!= EOF){
12129: ungetc(c,ficpar);
12130: fgets(line, MAXLINE, ficpar);
12131: numlinepar++;
12132: fputs(line,stdout);
12133: fputs(line,ficparo);
12134: fputs(line,ficlog);
12135: }
12136: ungetc(c,ficpar);
1.234 brouard 12137: fscanf(ficpar,"%1d%1d",&i1,&j1);
12138: if ((i1 != i) || (j1 != jj)){
12139: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 12140: It might be a problem of design; if ncovcol and the model are correct\n \
12141: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 12142: exit(1);
12143: }
12144: fprintf(ficparo,"%1d%1d",i1,j1);
12145: if(mle==1)
12146: printf("%1d%1d",i,jj);
12147: fprintf(ficlog,"%1d%1d",i,jj);
12148: for(k=1; k<=ncovmodel;k++){
12149: fscanf(ficpar," %lf",¶m[i][j][k]);
12150: if(mle==1){
12151: printf(" %lf",param[i][j][k]);
12152: fprintf(ficlog," %lf",param[i][j][k]);
12153: }
12154: else
12155: fprintf(ficlog," %lf",param[i][j][k]);
12156: fprintf(ficparo," %lf",param[i][j][k]);
12157: }
12158: fscanf(ficpar,"\n");
12159: numlinepar++;
12160: if(mle==1)
12161: printf("\n");
12162: fprintf(ficlog,"\n");
12163: fprintf(ficparo,"\n");
1.126 brouard 12164: }
12165: }
12166: fflush(ficlog);
1.234 brouard 12167:
1.251 brouard 12168: /* Reads parameters values */
1.126 brouard 12169: p=param[1][1];
1.251 brouard 12170: pstart=paramstart[1][1];
1.126 brouard 12171:
12172: /* Reads comments: lines beginning with '#' */
12173: while((c=getc(ficpar))=='#' && c!= EOF){
12174: ungetc(c,ficpar);
12175: fgets(line, MAXLINE, ficpar);
12176: numlinepar++;
1.141 brouard 12177: fputs(line,stdout);
1.126 brouard 12178: fputs(line,ficparo);
12179: fputs(line,ficlog);
12180: }
12181: ungetc(c,ficpar);
12182:
12183: for(i=1; i <=nlstate; i++){
12184: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 12185: fscanf(ficpar,"%1d%1d",&i1,&j1);
12186: if ( (i1-i) * (j1-j) != 0){
12187: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
12188: exit(1);
12189: }
12190: printf("%1d%1d",i,j);
12191: fprintf(ficparo,"%1d%1d",i1,j1);
12192: fprintf(ficlog,"%1d%1d",i1,j1);
12193: for(k=1; k<=ncovmodel;k++){
12194: fscanf(ficpar,"%le",&delti3[i][j][k]);
12195: printf(" %le",delti3[i][j][k]);
12196: fprintf(ficparo," %le",delti3[i][j][k]);
12197: fprintf(ficlog," %le",delti3[i][j][k]);
12198: }
12199: fscanf(ficpar,"\n");
12200: numlinepar++;
12201: printf("\n");
12202: fprintf(ficparo,"\n");
12203: fprintf(ficlog,"\n");
1.126 brouard 12204: }
12205: }
12206: fflush(ficlog);
1.234 brouard 12207:
1.145 brouard 12208: /* Reads covariance matrix */
1.126 brouard 12209: delti=delti3[1][1];
1.220 brouard 12210:
12211:
1.126 brouard 12212: /* 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 12213:
1.126 brouard 12214: /* Reads comments: lines beginning with '#' */
12215: while((c=getc(ficpar))=='#' && c!= EOF){
12216: ungetc(c,ficpar);
12217: fgets(line, MAXLINE, ficpar);
12218: numlinepar++;
1.141 brouard 12219: fputs(line,stdout);
1.126 brouard 12220: fputs(line,ficparo);
12221: fputs(line,ficlog);
12222: }
12223: ungetc(c,ficpar);
1.220 brouard 12224:
1.126 brouard 12225: matcov=matrix(1,npar,1,npar);
1.203 brouard 12226: hess=matrix(1,npar,1,npar);
1.131 brouard 12227: for(i=1; i <=npar; i++)
12228: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 12229:
1.194 brouard 12230: /* Scans npar lines */
1.126 brouard 12231: for(i=1; i <=npar; i++){
1.226 brouard 12232: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 12233: if(count != 3){
1.226 brouard 12234: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12235: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12236: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12237: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12238: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12239: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12240: exit(1);
1.220 brouard 12241: }else{
1.226 brouard 12242: if(mle==1)
12243: printf("%1d%1d%d",i1,j1,jk);
12244: }
12245: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
12246: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 12247: for(j=1; j <=i; j++){
1.226 brouard 12248: fscanf(ficpar," %le",&matcov[i][j]);
12249: if(mle==1){
12250: printf(" %.5le",matcov[i][j]);
12251: }
12252: fprintf(ficlog," %.5le",matcov[i][j]);
12253: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 12254: }
12255: fscanf(ficpar,"\n");
12256: numlinepar++;
12257: if(mle==1)
1.220 brouard 12258: printf("\n");
1.126 brouard 12259: fprintf(ficlog,"\n");
12260: fprintf(ficparo,"\n");
12261: }
1.194 brouard 12262: /* End of read covariance matrix npar lines */
1.126 brouard 12263: for(i=1; i <=npar; i++)
12264: for(j=i+1;j<=npar;j++)
1.226 brouard 12265: matcov[i][j]=matcov[j][i];
1.126 brouard 12266:
12267: if(mle==1)
12268: printf("\n");
12269: fprintf(ficlog,"\n");
12270:
12271: fflush(ficlog);
12272:
12273: } /* End of mle != -3 */
1.218 brouard 12274:
1.186 brouard 12275: /* Main data
12276: */
1.290 brouard 12277: nobs=lastobs-firstobs+1; /* was = lastobs;*/
12278: /* num=lvector(1,n); */
12279: /* moisnais=vector(1,n); */
12280: /* annais=vector(1,n); */
12281: /* moisdc=vector(1,n); */
12282: /* andc=vector(1,n); */
12283: /* weight=vector(1,n); */
12284: /* agedc=vector(1,n); */
12285: /* cod=ivector(1,n); */
12286: /* for(i=1;i<=n;i++){ */
12287: num=lvector(firstobs,lastobs);
12288: moisnais=vector(firstobs,lastobs);
12289: annais=vector(firstobs,lastobs);
12290: moisdc=vector(firstobs,lastobs);
12291: andc=vector(firstobs,lastobs);
12292: weight=vector(firstobs,lastobs);
12293: agedc=vector(firstobs,lastobs);
12294: cod=ivector(firstobs,lastobs);
12295: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 12296: num[i]=0;
12297: moisnais[i]=0;
12298: annais[i]=0;
12299: moisdc[i]=0;
12300: andc[i]=0;
12301: agedc[i]=0;
12302: cod[i]=0;
12303: weight[i]=1.0; /* Equal weights, 1 by default */
12304: }
1.290 brouard 12305: mint=matrix(1,maxwav,firstobs,lastobs);
12306: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 12307: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
12308: printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel));
1.126 brouard 12309: tab=ivector(1,NCOVMAX);
1.144 brouard 12310: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 12311: 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 12312:
1.136 brouard 12313: /* Reads data from file datafile */
12314: if (readdata(datafile, firstobs, lastobs, &imx)==1)
12315: goto end;
12316:
12317: /* Calculation of the number of parameters from char model */
1.234 brouard 12318: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 12319: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
12320: k=3 V4 Tvar[k=3]= 4 (from V4)
12321: k=2 V1 Tvar[k=2]= 1 (from V1)
12322: k=1 Tvar[1]=2 (from V2)
1.234 brouard 12323: */
12324:
12325: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
12326: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 12327: TnsdVar=ivector(1,NCOVMAX); /* */
1.234 brouard 12328: TvarsD=ivector(1,NCOVMAX); /* */
12329: TvarsQind=ivector(1,NCOVMAX); /* */
12330: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 12331: TvarF=ivector(1,NCOVMAX); /* */
12332: TvarFind=ivector(1,NCOVMAX); /* */
12333: TvarV=ivector(1,NCOVMAX); /* */
12334: TvarVind=ivector(1,NCOVMAX); /* */
12335: TvarA=ivector(1,NCOVMAX); /* */
12336: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 12337: TvarFD=ivector(1,NCOVMAX); /* */
12338: TvarFDind=ivector(1,NCOVMAX); /* */
12339: TvarFQ=ivector(1,NCOVMAX); /* */
12340: TvarFQind=ivector(1,NCOVMAX); /* */
12341: TvarVD=ivector(1,NCOVMAX); /* */
12342: TvarVDind=ivector(1,NCOVMAX); /* */
12343: TvarVQ=ivector(1,NCOVMAX); /* */
12344: TvarVQind=ivector(1,NCOVMAX); /* */
12345:
1.230 brouard 12346: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 12347: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 12348: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
12349: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
12350: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 12351: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
12352: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
12353: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
12354: */
12355: /* For model-covariate k tells which data-covariate to use but
12356: because this model-covariate is a construction we invent a new column
12357: ncovcol + k1
12358: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
12359: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 12360: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
12361: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 12362: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
12363: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 12364: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 12365: */
1.145 brouard 12366: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
12367: 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 12368: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
12369: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.330 brouard 12370: Tvardk=imatrix(1,NCOVMAX,1,2);
1.145 brouard 12371: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 12372: 4 covariates (3 plus signs)
12373: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 12374: */
12375: for(i=1;i<NCOVMAX;i++)
12376: Tage[i]=0;
1.230 brouard 12377: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 12378: * individual dummy, fixed or varying:
12379: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
12380: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 12381: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
12382: * V1 df, V2 qf, V3 & V4 dv, V5 qv
12383: * Tmodelind[1]@9={9,0,3,2,}*/
12384: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
12385: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 12386: * individual quantitative, fixed or varying:
12387: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
12388: * 3, 1, 0, 0, 0, 0, 0, 0},
12389: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 12390: /* Main decodemodel */
12391:
1.187 brouard 12392:
1.223 brouard 12393: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 12394: goto end;
12395:
1.137 brouard 12396: if((double)(lastobs-imx)/(double)imx > 1.10){
12397: nbwarn++;
12398: 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);
12399: 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);
12400: }
1.136 brouard 12401: /* if(mle==1){*/
1.137 brouard 12402: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
12403: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 12404: }
12405:
12406: /*-calculation of age at interview from date of interview and age at death -*/
12407: agev=matrix(1,maxwav,1,imx);
12408:
12409: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
12410: goto end;
12411:
1.126 brouard 12412:
1.136 brouard 12413: agegomp=(int)agemin;
1.290 brouard 12414: free_vector(moisnais,firstobs,lastobs);
12415: free_vector(annais,firstobs,lastobs);
1.126 brouard 12416: /* free_matrix(mint,1,maxwav,1,n);
12417: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 12418: /* free_vector(moisdc,1,n); */
12419: /* free_vector(andc,1,n); */
1.145 brouard 12420: /* */
12421:
1.126 brouard 12422: wav=ivector(1,imx);
1.214 brouard 12423: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
12424: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
12425: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
12426: 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.*/
12427: bh=imatrix(1,lastpass-firstpass+2,1,imx);
12428: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 12429:
12430: /* Concatenates waves */
1.214 brouard 12431: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
12432: Death is a valid wave (if date is known).
12433: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
12434: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
12435: and mw[mi+1][i]. dh depends on stepm.
12436: */
12437:
1.126 brouard 12438: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 12439: /* Concatenates waves */
1.145 brouard 12440:
1.290 brouard 12441: free_vector(moisdc,firstobs,lastobs);
12442: free_vector(andc,firstobs,lastobs);
1.215 brouard 12443:
1.126 brouard 12444: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
12445: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
12446: ncodemax[1]=1;
1.145 brouard 12447: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 12448: cptcoveff=0;
1.220 brouard 12449: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
12450: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 12451: }
12452:
12453: ncovcombmax=pow(2,cptcoveff);
12454: invalidvarcomb=ivector(1, ncovcombmax);
12455: for(i=1;i<ncovcombmax;i++)
12456: invalidvarcomb[i]=0;
12457:
1.211 brouard 12458: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 12459: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 12460: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 12461:
1.200 brouard 12462: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 12463: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 12464: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 12465: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
12466: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
12467: * (currently 0 or 1) in the data.
12468: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
12469: * corresponding modality (h,j).
12470: */
12471:
1.145 brouard 12472: h=0;
12473: /*if (cptcovn > 0) */
1.126 brouard 12474: m=pow(2,cptcoveff);
12475:
1.144 brouard 12476: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 12477: * For k=4 covariates, h goes from 1 to m=2**k
12478: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
12479: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 12480: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
12481: *______________________________ *______________________
12482: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
12483: * 2 2 1 1 1 * 1 0 0 0 1
12484: * 3 i=2 1 2 1 1 * 2 0 0 1 0
12485: * 4 2 2 1 1 * 3 0 0 1 1
12486: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
12487: * 6 2 1 2 1 * 5 0 1 0 1
12488: * 7 i=4 1 2 2 1 * 6 0 1 1 0
12489: * 8 2 2 2 1 * 7 0 1 1 1
12490: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
12491: * 10 2 1 1 2 * 9 1 0 0 1
12492: * 11 i=6 1 2 1 2 * 10 1 0 1 0
12493: * 12 2 2 1 2 * 11 1 0 1 1
12494: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
12495: * 14 2 1 2 2 * 13 1 1 0 1
12496: * 15 i=8 1 2 2 2 * 14 1 1 1 0
12497: * 16 2 2 2 2 * 15 1 1 1 1
12498: */
1.212 brouard 12499: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 12500: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
12501: * and the value of each covariate?
12502: * V1=1, V2=1, V3=2, V4=1 ?
12503: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
12504: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
12505: * In order to get the real value in the data, we use nbcode
12506: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
12507: * We are keeping this crazy system in order to be able (in the future?)
12508: * to have more than 2 values (0 or 1) for a covariate.
12509: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
12510: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
12511: * bbbbbbbb
12512: * 76543210
12513: * h-1 00000101 (6-1=5)
1.219 brouard 12514: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 12515: * &
12516: * 1 00000001 (1)
1.219 brouard 12517: * 00000000 = 1 & ((h-1) >> (k-1))
12518: * +1= 00000001 =1
1.211 brouard 12519: *
12520: * h=14, k=3 => h'=h-1=13, k'=k-1=2
12521: * h' 1101 =2^3+2^2+0x2^1+2^0
12522: * >>k' 11
12523: * & 00000001
12524: * = 00000001
12525: * +1 = 00000010=2 = codtabm(14,3)
12526: * Reverse h=6 and m=16?
12527: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
12528: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
12529: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
12530: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
12531: * V3=decodtabm(14,3,2**4)=2
12532: * h'=13 1101 =2^3+2^2+0x2^1+2^0
12533: *(h-1) >> (j-1) 0011 =13 >> 2
12534: * &1 000000001
12535: * = 000000001
12536: * +1= 000000010 =2
12537: * 2211
12538: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
12539: * V3=2
1.220 brouard 12540: * codtabm and decodtabm are identical
1.211 brouard 12541: */
12542:
1.145 brouard 12543:
12544: free_ivector(Ndum,-1,NCOVMAX);
12545:
12546:
1.126 brouard 12547:
1.186 brouard 12548: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 12549: strcpy(optionfilegnuplot,optionfilefiname);
12550: if(mle==-3)
1.201 brouard 12551: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 12552: strcat(optionfilegnuplot,".gp");
12553:
12554: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
12555: printf("Problem with file %s",optionfilegnuplot);
12556: }
12557: else{
1.204 brouard 12558: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 12559: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 12560: //fprintf(ficgp,"set missing 'NaNq'\n");
12561: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 12562: }
12563: /* fclose(ficgp);*/
1.186 brouard 12564:
12565:
12566: /* Initialisation of --------- index.htm --------*/
1.126 brouard 12567:
12568: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
12569: if(mle==-3)
1.201 brouard 12570: strcat(optionfilehtm,"-MORT_");
1.126 brouard 12571: strcat(optionfilehtm,".htm");
12572: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 12573: printf("Problem with %s \n",optionfilehtm);
12574: exit(0);
1.126 brouard 12575: }
12576:
12577: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
12578: strcat(optionfilehtmcov,"-cov.htm");
12579: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
12580: printf("Problem with %s \n",optionfilehtmcov), exit(0);
12581: }
12582: else{
12583: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
12584: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12585: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 12586: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
12587: }
12588:
1.332 ! brouard 12589: fprintf(fichtm,"<html><head>\n<head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<title>IMaCh %s</title></head>\n <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n<font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>-EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \
1.204 brouard 12590: <hr size=\"2\" color=\"#EC5E5E\"> \n\
12591: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 12592: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12593: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 12594: \n\
12595: <hr size=\"2\" color=\"#EC5E5E\">\
12596: <ul><li><h4>Parameter files</h4>\n\
12597: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
12598: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
12599: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
12600: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
12601: - Date and time at start: %s</ul>\n",\
12602: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
12603: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
12604: fileres,fileres,\
12605: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
12606: fflush(fichtm);
12607:
12608: strcpy(pathr,path);
12609: strcat(pathr,optionfilefiname);
1.184 brouard 12610: #ifdef WIN32
12611: _chdir(optionfilefiname); /* Move to directory named optionfile */
12612: #else
1.126 brouard 12613: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 12614: #endif
12615:
1.126 brouard 12616:
1.220 brouard 12617: /* Calculates basic frequencies. Computes observed prevalence at single age
12618: and for any valid combination of covariates
1.126 brouard 12619: and prints on file fileres'p'. */
1.251 brouard 12620: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 12621: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 12622:
12623: fprintf(fichtm,"\n");
1.286 brouard 12624: 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 12625: ftol, stepm);
12626: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
12627: ncurrv=1;
12628: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
12629: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
12630: ncurrv=i;
12631: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12632: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 12633: ncurrv=i;
12634: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12635: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 12636: ncurrv=i;
12637: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
12638: 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", \
12639: nlstate, ndeath, maxwav, mle, weightopt);
12640:
12641: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
12642: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
12643:
12644:
1.317 brouard 12645: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 12646: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
12647: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 12648: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 12649: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 12650: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12651: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12652: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12653: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 12654:
1.126 brouard 12655: /* For Powell, parameters are in a vector p[] starting at p[1]
12656: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
12657: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
12658:
12659: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 12660: /* For mortality only */
1.126 brouard 12661: if (mle==-3){
1.136 brouard 12662: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 12663: for(i=1;i<=NDIM;i++)
12664: for(j=1;j<=NDIM;j++)
12665: ximort[i][j]=0.;
1.186 brouard 12666: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 12667: cens=ivector(firstobs,lastobs);
12668: ageexmed=vector(firstobs,lastobs);
12669: agecens=vector(firstobs,lastobs);
12670: dcwave=ivector(firstobs,lastobs);
1.223 brouard 12671:
1.126 brouard 12672: for (i=1; i<=imx; i++){
12673: dcwave[i]=-1;
12674: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 12675: if (s[m][i]>nlstate) {
12676: dcwave[i]=m;
12677: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
12678: break;
12679: }
1.126 brouard 12680: }
1.226 brouard 12681:
1.126 brouard 12682: for (i=1; i<=imx; i++) {
12683: if (wav[i]>0){
1.226 brouard 12684: ageexmed[i]=agev[mw[1][i]][i];
12685: j=wav[i];
12686: agecens[i]=1.;
12687:
12688: if (ageexmed[i]> 1 && wav[i] > 0){
12689: agecens[i]=agev[mw[j][i]][i];
12690: cens[i]= 1;
12691: }else if (ageexmed[i]< 1)
12692: cens[i]= -1;
12693: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
12694: cens[i]=0 ;
1.126 brouard 12695: }
12696: else cens[i]=-1;
12697: }
12698:
12699: for (i=1;i<=NDIM;i++) {
12700: for (j=1;j<=NDIM;j++)
1.226 brouard 12701: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 12702: }
12703:
1.302 brouard 12704: p[1]=0.0268; p[NDIM]=0.083;
12705: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 12706:
12707:
1.136 brouard 12708: #ifdef GSL
12709: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 12710: #else
1.126 brouard 12711: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 12712: #endif
1.201 brouard 12713: strcpy(filerespow,"POW-MORT_");
12714: strcat(filerespow,fileresu);
1.126 brouard 12715: if((ficrespow=fopen(filerespow,"w"))==NULL) {
12716: printf("Problem with resultfile: %s\n", filerespow);
12717: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
12718: }
1.136 brouard 12719: #ifdef GSL
12720: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 12721: #else
1.126 brouard 12722: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 12723: #endif
1.126 brouard 12724: /* for (i=1;i<=nlstate;i++)
12725: for(j=1;j<=nlstate+ndeath;j++)
12726: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
12727: */
12728: fprintf(ficrespow,"\n");
1.136 brouard 12729: #ifdef GSL
12730: /* gsl starts here */
12731: T = gsl_multimin_fminimizer_nmsimplex;
12732: gsl_multimin_fminimizer *sfm = NULL;
12733: gsl_vector *ss, *x;
12734: gsl_multimin_function minex_func;
12735:
12736: /* Initial vertex size vector */
12737: ss = gsl_vector_alloc (NDIM);
12738:
12739: if (ss == NULL){
12740: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
12741: }
12742: /* Set all step sizes to 1 */
12743: gsl_vector_set_all (ss, 0.001);
12744:
12745: /* Starting point */
1.126 brouard 12746:
1.136 brouard 12747: x = gsl_vector_alloc (NDIM);
12748:
12749: if (x == NULL){
12750: gsl_vector_free(ss);
12751: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
12752: }
12753:
12754: /* Initialize method and iterate */
12755: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 12756: /* gsl_vector_set(x, 0, 0.0268); */
12757: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 12758: gsl_vector_set(x, 0, p[1]);
12759: gsl_vector_set(x, 1, p[2]);
12760:
12761: minex_func.f = &gompertz_f;
12762: minex_func.n = NDIM;
12763: minex_func.params = (void *)&p; /* ??? */
12764:
12765: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
12766: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
12767:
12768: printf("Iterations beginning .....\n\n");
12769: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
12770:
12771: iteri=0;
12772: while (rval == GSL_CONTINUE){
12773: iteri++;
12774: status = gsl_multimin_fminimizer_iterate(sfm);
12775:
12776: if (status) printf("error: %s\n", gsl_strerror (status));
12777: fflush(0);
12778:
12779: if (status)
12780: break;
12781:
12782: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
12783: ssval = gsl_multimin_fminimizer_size (sfm);
12784:
12785: if (rval == GSL_SUCCESS)
12786: printf ("converged to a local maximum at\n");
12787:
12788: printf("%5d ", iteri);
12789: for (it = 0; it < NDIM; it++){
12790: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
12791: }
12792: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
12793: }
12794:
12795: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
12796:
12797: gsl_vector_free(x); /* initial values */
12798: gsl_vector_free(ss); /* inital step size */
12799: for (it=0; it<NDIM; it++){
12800: p[it+1]=gsl_vector_get(sfm->x,it);
12801: fprintf(ficrespow," %.12lf", p[it]);
12802: }
12803: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
12804: #endif
12805: #ifdef POWELL
12806: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
12807: #endif
1.126 brouard 12808: fclose(ficrespow);
12809:
1.203 brouard 12810: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 12811:
12812: for(i=1; i <=NDIM; i++)
12813: for(j=i+1;j<=NDIM;j++)
1.220 brouard 12814: matcov[i][j]=matcov[j][i];
1.126 brouard 12815:
12816: printf("\nCovariance matrix\n ");
1.203 brouard 12817: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 12818: for(i=1; i <=NDIM; i++) {
12819: for(j=1;j<=NDIM;j++){
1.220 brouard 12820: printf("%f ",matcov[i][j]);
12821: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 12822: }
1.203 brouard 12823: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 12824: }
12825:
12826: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 12827: for (i=1;i<=NDIM;i++) {
1.126 brouard 12828: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 12829: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
12830: }
1.302 brouard 12831: lsurv=vector(agegomp,AGESUP);
12832: lpop=vector(agegomp,AGESUP);
12833: tpop=vector(agegomp,AGESUP);
1.126 brouard 12834: lsurv[agegomp]=100000;
12835:
12836: for (k=agegomp;k<=AGESUP;k++) {
12837: agemortsup=k;
12838: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
12839: }
12840:
12841: for (k=agegomp;k<agemortsup;k++)
12842: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
12843:
12844: for (k=agegomp;k<agemortsup;k++){
12845: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
12846: sumlpop=sumlpop+lpop[k];
12847: }
12848:
12849: tpop[agegomp]=sumlpop;
12850: for (k=agegomp;k<(agemortsup-3);k++){
12851: /* tpop[k+1]=2;*/
12852: tpop[k+1]=tpop[k]-lpop[k];
12853: }
12854:
12855:
12856: printf("\nAge lx qx dx Lx Tx e(x)\n");
12857: for (k=agegomp;k<(agemortsup-2);k++)
12858: 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]);
12859:
12860:
12861: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 12862: ageminpar=50;
12863: agemaxpar=100;
1.194 brouard 12864: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
12865: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12866: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12867: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
12868: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12869: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12870: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12871: }else{
12872: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
12873: 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 12874: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 12875: }
1.201 brouard 12876: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 12877: stepm, weightopt,\
12878: model,imx,p,matcov,agemortsup);
12879:
1.302 brouard 12880: free_vector(lsurv,agegomp,AGESUP);
12881: free_vector(lpop,agegomp,AGESUP);
12882: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 12883: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 12884: free_ivector(dcwave,firstobs,lastobs);
12885: free_vector(agecens,firstobs,lastobs);
12886: free_vector(ageexmed,firstobs,lastobs);
12887: free_ivector(cens,firstobs,lastobs);
1.220 brouard 12888: #ifdef GSL
1.136 brouard 12889: #endif
1.186 brouard 12890: } /* Endof if mle==-3 mortality only */
1.205 brouard 12891: /* Standard */
12892: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
12893: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12894: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 12895: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 12896: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12897: for (k=1; k<=npar;k++)
12898: printf(" %d %8.5f",k,p[k]);
12899: printf("\n");
1.205 brouard 12900: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
12901: /* mlikeli uses func not funcone */
1.247 brouard 12902: /* for(i=1;i<nlstate;i++){ */
12903: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12904: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12905: /* } */
1.205 brouard 12906: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
12907: }
12908: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
12909: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12910: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
12911: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12912: }
12913: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 12914: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12915: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12916: for (k=1; k<=npar;k++)
12917: printf(" %d %8.5f",k,p[k]);
12918: printf("\n");
12919:
12920: /*--------- results files --------------*/
1.283 brouard 12921: /* 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 12922:
12923:
12924: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 12925: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 12926: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 12927:
12928: printf("#model= 1 + age ");
12929: fprintf(ficres,"#model= 1 + age ");
12930: fprintf(ficlog,"#model= 1 + age ");
12931: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
12932: </ul>", model);
12933:
12934: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
12935: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
12936: if(nagesqr==1){
12937: printf(" + age*age ");
12938: fprintf(ficres," + age*age ");
12939: fprintf(ficlog," + age*age ");
12940: fprintf(fichtm, "<th>+ age*age</th>");
12941: }
12942: for(j=1;j <=ncovmodel-2;j++){
12943: if(Typevar[j]==0) {
12944: printf(" + V%d ",Tvar[j]);
12945: fprintf(ficres," + V%d ",Tvar[j]);
12946: fprintf(ficlog," + V%d ",Tvar[j]);
12947: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
12948: }else if(Typevar[j]==1) {
12949: printf(" + V%d*age ",Tvar[j]);
12950: fprintf(ficres," + V%d*age ",Tvar[j]);
12951: fprintf(ficlog," + V%d*age ",Tvar[j]);
12952: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
12953: }else if(Typevar[j]==2) {
12954: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12955: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12956: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12957: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12958: }
12959: }
12960: printf("\n");
12961: fprintf(ficres,"\n");
12962: fprintf(ficlog,"\n");
12963: fprintf(fichtm, "</tr>");
12964: fprintf(fichtm, "\n");
12965:
12966:
1.126 brouard 12967: for(i=1,jk=1; i <=nlstate; i++){
12968: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 12969: if (k != i) {
1.319 brouard 12970: fprintf(fichtm, "<tr>");
1.225 brouard 12971: printf("%d%d ",i,k);
12972: fprintf(ficlog,"%d%d ",i,k);
12973: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 12974: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 12975: for(j=1; j <=ncovmodel; j++){
12976: printf("%12.7f ",p[jk]);
12977: fprintf(ficlog,"%12.7f ",p[jk]);
12978: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 12979: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 12980: jk++;
12981: }
12982: printf("\n");
12983: fprintf(ficlog,"\n");
12984: fprintf(ficres,"\n");
1.319 brouard 12985: fprintf(fichtm, "</tr>\n");
1.225 brouard 12986: }
1.126 brouard 12987: }
12988: }
1.319 brouard 12989: /* fprintf(fichtm,"</tr>\n"); */
12990: fprintf(fichtm,"</table>\n");
12991: fprintf(fichtm, "\n");
12992:
1.203 brouard 12993: if(mle != 0){
12994: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 12995: ftolhess=ftol; /* Usually correct */
1.203 brouard 12996: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
12997: 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");
12998: 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 12999: 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 13000: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
13001: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
13002: if(nagesqr==1){
13003: printf(" + age*age ");
13004: fprintf(ficres," + age*age ");
13005: fprintf(ficlog," + age*age ");
13006: fprintf(fichtm, "<th>+ age*age</th>");
13007: }
13008: for(j=1;j <=ncovmodel-2;j++){
13009: if(Typevar[j]==0) {
13010: printf(" + V%d ",Tvar[j]);
13011: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
13012: }else if(Typevar[j]==1) {
13013: printf(" + V%d*age ",Tvar[j]);
13014: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
13015: }else if(Typevar[j]==2) {
13016: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
13017: }
13018: }
13019: fprintf(fichtm, "</tr>\n");
13020:
1.203 brouard 13021: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 13022: for(k=1; k <=(nlstate+ndeath); k++){
13023: if (k != i) {
1.319 brouard 13024: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 13025: printf("%d%d ",i,k);
13026: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 13027: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 13028: for(j=1; j <=ncovmodel; j++){
1.319 brouard 13029: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 13030: 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]));
13031: 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 13032: if(fabs(wald) > 1.96){
1.321 brouard 13033: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 13034: }else{
13035: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
13036: }
1.324 brouard 13037: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 13038: 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 13039: jk++;
13040: }
13041: printf("\n");
13042: fprintf(ficlog,"\n");
1.319 brouard 13043: fprintf(fichtm, "</tr>\n");
1.225 brouard 13044: }
13045: }
1.193 brouard 13046: }
1.203 brouard 13047: } /* end of hesscov and Wald tests */
1.319 brouard 13048: fprintf(fichtm,"</table>\n");
1.225 brouard 13049:
1.203 brouard 13050: /* */
1.126 brouard 13051: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
13052: printf("# Scales (for hessian or gradient estimation)\n");
13053: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
13054: for(i=1,jk=1; i <=nlstate; i++){
13055: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 13056: if (j!=i) {
13057: fprintf(ficres,"%1d%1d",i,j);
13058: printf("%1d%1d",i,j);
13059: fprintf(ficlog,"%1d%1d",i,j);
13060: for(k=1; k<=ncovmodel;k++){
13061: printf(" %.5e",delti[jk]);
13062: fprintf(ficlog," %.5e",delti[jk]);
13063: fprintf(ficres," %.5e",delti[jk]);
13064: jk++;
13065: }
13066: printf("\n");
13067: fprintf(ficlog,"\n");
13068: fprintf(ficres,"\n");
13069: }
1.126 brouard 13070: }
13071: }
13072:
13073: fprintf(ficres,"# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n");
1.203 brouard 13074: if(mle >= 1) /* To big for the screen */
1.126 brouard 13075: 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");
13076: 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");
13077: /* # 121 Var(a12)\n\ */
13078: /* # 122 Cov(b12,a12) Var(b12)\n\ */
13079: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
13080: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
13081: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
13082: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
13083: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
13084: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
13085:
13086:
13087: /* Just to have a covariance matrix which will be more understandable
13088: even is we still don't want to manage dictionary of variables
13089: */
13090: for(itimes=1;itimes<=2;itimes++){
13091: jj=0;
13092: for(i=1; i <=nlstate; i++){
1.225 brouard 13093: for(j=1; j <=nlstate+ndeath; j++){
13094: if(j==i) continue;
13095: for(k=1; k<=ncovmodel;k++){
13096: jj++;
13097: ca[0]= k+'a'-1;ca[1]='\0';
13098: if(itimes==1){
13099: if(mle>=1)
13100: printf("#%1d%1d%d",i,j,k);
13101: fprintf(ficlog,"#%1d%1d%d",i,j,k);
13102: fprintf(ficres,"#%1d%1d%d",i,j,k);
13103: }else{
13104: if(mle>=1)
13105: printf("%1d%1d%d",i,j,k);
13106: fprintf(ficlog,"%1d%1d%d",i,j,k);
13107: fprintf(ficres,"%1d%1d%d",i,j,k);
13108: }
13109: ll=0;
13110: for(li=1;li <=nlstate; li++){
13111: for(lj=1;lj <=nlstate+ndeath; lj++){
13112: if(lj==li) continue;
13113: for(lk=1;lk<=ncovmodel;lk++){
13114: ll++;
13115: if(ll<=jj){
13116: cb[0]= lk +'a'-1;cb[1]='\0';
13117: if(ll<jj){
13118: if(itimes==1){
13119: if(mle>=1)
13120: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13121: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13122: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
13123: }else{
13124: if(mle>=1)
13125: printf(" %.5e",matcov[jj][ll]);
13126: fprintf(ficlog," %.5e",matcov[jj][ll]);
13127: fprintf(ficres," %.5e",matcov[jj][ll]);
13128: }
13129: }else{
13130: if(itimes==1){
13131: if(mle>=1)
13132: printf(" Var(%s%1d%1d)",ca,i,j);
13133: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
13134: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
13135: }else{
13136: if(mle>=1)
13137: printf(" %.7e",matcov[jj][ll]);
13138: fprintf(ficlog," %.7e",matcov[jj][ll]);
13139: fprintf(ficres," %.7e",matcov[jj][ll]);
13140: }
13141: }
13142: }
13143: } /* end lk */
13144: } /* end lj */
13145: } /* end li */
13146: if(mle>=1)
13147: printf("\n");
13148: fprintf(ficlog,"\n");
13149: fprintf(ficres,"\n");
13150: numlinepar++;
13151: } /* end k*/
13152: } /*end j */
1.126 brouard 13153: } /* end i */
13154: } /* end itimes */
13155:
13156: fflush(ficlog);
13157: fflush(ficres);
1.225 brouard 13158: while(fgets(line, MAXLINE, ficpar)) {
13159: /* If line starts with a # it is a comment */
13160: if (line[0] == '#') {
13161: numlinepar++;
13162: fputs(line,stdout);
13163: fputs(line,ficparo);
13164: fputs(line,ficlog);
1.299 brouard 13165: fputs(line,ficres);
1.225 brouard 13166: continue;
13167: }else
13168: break;
13169: }
13170:
1.209 brouard 13171: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
13172: /* ungetc(c,ficpar); */
13173: /* fgets(line, MAXLINE, ficpar); */
13174: /* fputs(line,stdout); */
13175: /* fputs(line,ficparo); */
13176: /* } */
13177: /* ungetc(c,ficpar); */
1.126 brouard 13178:
13179: estepm=0;
1.209 brouard 13180: 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 13181:
13182: if (num_filled != 6) {
13183: 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);
13184: 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);
13185: goto end;
13186: }
13187: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
13188: }
13189: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
13190: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
13191:
1.209 brouard 13192: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 13193: if (estepm==0 || estepm < stepm) estepm=stepm;
13194: if (fage <= 2) {
13195: bage = ageminpar;
13196: fage = agemaxpar;
13197: }
13198:
13199: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 13200: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
13201: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 13202:
1.186 brouard 13203: /* Other stuffs, more or less useful */
1.254 brouard 13204: while(fgets(line, MAXLINE, ficpar)) {
13205: /* If line starts with a # it is a comment */
13206: if (line[0] == '#') {
13207: numlinepar++;
13208: fputs(line,stdout);
13209: fputs(line,ficparo);
13210: fputs(line,ficlog);
1.299 brouard 13211: fputs(line,ficres);
1.254 brouard 13212: continue;
13213: }else
13214: break;
13215: }
13216:
13217: 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){
13218:
13219: if (num_filled != 7) {
13220: 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);
13221: 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);
13222: goto end;
13223: }
13224: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
13225: 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);
13226: 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);
13227: 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 13228: }
1.254 brouard 13229:
13230: while(fgets(line, MAXLINE, ficpar)) {
13231: /* If line starts with a # it is a comment */
13232: if (line[0] == '#') {
13233: numlinepar++;
13234: fputs(line,stdout);
13235: fputs(line,ficparo);
13236: fputs(line,ficlog);
1.299 brouard 13237: fputs(line,ficres);
1.254 brouard 13238: continue;
13239: }else
13240: break;
1.126 brouard 13241: }
13242:
13243:
13244: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
13245: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
13246:
1.254 brouard 13247: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
13248: if (num_filled != 1) {
13249: 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);
13250: 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);
13251: goto end;
13252: }
13253: printf("pop_based=%d\n",popbased);
13254: fprintf(ficlog,"pop_based=%d\n",popbased);
13255: fprintf(ficparo,"pop_based=%d\n",popbased);
13256: fprintf(ficres,"pop_based=%d\n",popbased);
13257: }
13258:
1.258 brouard 13259: /* Results */
1.332 ! brouard 13260: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
! 13261: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
! 13262: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 13263: endishere=0;
1.258 brouard 13264: nresult=0;
1.308 brouard 13265: parameterline=0;
1.258 brouard 13266: do{
13267: if(!fgets(line, MAXLINE, ficpar)){
13268: endishere=1;
1.308 brouard 13269: parameterline=15;
1.258 brouard 13270: }else if (line[0] == '#') {
13271: /* If line starts with a # it is a comment */
1.254 brouard 13272: numlinepar++;
13273: fputs(line,stdout);
13274: fputs(line,ficparo);
13275: fputs(line,ficlog);
1.299 brouard 13276: fputs(line,ficres);
1.254 brouard 13277: continue;
1.258 brouard 13278: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
13279: parameterline=11;
1.296 brouard 13280: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 13281: parameterline=12;
1.307 brouard 13282: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 13283: parameterline=13;
1.307 brouard 13284: }
1.258 brouard 13285: else{
13286: parameterline=14;
1.254 brouard 13287: }
1.308 brouard 13288: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 13289: case 11:
1.296 brouard 13290: 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)){
13291: 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 13292: 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);
13293: 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);
13294: 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);
13295: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 13296: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
13297: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 13298: prvforecast = 1;
13299: }
13300: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 13301: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13302: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13303: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 13304: prvforecast = 2;
13305: }
13306: else {
13307: 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);
13308: 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);
13309: goto end;
1.258 brouard 13310: }
1.254 brouard 13311: break;
1.258 brouard 13312: case 12:
1.296 brouard 13313: 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)){
13314: 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);
13315: 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);
13316: 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);
13317: 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);
13318: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 13319: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
13320: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 13321: prvbackcast = 1;
13322: }
13323: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 13324: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
13325: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
13326: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 13327: prvbackcast = 2;
13328: }
13329: else {
13330: 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);
13331: 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);
13332: goto end;
1.258 brouard 13333: }
1.230 brouard 13334: break;
1.258 brouard 13335: case 13:
1.332 ! brouard 13336: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 13337: nresult++; /* Sum of resultlines */
1.332 ! brouard 13338: printf("Result %d: result:%s\n",nresult, resultlineori);
! 13339: /* removefirstspace(&resultlineori); */
! 13340:
! 13341: if(strstr(resultlineori,"v") !=0){
! 13342: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
! 13343: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
! 13344: return 1;
! 13345: }
! 13346: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
! 13347: printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori);
1.318 brouard 13348: if(nresult > MAXRESULTLINESPONE-1){
13349: 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);
13350: 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 13351: goto end;
13352: }
1.332 ! brouard 13353:
1.310 brouard 13354: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 13355: fprintf(ficparo,"result: %s\n",resultline);
13356: fprintf(ficres,"result: %s\n",resultline);
13357: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 13358: } else
13359: goto end;
1.307 brouard 13360: break;
13361: case 14:
13362: printf("Error: Unknown command '%s'\n",line);
13363: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 13364: if(line[0] == ' ' || line[0] == '\n'){
13365: printf("It should not be an empty line '%s'\n",line);
13366: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
13367: }
1.307 brouard 13368: if(ncovmodel >=2 && nresult==0 ){
13369: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
13370: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 13371: }
1.307 brouard 13372: /* goto end; */
13373: break;
1.308 brouard 13374: case 15:
13375: printf("End of resultlines.\n");
13376: fprintf(ficlog,"End of resultlines.\n");
13377: break;
13378: default: /* parameterline =0 */
1.307 brouard 13379: nresult=1;
13380: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 13381: } /* End switch parameterline */
13382: }while(endishere==0); /* End do */
1.126 brouard 13383:
1.230 brouard 13384: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 13385: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 13386:
13387: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 13388: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 13389: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 13390: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13391: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 13392: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 13393: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13394: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 13395: }else{
1.270 brouard 13396: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 13397: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
13398: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
13399: if(prvforecast==1){
13400: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
13401: jprojd=jproj1;
13402: mprojd=mproj1;
13403: anprojd=anproj1;
13404: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
13405: jprojf=jproj2;
13406: mprojf=mproj2;
13407: anprojf=anproj2;
13408: } else if(prvforecast == 2){
13409: dateprojd=dateintmean;
13410: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
13411: dateprojf=dateintmean+yrfproj;
13412: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
13413: }
13414: if(prvbackcast==1){
13415: datebackd=(jback1+12*mback1+365*anback1)/365;
13416: jbackd=jback1;
13417: mbackd=mback1;
13418: anbackd=anback1;
13419: datebackf=(jback2+12*mback2+365*anback2)/365;
13420: jbackf=jback2;
13421: mbackf=mback2;
13422: anbackf=anback2;
13423: } else if(prvbackcast == 2){
13424: datebackd=dateintmean;
13425: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
13426: datebackf=dateintmean-yrbproj;
13427: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
13428: }
13429:
13430: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 13431: }
13432: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 13433: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
13434: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 13435:
1.225 brouard 13436: /*------------ free_vector -------------*/
13437: /* chdir(path); */
1.220 brouard 13438:
1.215 brouard 13439: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
13440: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
13441: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
13442: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 13443: free_lvector(num,firstobs,lastobs);
13444: free_vector(agedc,firstobs,lastobs);
1.126 brouard 13445: /*free_matrix(covar,0,NCOVMAX,1,n);*/
13446: /*free_matrix(covar,1,NCOVMAX,1,n);*/
13447: fclose(ficparo);
13448: fclose(ficres);
1.220 brouard 13449:
13450:
1.186 brouard 13451: /* Other results (useful)*/
1.220 brouard 13452:
13453:
1.126 brouard 13454: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 13455: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
13456: prlim=matrix(1,nlstate,1,nlstate);
1.332 ! brouard 13457: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 13458: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 13459: fclose(ficrespl);
13460:
13461: /*------------- h Pij x at various ages ------------*/
1.180 brouard 13462: /*#include "hpijx.h"*/
1.332 ! brouard 13463: /** 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?*/
! 13464: /* calls hpxij with combination k */
1.180 brouard 13465: hPijx(p, bage, fage);
1.145 brouard 13466: fclose(ficrespij);
1.227 brouard 13467:
1.220 brouard 13468: /* ncovcombmax= pow(2,cptcoveff); */
1.332 ! brouard 13469: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 13470: k=1;
1.126 brouard 13471: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 13472:
1.269 brouard 13473: /* Prevalence for each covariate combination in probs[age][status][cov] */
13474: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13475: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 13476: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 13477: for(k=1;k<=ncovcombmax;k++)
13478: probs[i][j][k]=0.;
1.269 brouard 13479: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
13480: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 13481: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 13482: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13483: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 13484: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 13485: for(k=1;k<=ncovcombmax;k++)
13486: mobaverages[i][j][k]=0.;
1.219 brouard 13487: mobaverage=mobaverages;
13488: if (mobilav!=0) {
1.235 brouard 13489: printf("Movingaveraging observed prevalence\n");
1.258 brouard 13490: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 13491: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
13492: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
13493: printf(" Error in movingaverage mobilav=%d\n",mobilav);
13494: }
1.269 brouard 13495: } else if (mobilavproj !=0) {
1.235 brouard 13496: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 13497: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 13498: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
13499: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
13500: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
13501: }
1.269 brouard 13502: }else{
13503: printf("Internal error moving average\n");
13504: fflush(stdout);
13505: exit(1);
1.219 brouard 13506: }
13507: }/* end if moving average */
1.227 brouard 13508:
1.126 brouard 13509: /*---------- Forecasting ------------------*/
1.296 brouard 13510: if(prevfcast==1){
13511: /* /\* if(stepm ==1){*\/ */
13512: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13513: /*This done previously after freqsummary.*/
13514: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
13515: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
13516:
13517: /* } else if (prvforecast==2){ */
13518: /* /\* if(stepm ==1){*\/ */
13519: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13520: /* } */
13521: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
13522: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 13523: }
1.269 brouard 13524:
1.296 brouard 13525: /* Prevbcasting */
13526: if(prevbcast==1){
1.219 brouard 13527: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13528: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13529: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13530:
13531: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
13532:
13533: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 13534:
1.219 brouard 13535: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
13536: fclose(ficresplb);
13537:
1.222 brouard 13538: hBijx(p, bage, fage, mobaverage);
13539: fclose(ficrespijb);
1.219 brouard 13540:
1.296 brouard 13541: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
13542: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
13543: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
13544: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
13545: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
13546: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
13547:
13548:
1.269 brouard 13549: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13550:
13551:
1.269 brouard 13552: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 13553: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13554: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13555: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 13556: } /* end Prevbcasting */
1.268 brouard 13557:
1.186 brouard 13558:
13559: /* ------ Other prevalence ratios------------ */
1.126 brouard 13560:
1.215 brouard 13561: free_ivector(wav,1,imx);
13562: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
13563: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
13564: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 13565:
13566:
1.127 brouard 13567: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 13568:
1.201 brouard 13569: strcpy(filerese,"E_");
13570: strcat(filerese,fileresu);
1.126 brouard 13571: if((ficreseij=fopen(filerese,"w"))==NULL) {
13572: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13573: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13574: }
1.208 brouard 13575: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
13576: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 13577:
13578: pstamp(ficreseij);
1.219 brouard 13579:
1.235 brouard 13580: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13581: if (cptcovn < 1){i1=1;}
13582:
13583: for(nres=1; nres <= nresult; nres++) /* For each resultline */
13584: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 13585: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 13586: continue;
1.219 brouard 13587: fprintf(ficreseij,"\n#****** ");
1.235 brouard 13588: printf("\n#****** ");
1.225 brouard 13589: for(j=1;j<=cptcoveff;j++) {
1.332 ! brouard 13590: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
! 13591: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.235 brouard 13592: }
13593: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 ! brouard 13594: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
! 13595: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
1.219 brouard 13596: }
13597: fprintf(ficreseij,"******\n");
1.235 brouard 13598: printf("******\n");
1.219 brouard 13599:
13600: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13601: oldm=oldms;savm=savms;
1.330 brouard 13602: /* 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 13603: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 13604:
1.219 brouard 13605: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 13606: }
13607: fclose(ficreseij);
1.208 brouard 13608: printf("done evsij\n");fflush(stdout);
13609: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 13610:
1.218 brouard 13611:
1.227 brouard 13612: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 13613:
1.201 brouard 13614: strcpy(filerest,"T_");
13615: strcat(filerest,fileresu);
1.127 brouard 13616: if((ficrest=fopen(filerest,"w"))==NULL) {
13617: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
13618: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
13619: }
1.208 brouard 13620: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
13621: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 13622: strcpy(fileresstde,"STDE_");
13623: strcat(fileresstde,fileresu);
1.126 brouard 13624: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 13625: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
13626: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 13627: }
1.227 brouard 13628: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
13629: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 13630:
1.201 brouard 13631: strcpy(filerescve,"CVE_");
13632: strcat(filerescve,fileresu);
1.126 brouard 13633: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 13634: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
13635: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 13636: }
1.227 brouard 13637: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
13638: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 13639:
1.201 brouard 13640: strcpy(fileresv,"V_");
13641: strcat(fileresv,fileresu);
1.126 brouard 13642: if((ficresvij=fopen(fileresv,"w"))==NULL) {
13643: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
13644: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
13645: }
1.227 brouard 13646: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
13647: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 13648:
1.235 brouard 13649: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13650: if (cptcovn < 1){i1=1;}
13651:
13652: for(nres=1; nres <= nresult; nres++) /* For each resultline */
13653: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 13654: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 13655: continue;
1.321 brouard 13656: printf("\n# model %s \n#****** Result for:", model);
13657: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
13658: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.227 brouard 13659: for(j=1;j<=cptcoveff;j++){
1.332 ! brouard 13660: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
! 13661: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
! 13662: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.227 brouard 13663: }
1.235 brouard 13664: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 ! brouard 13665: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
! 13666: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
! 13667: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
1.235 brouard 13668: }
1.208 brouard 13669: fprintf(ficrest,"******\n");
1.227 brouard 13670: fprintf(ficlog,"******\n");
13671: printf("******\n");
1.208 brouard 13672:
13673: fprintf(ficresstdeij,"\n#****** ");
13674: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 13675: for(j=1;j<=cptcoveff;j++) {
1.332 ! brouard 13676: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
! 13677: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
1.208 brouard 13678: }
1.235 brouard 13679: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 ! brouard 13680: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
! 13681: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]);
1.235 brouard 13682: }
1.208 brouard 13683: fprintf(ficresstdeij,"******\n");
13684: fprintf(ficrescveij,"******\n");
13685:
13686: fprintf(ficresvij,"\n#****** ");
1.238 brouard 13687: /* pstamp(ficresvij); */
1.225 brouard 13688: for(j=1;j<=cptcoveff;j++)
1.332 ! brouard 13689: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]);
1.235 brouard 13690: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 ! brouard 13691: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
! 13692: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 13693: }
1.208 brouard 13694: fprintf(ficresvij,"******\n");
13695:
13696: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13697: oldm=oldms;savm=savms;
1.235 brouard 13698: printf(" cvevsij ");
13699: fprintf(ficlog, " cvevsij ");
13700: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 13701: printf(" end cvevsij \n ");
13702: fprintf(ficlog, " end cvevsij \n ");
13703:
13704: /*
13705: */
13706: /* goto endfree; */
13707:
13708: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13709: pstamp(ficrest);
13710:
1.269 brouard 13711: epj=vector(1,nlstate+1);
1.208 brouard 13712: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 13713: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
13714: cptcod= 0; /* To be deleted */
13715: printf("varevsij vpopbased=%d \n",vpopbased);
13716: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 13717: 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 13718: 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 ");
13719: if(vpopbased==1)
13720: 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);
13721: else
1.288 brouard 13722: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13723: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
13724: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
13725: fprintf(ficrest,"\n");
13726: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 13727: printf("Computing age specific forward period (stable) prevalences in each health state \n");
13728: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13729: for(age=bage; age <=fage ;age++){
1.235 brouard 13730: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 13731: if (vpopbased==1) {
13732: if(mobilav ==0){
13733: for(i=1; i<=nlstate;i++)
13734: prlim[i][i]=probs[(int)age][i][k];
13735: }else{ /* mobilav */
13736: for(i=1; i<=nlstate;i++)
13737: prlim[i][i]=mobaverage[(int)age][i][k];
13738: }
13739: }
1.219 brouard 13740:
1.227 brouard 13741: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
13742: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
13743: /* printf(" age %4.0f ",age); */
13744: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
13745: for(i=1, epj[j]=0.;i <=nlstate;i++) {
13746: epj[j] += prlim[i][i]*eij[i][j][(int)age];
13747: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
13748: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
13749: }
13750: epj[nlstate+1] +=epj[j];
13751: }
13752: /* printf(" age %4.0f \n",age); */
1.219 brouard 13753:
1.227 brouard 13754: for(i=1, vepp=0.;i <=nlstate;i++)
13755: for(j=1;j <=nlstate;j++)
13756: vepp += vareij[i][j][(int)age];
13757: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
13758: for(j=1;j <=nlstate;j++){
13759: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
13760: }
13761: fprintf(ficrest,"\n");
13762: }
1.208 brouard 13763: } /* End vpopbased */
1.269 brouard 13764: free_vector(epj,1,nlstate+1);
1.208 brouard 13765: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
13766: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 13767: printf("done selection\n");fflush(stdout);
13768: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 13769:
1.235 brouard 13770: } /* End k selection */
1.227 brouard 13771:
13772: printf("done State-specific expectancies\n");fflush(stdout);
13773: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
13774:
1.288 brouard 13775: /* variance-covariance of forward period prevalence*/
1.269 brouard 13776: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13777:
1.227 brouard 13778:
1.290 brouard 13779: free_vector(weight,firstobs,lastobs);
1.330 brouard 13780: free_imatrix(Tvardk,1,NCOVMAX,1,2);
1.227 brouard 13781: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 13782: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
13783: free_matrix(anint,1,maxwav,firstobs,lastobs);
13784: free_matrix(mint,1,maxwav,firstobs,lastobs);
13785: free_ivector(cod,firstobs,lastobs);
1.227 brouard 13786: free_ivector(tab,1,NCOVMAX);
13787: fclose(ficresstdeij);
13788: fclose(ficrescveij);
13789: fclose(ficresvij);
13790: fclose(ficrest);
13791: fclose(ficpar);
13792:
13793:
1.126 brouard 13794: /*---------- End : free ----------------*/
1.219 brouard 13795: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 13796: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
13797: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 13798: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
13799: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 13800: } /* mle==-3 arrives here for freeing */
1.227 brouard 13801: /* endfree:*/
13802: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
13803: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
13804: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 13805: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
13806: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
13807: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
13808: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 13809: free_matrix(matcov,1,npar,1,npar);
13810: free_matrix(hess,1,npar,1,npar);
13811: /*free_vector(delti,1,npar);*/
13812: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13813: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 13814: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 13815: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13816:
13817: free_ivector(ncodemax,1,NCOVMAX);
13818: free_ivector(ncodemaxwundef,1,NCOVMAX);
13819: free_ivector(Dummy,-1,NCOVMAX);
13820: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 13821: free_ivector(DummyV,1,NCOVMAX);
13822: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 13823: free_ivector(Typevar,-1,NCOVMAX);
13824: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 13825: free_ivector(TvarsQ,1,NCOVMAX);
13826: free_ivector(TvarsQind,1,NCOVMAX);
13827: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 13828: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 13829: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 13830: free_ivector(TvarFD,1,NCOVMAX);
13831: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 13832: free_ivector(TvarF,1,NCOVMAX);
13833: free_ivector(TvarFind,1,NCOVMAX);
13834: free_ivector(TvarV,1,NCOVMAX);
13835: free_ivector(TvarVind,1,NCOVMAX);
13836: free_ivector(TvarA,1,NCOVMAX);
13837: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 13838: free_ivector(TvarFQ,1,NCOVMAX);
13839: free_ivector(TvarFQind,1,NCOVMAX);
13840: free_ivector(TvarVD,1,NCOVMAX);
13841: free_ivector(TvarVDind,1,NCOVMAX);
13842: free_ivector(TvarVQ,1,NCOVMAX);
13843: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 13844: free_ivector(Tvarsel,1,NCOVMAX);
13845: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 13846: free_ivector(Tposprod,1,NCOVMAX);
13847: free_ivector(Tprod,1,NCOVMAX);
13848: free_ivector(Tvaraff,1,NCOVMAX);
13849: free_ivector(invalidvarcomb,1,ncovcombmax);
13850: free_ivector(Tage,1,NCOVMAX);
13851: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 13852: free_ivector(TmodelInvind,1,NCOVMAX);
13853: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 ! brouard 13854:
! 13855: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
! 13856:
1.227 brouard 13857: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
13858: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 13859: fflush(fichtm);
13860: fflush(ficgp);
13861:
1.227 brouard 13862:
1.126 brouard 13863: if((nberr >0) || (nbwarn>0)){
1.216 brouard 13864: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
13865: 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 13866: }else{
13867: printf("End of Imach\n");
13868: fprintf(ficlog,"End of Imach\n");
13869: }
13870: printf("See log file on %s\n",filelog);
13871: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 13872: /*(void) gettimeofday(&end_time,&tzp);*/
13873: rend_time = time(NULL);
13874: end_time = *localtime(&rend_time);
13875: /* tml = *localtime(&end_time.tm_sec); */
13876: strcpy(strtend,asctime(&end_time));
1.126 brouard 13877: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
13878: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 13879: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 13880:
1.157 brouard 13881: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
13882: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
13883: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 13884: /* printf("Total time was %d uSec.\n", total_usecs);*/
13885: /* if(fileappend(fichtm,optionfilehtm)){ */
13886: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13887: fclose(fichtm);
13888: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13889: fclose(fichtmcov);
13890: fclose(ficgp);
13891: fclose(ficlog);
13892: /*------ End -----------*/
1.227 brouard 13893:
1.281 brouard 13894:
13895: /* Executes gnuplot */
1.227 brouard 13896:
13897: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 13898: #ifdef WIN32
1.227 brouard 13899: if (_chdir(pathcd) != 0)
13900: printf("Can't move to directory %s!\n",path);
13901: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 13902: #else
1.227 brouard 13903: if(chdir(pathcd) != 0)
13904: printf("Can't move to directory %s!\n", path);
13905: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 13906: #endif
1.126 brouard 13907: printf("Current directory %s!\n",pathcd);
13908: /*strcat(plotcmd,CHARSEPARATOR);*/
13909: sprintf(plotcmd,"gnuplot");
1.157 brouard 13910: #ifdef _WIN32
1.126 brouard 13911: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
13912: #endif
13913: if(!stat(plotcmd,&info)){
1.158 brouard 13914: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13915: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 13916: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 13917: }else
13918: strcpy(pplotcmd,plotcmd);
1.157 brouard 13919: #ifdef __unix
1.126 brouard 13920: strcpy(plotcmd,GNUPLOTPROGRAM);
13921: if(!stat(plotcmd,&info)){
1.158 brouard 13922: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13923: }else
13924: strcpy(pplotcmd,plotcmd);
13925: #endif
13926: }else
13927: strcpy(pplotcmd,plotcmd);
13928:
13929: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 13930: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 13931: strcpy(pplotcmd,plotcmd);
1.227 brouard 13932:
1.126 brouard 13933: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 13934: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 13935: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 13936: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 13937: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 13938: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 13939: strcpy(plotcmd,pplotcmd);
13940: }
1.126 brouard 13941: }
1.158 brouard 13942: printf(" Successful, please wait...");
1.126 brouard 13943: while (z[0] != 'q') {
13944: /* chdir(path); */
1.154 brouard 13945: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 13946: scanf("%s",z);
13947: /* if (z[0] == 'c') system("./imach"); */
13948: if (z[0] == 'e') {
1.158 brouard 13949: #ifdef __APPLE__
1.152 brouard 13950: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 13951: #elif __linux
13952: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 13953: #else
1.152 brouard 13954: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 13955: #endif
13956: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
13957: system(pplotcmd);
1.126 brouard 13958: }
13959: else if (z[0] == 'g') system(plotcmd);
13960: else if (z[0] == 'q') exit(0);
13961: }
1.227 brouard 13962: end:
1.126 brouard 13963: while (z[0] != 'q') {
1.195 brouard 13964: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 13965: scanf("%s",z);
13966: }
1.283 brouard 13967: printf("End\n");
1.282 brouard 13968: exit(0);
1.126 brouard 13969: }
FreeBSD-CVSweb <freebsd-cvsweb@FreeBSD.org>
![[BACK]](/icons/small/back.gif){kind=icon}
Return to imach.c CVS log ![[TXT]](/icons/small/text.gif){kind=icon}
![[DIR]](/icons/small/dir.gif){kind=icon}
Up to [Local Repository] / imach / src