Annotation of imach/src/imach.c, revision 1.331
1.331 ! brouard 1: /* $Id: imach.c,v 1.330 2022/08/06 07:18:25 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.331 ! brouard 4: Revision 1.330 2022/08/06 07:18:25 brouard
! 5: Summary: last 0.99r31
! 6:
! 7: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
! 8:
1.330 brouard 9: Revision 1.329 2022/08/03 17:29:54 brouard
10: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
11:
1.329 brouard 12: Revision 1.328 2022/07/27 17:40:48 brouard
13: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
14:
1.328 brouard 15: Revision 1.327 2022/07/27 14:47:35 brouard
16: Summary: Still a problem for one-step probabilities in case of quantitative variables
17:
1.327 brouard 18: Revision 1.326 2022/07/26 17:33:55 brouard
19: Summary: some test with nres=1
20:
1.326 brouard 21: Revision 1.325 2022/07/25 14:27:23 brouard
22: Summary: r30
23:
24: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
25: coredumped, revealed by Feiuno, thank you.
26:
1.325 brouard 27: Revision 1.324 2022/07/23 17:44:26 brouard
28: *** empty log message ***
29:
1.324 brouard 30: Revision 1.323 2022/07/22 12:30:08 brouard
31: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
32:
1.323 brouard 33: Revision 1.322 2022/07/22 12:27:48 brouard
34: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
35:
1.322 brouard 36: Revision 1.321 2022/07/22 12:04:24 brouard
37: Summary: r28
38:
39: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
40:
1.321 brouard 41: Revision 1.320 2022/06/02 05:10:11 brouard
42: *** empty log message ***
43:
1.320 brouard 44: Revision 1.319 2022/06/02 04:45:11 brouard
45: * imach.c (Module): Adding the Wald tests from the log to the main
46: htm for better display of the maximum likelihood estimators.
47:
1.319 brouard 48: Revision 1.318 2022/05/24 08:10:59 brouard
49: * imach.c (Module): Some attempts to find a bug of wrong estimates
50: of confidencce intervals with product in the equation modelC
51:
1.318 brouard 52: Revision 1.317 2022/05/15 15:06:23 brouard
53: * imach.c (Module): Some minor improvements
54:
1.317 brouard 55: Revision 1.316 2022/05/11 15:11:31 brouard
56: Summary: r27
57:
1.316 brouard 58: Revision 1.315 2022/05/11 15:06:32 brouard
59: *** empty log message ***
60:
1.315 brouard 61: Revision 1.314 2022/04/13 17:43:09 brouard
62: * imach.c (Module): Adding link to text data files
63:
1.314 brouard 64: Revision 1.313 2022/04/11 15:57:42 brouard
65: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
66:
1.313 brouard 67: Revision 1.312 2022/04/05 21:24:39 brouard
68: *** empty log message ***
69:
1.312 brouard 70: Revision 1.311 2022/04/05 21:03:51 brouard
71: Summary: Fixed quantitative covariates
72:
73: Fixed covariates (dummy or quantitative)
74: with missing values have never been allowed but are ERRORS and
75: program quits. Standard deviations of fixed covariates were
76: wrongly computed. Mean and standard deviations of time varying
77: covariates are still not computed.
78:
1.311 brouard 79: Revision 1.310 2022/03/17 08:45:53 brouard
80: Summary: 99r25
81:
82: Improving detection of errors: result lines should be compatible with
83: the model.
84:
1.310 brouard 85: Revision 1.309 2021/05/20 12:39:14 brouard
86: Summary: Version 0.99r24
87:
1.309 brouard 88: Revision 1.308 2021/03/31 13:11:57 brouard
89: Summary: Version 0.99r23
90:
91:
92: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
93:
1.308 brouard 94: Revision 1.307 2021/03/08 18:11:32 brouard
95: Summary: 0.99r22 fixed bug on result:
96:
1.307 brouard 97: Revision 1.306 2021/02/20 15:44:02 brouard
98: Summary: Version 0.99r21
99:
100: * imach.c (Module): Fix bug on quitting after result lines!
101: (Module): Version 0.99r21
102:
1.306 brouard 103: Revision 1.305 2021/02/20 15:28:30 brouard
104: * imach.c (Module): Fix bug on quitting after result lines!
105:
1.305 brouard 106: Revision 1.304 2021/02/12 11:34:20 brouard
107: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
108:
1.304 brouard 109: Revision 1.303 2021/02/11 19:50:15 brouard
110: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
111:
1.303 brouard 112: Revision 1.302 2020/02/22 21:00:05 brouard
113: * (Module): imach.c Update mle=-3 (for computing Life expectancy
114: and life table from the data without any state)
115:
1.302 brouard 116: Revision 1.301 2019/06/04 13:51:20 brouard
117: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
118:
1.301 brouard 119: Revision 1.300 2019/05/22 19:09:45 brouard
120: Summary: version 0.99r19 of May 2019
121:
1.300 brouard 122: Revision 1.299 2019/05/22 18:37:08 brouard
123: Summary: Cleaned 0.99r19
124:
1.299 brouard 125: Revision 1.298 2019/05/22 18:19:56 brouard
126: *** empty log message ***
127:
1.298 brouard 128: Revision 1.297 2019/05/22 17:56:10 brouard
129: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
130:
1.297 brouard 131: Revision 1.296 2019/05/20 13:03:18 brouard
132: Summary: Projection syntax simplified
133:
134:
135: We can now start projections, forward or backward, from the mean date
136: of inteviews up to or down to a number of years of projection:
137: prevforecast=1 yearsfproj=15.3 mobil_average=0
138: or
139: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
140: or
141: prevbackcast=1 yearsbproj=12.3 mobil_average=1
142: or
143: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
144:
1.296 brouard 145: Revision 1.295 2019/05/18 09:52:50 brouard
146: Summary: doxygen tex bug
147:
1.295 brouard 148: Revision 1.294 2019/05/16 14:54:33 brouard
149: Summary: There was some wrong lines added
150:
1.294 brouard 151: Revision 1.293 2019/05/09 15:17:34 brouard
152: *** empty log message ***
153:
1.293 brouard 154: Revision 1.292 2019/05/09 14:17:20 brouard
155: Summary: Some updates
156:
1.292 brouard 157: Revision 1.291 2019/05/09 13:44:18 brouard
158: Summary: Before ncovmax
159:
1.291 brouard 160: Revision 1.290 2019/05/09 13:39:37 brouard
161: Summary: 0.99r18 unlimited number of individuals
162:
163: 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.
164:
1.290 brouard 165: Revision 1.289 2018/12/13 09:16:26 brouard
166: Summary: Bug for young ages (<-30) will be in r17
167:
1.289 brouard 168: Revision 1.288 2018/05/02 20:58:27 brouard
169: Summary: Some bugs fixed
170:
1.288 brouard 171: Revision 1.287 2018/05/01 17:57:25 brouard
172: Summary: Bug fixed by providing frequencies only for non missing covariates
173:
1.287 brouard 174: Revision 1.286 2018/04/27 14:27:04 brouard
175: Summary: some minor bugs
176:
1.286 brouard 177: Revision 1.285 2018/04/21 21:02:16 brouard
178: Summary: Some bugs fixed, valgrind tested
179:
1.285 brouard 180: Revision 1.284 2018/04/20 05:22:13 brouard
181: Summary: Computing mean and stdeviation of fixed quantitative variables
182:
1.284 brouard 183: Revision 1.283 2018/04/19 14:49:16 brouard
184: Summary: Some minor bugs fixed
185:
1.283 brouard 186: Revision 1.282 2018/02/27 22:50:02 brouard
187: *** empty log message ***
188:
1.282 brouard 189: Revision 1.281 2018/02/27 19:25:23 brouard
190: Summary: Adding second argument for quitting
191:
1.281 brouard 192: Revision 1.280 2018/02/21 07:58:13 brouard
193: Summary: 0.99r15
194:
195: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
196:
1.280 brouard 197: Revision 1.279 2017/07/20 13:35:01 brouard
198: Summary: temporary working
199:
1.279 brouard 200: Revision 1.278 2017/07/19 14:09:02 brouard
201: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
202:
1.278 brouard 203: Revision 1.277 2017/07/17 08:53:49 brouard
204: Summary: BOM files can be read now
205:
1.277 brouard 206: Revision 1.276 2017/06/30 15:48:31 brouard
207: Summary: Graphs improvements
208:
1.276 brouard 209: Revision 1.275 2017/06/30 13:39:33 brouard
210: Summary: Saito's color
211:
1.275 brouard 212: Revision 1.274 2017/06/29 09:47:08 brouard
213: Summary: Version 0.99r14
214:
1.274 brouard 215: Revision 1.273 2017/06/27 11:06:02 brouard
216: Summary: More documentation on projections
217:
1.273 brouard 218: Revision 1.272 2017/06/27 10:22:40 brouard
219: Summary: Color of backprojection changed from 6 to 5(yellow)
220:
1.272 brouard 221: Revision 1.271 2017/06/27 10:17:50 brouard
222: Summary: Some bug with rint
223:
1.271 brouard 224: Revision 1.270 2017/05/24 05:45:29 brouard
225: *** empty log message ***
226:
1.270 brouard 227: Revision 1.269 2017/05/23 08:39:25 brouard
228: Summary: Code into subroutine, cleanings
229:
1.269 brouard 230: Revision 1.268 2017/05/18 20:09:32 brouard
231: Summary: backprojection and confidence intervals of backprevalence
232:
1.268 brouard 233: Revision 1.267 2017/05/13 10:25:05 brouard
234: Summary: temporary save for backprojection
235:
1.267 brouard 236: Revision 1.266 2017/05/13 07:26:12 brouard
237: Summary: Version 0.99r13 (improvements and bugs fixed)
238:
1.266 brouard 239: Revision 1.265 2017/04/26 16:22:11 brouard
240: Summary: imach 0.99r13 Some bugs fixed
241:
1.265 brouard 242: Revision 1.264 2017/04/26 06:01:29 brouard
243: Summary: Labels in graphs
244:
1.264 brouard 245: Revision 1.263 2017/04/24 15:23:15 brouard
246: Summary: to save
247:
1.263 brouard 248: Revision 1.262 2017/04/18 16:48:12 brouard
249: *** empty log message ***
250:
1.262 brouard 251: Revision 1.261 2017/04/05 10:14:09 brouard
252: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
253:
1.261 brouard 254: Revision 1.260 2017/04/04 17:46:59 brouard
255: Summary: Gnuplot indexations fixed (humm)
256:
1.260 brouard 257: Revision 1.259 2017/04/04 13:01:16 brouard
258: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
259:
1.259 brouard 260: Revision 1.258 2017/04/03 10:17:47 brouard
261: Summary: Version 0.99r12
262:
263: Some cleanings, conformed with updated documentation.
264:
1.258 brouard 265: Revision 1.257 2017/03/29 16:53:30 brouard
266: Summary: Temp
267:
1.257 brouard 268: Revision 1.256 2017/03/27 05:50:23 brouard
269: Summary: Temporary
270:
1.256 brouard 271: Revision 1.255 2017/03/08 16:02:28 brouard
272: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
273:
1.255 brouard 274: Revision 1.254 2017/03/08 07:13:00 brouard
275: Summary: Fixing data parameter line
276:
1.254 brouard 277: Revision 1.253 2016/12/15 11:59:41 brouard
278: Summary: 0.99 in progress
279:
1.253 brouard 280: Revision 1.252 2016/09/15 21:15:37 brouard
281: *** empty log message ***
282:
1.252 brouard 283: Revision 1.251 2016/09/15 15:01:13 brouard
284: Summary: not working
285:
1.251 brouard 286: Revision 1.250 2016/09/08 16:07:27 brouard
287: Summary: continue
288:
1.250 brouard 289: Revision 1.249 2016/09/07 17:14:18 brouard
290: Summary: Starting values from frequencies
291:
1.249 brouard 292: Revision 1.248 2016/09/07 14:10:18 brouard
293: *** empty log message ***
294:
1.248 brouard 295: Revision 1.247 2016/09/02 11:11:21 brouard
296: *** empty log message ***
297:
1.247 brouard 298: Revision 1.246 2016/09/02 08:49:22 brouard
299: *** empty log message ***
300:
1.246 brouard 301: Revision 1.245 2016/09/02 07:25:01 brouard
302: *** empty log message ***
303:
1.245 brouard 304: Revision 1.244 2016/09/02 07:17:34 brouard
305: *** empty log message ***
306:
1.244 brouard 307: Revision 1.243 2016/09/02 06:45:35 brouard
308: *** empty log message ***
309:
1.243 brouard 310: Revision 1.242 2016/08/30 15:01:20 brouard
311: Summary: Fixing a lots
312:
1.242 brouard 313: Revision 1.241 2016/08/29 17:17:25 brouard
314: Summary: gnuplot problem in Back projection to fix
315:
1.241 brouard 316: Revision 1.240 2016/08/29 07:53:18 brouard
317: Summary: Better
318:
1.240 brouard 319: Revision 1.239 2016/08/26 15:51:03 brouard
320: Summary: Improvement in Powell output in order to copy and paste
321:
322: Author:
323:
1.239 brouard 324: Revision 1.238 2016/08/26 14:23:35 brouard
325: Summary: Starting tests of 0.99
326:
1.238 brouard 327: Revision 1.237 2016/08/26 09:20:19 brouard
328: Summary: to valgrind
329:
1.237 brouard 330: Revision 1.236 2016/08/25 10:50:18 brouard
331: *** empty log message ***
332:
1.236 brouard 333: Revision 1.235 2016/08/25 06:59:23 brouard
334: *** empty log message ***
335:
1.235 brouard 336: Revision 1.234 2016/08/23 16:51:20 brouard
337: *** empty log message ***
338:
1.234 brouard 339: Revision 1.233 2016/08/23 07:40:50 brouard
340: Summary: not working
341:
1.233 brouard 342: Revision 1.232 2016/08/22 14:20:21 brouard
343: Summary: not working
344:
1.232 brouard 345: Revision 1.231 2016/08/22 07:17:15 brouard
346: Summary: not working
347:
1.231 brouard 348: Revision 1.230 2016/08/22 06:55:53 brouard
349: Summary: Not working
350:
1.230 brouard 351: Revision 1.229 2016/07/23 09:45:53 brouard
352: Summary: Completing for func too
353:
1.229 brouard 354: Revision 1.228 2016/07/22 17:45:30 brouard
355: Summary: Fixing some arrays, still debugging
356:
1.227 brouard 357: Revision 1.226 2016/07/12 18:42:34 brouard
358: Summary: temp
359:
1.226 brouard 360: Revision 1.225 2016/07/12 08:40:03 brouard
361: Summary: saving but not running
362:
1.225 brouard 363: Revision 1.224 2016/07/01 13:16:01 brouard
364: Summary: Fixes
365:
1.224 brouard 366: Revision 1.223 2016/02/19 09:23:35 brouard
367: Summary: temporary
368:
1.223 brouard 369: Revision 1.222 2016/02/17 08:14:50 brouard
370: Summary: Probably last 0.98 stable version 0.98r6
371:
1.222 brouard 372: Revision 1.221 2016/02/15 23:35:36 brouard
373: Summary: minor bug
374:
1.220 brouard 375: Revision 1.219 2016/02/15 00:48:12 brouard
376: *** empty log message ***
377:
1.219 brouard 378: Revision 1.218 2016/02/12 11:29:23 brouard
379: Summary: 0.99 Back projections
380:
1.218 brouard 381: Revision 1.217 2015/12/23 17:18:31 brouard
382: Summary: Experimental backcast
383:
1.217 brouard 384: Revision 1.216 2015/12/18 17:32:11 brouard
385: Summary: 0.98r4 Warning and status=-2
386:
387: Version 0.98r4 is now:
388: - displaying an error when status is -1, date of interview unknown and date of death known;
389: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
390: Older changes concerning s=-2, dating from 2005 have been supersed.
391:
1.216 brouard 392: Revision 1.215 2015/12/16 08:52:24 brouard
393: Summary: 0.98r4 working
394:
1.215 brouard 395: Revision 1.214 2015/12/16 06:57:54 brouard
396: Summary: temporary not working
397:
1.214 brouard 398: Revision 1.213 2015/12/11 18:22:17 brouard
399: Summary: 0.98r4
400:
1.213 brouard 401: Revision 1.212 2015/11/21 12:47:24 brouard
402: Summary: minor typo
403:
1.212 brouard 404: Revision 1.211 2015/11/21 12:41:11 brouard
405: Summary: 0.98r3 with some graph of projected cross-sectional
406:
407: Author: Nicolas Brouard
408:
1.211 brouard 409: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 410: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 411: Summary: Adding ftolpl parameter
412: Author: N Brouard
413:
414: We had difficulties to get smoothed confidence intervals. It was due
415: to the period prevalence which wasn't computed accurately. The inner
416: parameter ftolpl is now an outer parameter of the .imach parameter
417: file after estepm. If ftolpl is small 1.e-4 and estepm too,
418: computation are long.
419:
1.209 brouard 420: Revision 1.208 2015/11/17 14:31:57 brouard
421: Summary: temporary
422:
1.208 brouard 423: Revision 1.207 2015/10/27 17:36:57 brouard
424: *** empty log message ***
425:
1.207 brouard 426: Revision 1.206 2015/10/24 07:14:11 brouard
427: *** empty log message ***
428:
1.206 brouard 429: Revision 1.205 2015/10/23 15:50:53 brouard
430: Summary: 0.98r3 some clarification for graphs on likelihood contributions
431:
1.205 brouard 432: Revision 1.204 2015/10/01 16:20:26 brouard
433: Summary: Some new graphs of contribution to likelihood
434:
1.204 brouard 435: Revision 1.203 2015/09/30 17:45:14 brouard
436: Summary: looking at better estimation of the hessian
437:
438: Also a better criteria for convergence to the period prevalence And
439: therefore adding the number of years needed to converge. (The
440: prevalence in any alive state shold sum to one
441:
1.203 brouard 442: Revision 1.202 2015/09/22 19:45:16 brouard
443: Summary: Adding some overall graph on contribution to likelihood. Might change
444:
1.202 brouard 445: Revision 1.201 2015/09/15 17:34:58 brouard
446: Summary: 0.98r0
447:
448: - Some new graphs like suvival functions
449: - Some bugs fixed like model=1+age+V2.
450:
1.201 brouard 451: Revision 1.200 2015/09/09 16:53:55 brouard
452: Summary: Big bug thanks to Flavia
453:
454: Even model=1+age+V2. did not work anymore
455:
1.200 brouard 456: Revision 1.199 2015/09/07 14:09:23 brouard
457: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
458:
1.199 brouard 459: Revision 1.198 2015/09/03 07:14:39 brouard
460: Summary: 0.98q5 Flavia
461:
1.198 brouard 462: Revision 1.197 2015/09/01 18:24:39 brouard
463: *** empty log message ***
464:
1.197 brouard 465: Revision 1.196 2015/08/18 23:17:52 brouard
466: Summary: 0.98q5
467:
1.196 brouard 468: Revision 1.195 2015/08/18 16:28:39 brouard
469: Summary: Adding a hack for testing purpose
470:
471: After reading the title, ftol and model lines, if the comment line has
472: a q, starting with #q, the answer at the end of the run is quit. It
473: permits to run test files in batch with ctest. The former workaround was
474: $ echo q | imach foo.imach
475:
1.195 brouard 476: Revision 1.194 2015/08/18 13:32:00 brouard
477: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
478:
1.194 brouard 479: Revision 1.193 2015/08/04 07:17:42 brouard
480: Summary: 0.98q4
481:
1.193 brouard 482: Revision 1.192 2015/07/16 16:49:02 brouard
483: Summary: Fixing some outputs
484:
1.192 brouard 485: Revision 1.191 2015/07/14 10:00:33 brouard
486: Summary: Some fixes
487:
1.191 brouard 488: Revision 1.190 2015/05/05 08:51:13 brouard
489: Summary: Adding digits in output parameters (7 digits instead of 6)
490:
491: Fix 1+age+.
492:
1.190 brouard 493: Revision 1.189 2015/04/30 14:45:16 brouard
494: Summary: 0.98q2
495:
1.189 brouard 496: Revision 1.188 2015/04/30 08:27:53 brouard
497: *** empty log message ***
498:
1.188 brouard 499: Revision 1.187 2015/04/29 09:11:15 brouard
500: *** empty log message ***
501:
1.187 brouard 502: Revision 1.186 2015/04/23 12:01:52 brouard
503: Summary: V1*age is working now, version 0.98q1
504:
505: Some codes had been disabled in order to simplify and Vn*age was
506: working in the optimization phase, ie, giving correct MLE parameters,
507: but, as usual, outputs were not correct and program core dumped.
508:
1.186 brouard 509: Revision 1.185 2015/03/11 13:26:42 brouard
510: Summary: Inclusion of compile and links command line for Intel Compiler
511:
1.185 brouard 512: Revision 1.184 2015/03/11 11:52:39 brouard
513: Summary: Back from Windows 8. Intel Compiler
514:
1.184 brouard 515: Revision 1.183 2015/03/10 20:34:32 brouard
516: Summary: 0.98q0, trying with directest, mnbrak fixed
517:
518: We use directest instead of original Powell test; probably no
519: incidence on the results, but better justifications;
520: We fixed Numerical Recipes mnbrak routine which was wrong and gave
521: wrong results.
522:
1.183 brouard 523: Revision 1.182 2015/02/12 08:19:57 brouard
524: Summary: Trying to keep directest which seems simpler and more general
525: Author: Nicolas Brouard
526:
1.182 brouard 527: Revision 1.181 2015/02/11 23:22:24 brouard
528: Summary: Comments on Powell added
529:
530: Author:
531:
1.181 brouard 532: Revision 1.180 2015/02/11 17:33:45 brouard
533: Summary: Finishing move from main to function (hpijx and prevalence_limit)
534:
1.180 brouard 535: Revision 1.179 2015/01/04 09:57:06 brouard
536: Summary: back to OS/X
537:
1.179 brouard 538: Revision 1.178 2015/01/04 09:35:48 brouard
539: *** empty log message ***
540:
1.178 brouard 541: Revision 1.177 2015/01/03 18:40:56 brouard
542: Summary: Still testing ilc32 on OSX
543:
1.177 brouard 544: Revision 1.176 2015/01/03 16:45:04 brouard
545: *** empty log message ***
546:
1.176 brouard 547: Revision 1.175 2015/01/03 16:33:42 brouard
548: *** empty log message ***
549:
1.175 brouard 550: Revision 1.174 2015/01/03 16:15:49 brouard
551: Summary: Still in cross-compilation
552:
1.174 brouard 553: Revision 1.173 2015/01/03 12:06:26 brouard
554: Summary: trying to detect cross-compilation
555:
1.173 brouard 556: Revision 1.172 2014/12/27 12:07:47 brouard
557: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
558:
1.172 brouard 559: Revision 1.171 2014/12/23 13:26:59 brouard
560: Summary: Back from Visual C
561:
562: Still problem with utsname.h on Windows
563:
1.171 brouard 564: Revision 1.170 2014/12/23 11:17:12 brouard
565: Summary: Cleaning some \%% back to %%
566:
567: The escape was mandatory for a specific compiler (which one?), but too many warnings.
568:
1.170 brouard 569: Revision 1.169 2014/12/22 23:08:31 brouard
570: Summary: 0.98p
571:
572: Outputs some informations on compiler used, OS etc. Testing on different platforms.
573:
1.169 brouard 574: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 575: Summary: update
1.169 brouard 576:
1.168 brouard 577: Revision 1.167 2014/12/22 13:50:56 brouard
578: Summary: Testing uname and compiler version and if compiled 32 or 64
579:
580: Testing on Linux 64
581:
1.167 brouard 582: Revision 1.166 2014/12/22 11:40:47 brouard
583: *** empty log message ***
584:
1.166 brouard 585: Revision 1.165 2014/12/16 11:20:36 brouard
586: Summary: After compiling on Visual C
587:
588: * imach.c (Module): Merging 1.61 to 1.162
589:
1.165 brouard 590: Revision 1.164 2014/12/16 10:52:11 brouard
591: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
592:
593: * imach.c (Module): Merging 1.61 to 1.162
594:
1.164 brouard 595: Revision 1.163 2014/12/16 10:30:11 brouard
596: * imach.c (Module): Merging 1.61 to 1.162
597:
1.163 brouard 598: Revision 1.162 2014/09/25 11:43:39 brouard
599: Summary: temporary backup 0.99!
600:
1.162 brouard 601: Revision 1.1 2014/09/16 11:06:58 brouard
602: Summary: With some code (wrong) for nlopt
603:
604: Author:
605:
606: Revision 1.161 2014/09/15 20:41:41 brouard
607: Summary: Problem with macro SQR on Intel compiler
608:
1.161 brouard 609: Revision 1.160 2014/09/02 09:24:05 brouard
610: *** empty log message ***
611:
1.160 brouard 612: Revision 1.159 2014/09/01 10:34:10 brouard
613: Summary: WIN32
614: Author: Brouard
615:
1.159 brouard 616: Revision 1.158 2014/08/27 17:11:51 brouard
617: *** empty log message ***
618:
1.158 brouard 619: Revision 1.157 2014/08/27 16:26:55 brouard
620: Summary: Preparing windows Visual studio version
621: Author: Brouard
622:
623: In order to compile on Visual studio, time.h is now correct and time_t
624: and tm struct should be used. difftime should be used but sometimes I
625: just make the differences in raw time format (time(&now).
626: Trying to suppress #ifdef LINUX
627: Add xdg-open for __linux in order to open default browser.
628:
1.157 brouard 629: Revision 1.156 2014/08/25 20:10:10 brouard
630: *** empty log message ***
631:
1.156 brouard 632: Revision 1.155 2014/08/25 18:32:34 brouard
633: Summary: New compile, minor changes
634: Author: Brouard
635:
1.155 brouard 636: Revision 1.154 2014/06/20 17:32:08 brouard
637: Summary: Outputs now all graphs of convergence to period prevalence
638:
1.154 brouard 639: Revision 1.153 2014/06/20 16:45:46 brouard
640: Summary: If 3 live state, convergence to period prevalence on same graph
641: Author: Brouard
642:
1.153 brouard 643: Revision 1.152 2014/06/18 17:54:09 brouard
644: Summary: open browser, use gnuplot on same dir than imach if not found in the path
645:
1.152 brouard 646: Revision 1.151 2014/06/18 16:43:30 brouard
647: *** empty log message ***
648:
1.151 brouard 649: Revision 1.150 2014/06/18 16:42:35 brouard
650: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
651: Author: brouard
652:
1.150 brouard 653: Revision 1.149 2014/06/18 15:51:14 brouard
654: Summary: Some fixes in parameter files errors
655: Author: Nicolas Brouard
656:
1.149 brouard 657: Revision 1.148 2014/06/17 17:38:48 brouard
658: Summary: Nothing new
659: Author: Brouard
660:
661: Just a new packaging for OS/X version 0.98nS
662:
1.148 brouard 663: Revision 1.147 2014/06/16 10:33:11 brouard
664: *** empty log message ***
665:
1.147 brouard 666: Revision 1.146 2014/06/16 10:20:28 brouard
667: Summary: Merge
668: Author: Brouard
669:
670: Merge, before building revised version.
671:
1.146 brouard 672: Revision 1.145 2014/06/10 21:23:15 brouard
673: Summary: Debugging with valgrind
674: Author: Nicolas Brouard
675:
676: Lot of changes in order to output the results with some covariates
677: After the Edimburgh REVES conference 2014, it seems mandatory to
678: improve the code.
679: No more memory valgrind error but a lot has to be done in order to
680: continue the work of splitting the code into subroutines.
681: Also, decodemodel has been improved. Tricode is still not
682: optimal. nbcode should be improved. Documentation has been added in
683: the source code.
684:
1.144 brouard 685: Revision 1.143 2014/01/26 09:45:38 brouard
686: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
687:
688: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
689: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
690:
1.143 brouard 691: Revision 1.142 2014/01/26 03:57:36 brouard
692: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
693:
694: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
695:
1.142 brouard 696: Revision 1.141 2014/01/26 02:42:01 brouard
697: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
698:
1.141 brouard 699: Revision 1.140 2011/09/02 10:37:54 brouard
700: Summary: times.h is ok with mingw32 now.
701:
1.140 brouard 702: Revision 1.139 2010/06/14 07:50:17 brouard
703: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
704: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
705:
1.139 brouard 706: Revision 1.138 2010/04/30 18:19:40 brouard
707: *** empty log message ***
708:
1.138 brouard 709: Revision 1.137 2010/04/29 18:11:38 brouard
710: (Module): Checking covariates for more complex models
711: than V1+V2. A lot of change to be done. Unstable.
712:
1.137 brouard 713: Revision 1.136 2010/04/26 20:30:53 brouard
714: (Module): merging some libgsl code. Fixing computation
715: of likelione (using inter/intrapolation if mle = 0) in order to
716: get same likelihood as if mle=1.
717: Some cleaning of code and comments added.
718:
1.136 brouard 719: Revision 1.135 2009/10/29 15:33:14 brouard
720: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
721:
1.135 brouard 722: Revision 1.134 2009/10/29 13:18:53 brouard
723: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
724:
1.134 brouard 725: Revision 1.133 2009/07/06 10:21:25 brouard
726: just nforces
727:
1.133 brouard 728: Revision 1.132 2009/07/06 08:22:05 brouard
729: Many tings
730:
1.132 brouard 731: Revision 1.131 2009/06/20 16:22:47 brouard
732: Some dimensions resccaled
733:
1.131 brouard 734: Revision 1.130 2009/05/26 06:44:34 brouard
735: (Module): Max Covariate is now set to 20 instead of 8. A
736: lot of cleaning with variables initialized to 0. Trying to make
737: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
738:
1.130 brouard 739: Revision 1.129 2007/08/31 13:49:27 lievre
740: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
741:
1.129 lievre 742: Revision 1.128 2006/06/30 13:02:05 brouard
743: (Module): Clarifications on computing e.j
744:
1.128 brouard 745: Revision 1.127 2006/04/28 18:11:50 brouard
746: (Module): Yes the sum of survivors was wrong since
747: imach-114 because nhstepm was no more computed in the age
748: loop. Now we define nhstepma in the age loop.
749: (Module): In order to speed up (in case of numerous covariates) we
750: compute health expectancies (without variances) in a first step
751: and then all the health expectancies with variances or standard
752: deviation (needs data from the Hessian matrices) which slows the
753: computation.
754: In the future we should be able to stop the program is only health
755: expectancies and graph are needed without standard deviations.
756:
1.127 brouard 757: Revision 1.126 2006/04/28 17:23:28 brouard
758: (Module): Yes the sum of survivors was wrong since
759: imach-114 because nhstepm was no more computed in the age
760: loop. Now we define nhstepma in the age loop.
761: Version 0.98h
762:
1.126 brouard 763: Revision 1.125 2006/04/04 15:20:31 lievre
764: Errors in calculation of health expectancies. Age was not initialized.
765: Forecasting file added.
766:
767: Revision 1.124 2006/03/22 17:13:53 lievre
768: Parameters are printed with %lf instead of %f (more numbers after the comma).
769: The log-likelihood is printed in the log file
770:
771: Revision 1.123 2006/03/20 10:52:43 brouard
772: * imach.c (Module): <title> changed, corresponds to .htm file
773: name. <head> headers where missing.
774:
775: * imach.c (Module): Weights can have a decimal point as for
776: English (a comma might work with a correct LC_NUMERIC environment,
777: otherwise the weight is truncated).
778: Modification of warning when the covariates values are not 0 or
779: 1.
780: Version 0.98g
781:
782: Revision 1.122 2006/03/20 09:45:41 brouard
783: (Module): Weights can have a decimal point as for
784: English (a comma might work with a correct LC_NUMERIC environment,
785: otherwise the weight is truncated).
786: Modification of warning when the covariates values are not 0 or
787: 1.
788: Version 0.98g
789:
790: Revision 1.121 2006/03/16 17:45:01 lievre
791: * imach.c (Module): Comments concerning covariates added
792:
793: * imach.c (Module): refinements in the computation of lli if
794: status=-2 in order to have more reliable computation if stepm is
795: not 1 month. Version 0.98f
796:
797: Revision 1.120 2006/03/16 15:10:38 lievre
798: (Module): refinements in the computation of lli if
799: status=-2 in order to have more reliable computation if stepm is
800: not 1 month. Version 0.98f
801:
802: Revision 1.119 2006/03/15 17:42:26 brouard
803: (Module): Bug if status = -2, the loglikelihood was
804: computed as likelihood omitting the logarithm. Version O.98e
805:
806: Revision 1.118 2006/03/14 18:20:07 brouard
807: (Module): varevsij Comments added explaining the second
808: table of variances if popbased=1 .
809: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
810: (Module): Function pstamp added
811: (Module): Version 0.98d
812:
813: Revision 1.117 2006/03/14 17:16:22 brouard
814: (Module): varevsij Comments added explaining the second
815: table of variances if popbased=1 .
816: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
817: (Module): Function pstamp added
818: (Module): Version 0.98d
819:
820: Revision 1.116 2006/03/06 10:29:27 brouard
821: (Module): Variance-covariance wrong links and
822: varian-covariance of ej. is needed (Saito).
823:
824: Revision 1.115 2006/02/27 12:17:45 brouard
825: (Module): One freematrix added in mlikeli! 0.98c
826:
827: Revision 1.114 2006/02/26 12:57:58 brouard
828: (Module): Some improvements in processing parameter
829: filename with strsep.
830:
831: Revision 1.113 2006/02/24 14:20:24 brouard
832: (Module): Memory leaks checks with valgrind and:
833: datafile was not closed, some imatrix were not freed and on matrix
834: allocation too.
835:
836: Revision 1.112 2006/01/30 09:55:26 brouard
837: (Module): Back to gnuplot.exe instead of wgnuplot.exe
838:
839: Revision 1.111 2006/01/25 20:38:18 brouard
840: (Module): Lots of cleaning and bugs added (Gompertz)
841: (Module): Comments can be added in data file. Missing date values
842: can be a simple dot '.'.
843:
844: Revision 1.110 2006/01/25 00:51:50 brouard
845: (Module): Lots of cleaning and bugs added (Gompertz)
846:
847: Revision 1.109 2006/01/24 19:37:15 brouard
848: (Module): Comments (lines starting with a #) are allowed in data.
849:
850: Revision 1.108 2006/01/19 18:05:42 lievre
851: Gnuplot problem appeared...
852: To be fixed
853:
854: Revision 1.107 2006/01/19 16:20:37 brouard
855: Test existence of gnuplot in imach path
856:
857: Revision 1.106 2006/01/19 13:24:36 brouard
858: Some cleaning and links added in html output
859:
860: Revision 1.105 2006/01/05 20:23:19 lievre
861: *** empty log message ***
862:
863: Revision 1.104 2005/09/30 16:11:43 lievre
864: (Module): sump fixed, loop imx fixed, and simplifications.
865: (Module): If the status is missing at the last wave but we know
866: that the person is alive, then we can code his/her status as -2
867: (instead of missing=-1 in earlier versions) and his/her
868: contributions to the likelihood is 1 - Prob of dying from last
869: health status (= 1-p13= p11+p12 in the easiest case of somebody in
870: the healthy state at last known wave). Version is 0.98
871:
872: Revision 1.103 2005/09/30 15:54:49 lievre
873: (Module): sump fixed, loop imx fixed, and simplifications.
874:
875: Revision 1.102 2004/09/15 17:31:30 brouard
876: Add the possibility to read data file including tab characters.
877:
878: Revision 1.101 2004/09/15 10:38:38 brouard
879: Fix on curr_time
880:
881: Revision 1.100 2004/07/12 18:29:06 brouard
882: Add version for Mac OS X. Just define UNIX in Makefile
883:
884: Revision 1.99 2004/06/05 08:57:40 brouard
885: *** empty log message ***
886:
887: Revision 1.98 2004/05/16 15:05:56 brouard
888: New version 0.97 . First attempt to estimate force of mortality
889: directly from the data i.e. without the need of knowing the health
890: state at each age, but using a Gompertz model: log u =a + b*age .
891: This is the basic analysis of mortality and should be done before any
892: other analysis, in order to test if the mortality estimated from the
893: cross-longitudinal survey is different from the mortality estimated
894: from other sources like vital statistic data.
895:
896: The same imach parameter file can be used but the option for mle should be -3.
897:
1.324 brouard 898: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 899: former routines in order to include the new code within the former code.
900:
901: The output is very simple: only an estimate of the intercept and of
902: the slope with 95% confident intervals.
903:
904: Current limitations:
905: A) Even if you enter covariates, i.e. with the
906: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
907: B) There is no computation of Life Expectancy nor Life Table.
908:
909: Revision 1.97 2004/02/20 13:25:42 lievre
910: Version 0.96d. Population forecasting command line is (temporarily)
911: suppressed.
912:
913: Revision 1.96 2003/07/15 15:38:55 brouard
914: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
915: rewritten within the same printf. Workaround: many printfs.
916:
917: Revision 1.95 2003/07/08 07:54:34 brouard
918: * imach.c (Repository):
919: (Repository): Using imachwizard code to output a more meaningful covariance
920: matrix (cov(a12,c31) instead of numbers.
921:
922: Revision 1.94 2003/06/27 13:00:02 brouard
923: Just cleaning
924:
925: Revision 1.93 2003/06/25 16:33:55 brouard
926: (Module): On windows (cygwin) function asctime_r doesn't
927: exist so I changed back to asctime which exists.
928: (Module): Version 0.96b
929:
930: Revision 1.92 2003/06/25 16:30:45 brouard
931: (Module): On windows (cygwin) function asctime_r doesn't
932: exist so I changed back to asctime which exists.
933:
934: Revision 1.91 2003/06/25 15:30:29 brouard
935: * imach.c (Repository): Duplicated warning errors corrected.
936: (Repository): Elapsed time after each iteration is now output. It
937: helps to forecast when convergence will be reached. Elapsed time
938: is stamped in powell. We created a new html file for the graphs
939: concerning matrix of covariance. It has extension -cov.htm.
940:
941: Revision 1.90 2003/06/24 12:34:15 brouard
942: (Module): Some bugs corrected for windows. Also, when
943: mle=-1 a template is output in file "or"mypar.txt with the design
944: of the covariance matrix to be input.
945:
946: Revision 1.89 2003/06/24 12:30:52 brouard
947: (Module): Some bugs corrected for windows. Also, when
948: mle=-1 a template is output in file "or"mypar.txt with the design
949: of the covariance matrix to be input.
950:
951: Revision 1.88 2003/06/23 17:54:56 brouard
952: * 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.
953:
954: Revision 1.87 2003/06/18 12:26:01 brouard
955: Version 0.96
956:
957: Revision 1.86 2003/06/17 20:04:08 brouard
958: (Module): Change position of html and gnuplot routines and added
959: routine fileappend.
960:
961: Revision 1.85 2003/06/17 13:12:43 brouard
962: * imach.c (Repository): Check when date of death was earlier that
963: current date of interview. It may happen when the death was just
964: prior to the death. In this case, dh was negative and likelihood
965: was wrong (infinity). We still send an "Error" but patch by
966: assuming that the date of death was just one stepm after the
967: interview.
968: (Repository): Because some people have very long ID (first column)
969: we changed int to long in num[] and we added a new lvector for
970: memory allocation. But we also truncated to 8 characters (left
971: truncation)
972: (Repository): No more line truncation errors.
973:
974: Revision 1.84 2003/06/13 21:44:43 brouard
975: * imach.c (Repository): Replace "freqsummary" at a correct
976: place. It differs from routine "prevalence" which may be called
977: many times. Probs is memory consuming and must be used with
978: parcimony.
979: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
980:
981: Revision 1.83 2003/06/10 13:39:11 lievre
982: *** empty log message ***
983:
984: Revision 1.82 2003/06/05 15:57:20 brouard
985: Add log in imach.c and fullversion number is now printed.
986:
987: */
988: /*
989: Interpolated Markov Chain
990:
991: Short summary of the programme:
992:
1.227 brouard 993: This program computes Healthy Life Expectancies or State-specific
994: (if states aren't health statuses) Expectancies from
995: cross-longitudinal data. Cross-longitudinal data consist in:
996:
997: -1- a first survey ("cross") where individuals from different ages
998: are interviewed on their health status or degree of disability (in
999: the case of a health survey which is our main interest)
1000:
1001: -2- at least a second wave of interviews ("longitudinal") which
1002: measure each change (if any) in individual health status. Health
1003: expectancies are computed from the time spent in each health state
1004: according to a model. More health states you consider, more time is
1005: necessary to reach the Maximum Likelihood of the parameters involved
1006: in the model. The simplest model is the multinomial logistic model
1007: where pij is the probability to be observed in state j at the second
1008: wave conditional to be observed in state i at the first
1009: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1010: etc , where 'age' is age and 'sex' is a covariate. If you want to
1011: have a more complex model than "constant and age", you should modify
1012: the program where the markup *Covariates have to be included here
1013: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1014: convergence.
1015:
1016: The advantage of this computer programme, compared to a simple
1017: multinomial logistic model, is clear when the delay between waves is not
1018: identical for each individual. Also, if a individual missed an
1019: intermediate interview, the information is lost, but taken into
1020: account using an interpolation or extrapolation.
1021:
1022: hPijx is the probability to be observed in state i at age x+h
1023: conditional to the observed state i at age x. The delay 'h' can be
1024: split into an exact number (nh*stepm) of unobserved intermediate
1025: states. This elementary transition (by month, quarter,
1026: semester or year) is modelled as a multinomial logistic. The hPx
1027: matrix is simply the matrix product of nh*stepm elementary matrices
1028: and the contribution of each individual to the likelihood is simply
1029: hPijx.
1030:
1031: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1032: of the life expectancies. It also computes the period (stable) prevalence.
1033:
1034: Back prevalence and projections:
1.227 brouard 1035:
1036: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1037: double agemaxpar, double ftolpl, int *ncvyearp, double
1038: dateprev1,double dateprev2, int firstpass, int lastpass, int
1039: mobilavproj)
1040:
1041: Computes the back prevalence limit for any combination of
1042: covariate values k at any age between ageminpar and agemaxpar and
1043: returns it in **bprlim. In the loops,
1044:
1045: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1046: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1047:
1048: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1049: Computes for any combination of covariates k and any age between bage and fage
1050: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1051: oldm=oldms;savm=savms;
1.227 brouard 1052:
1.267 brouard 1053: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1054: Computes the transition matrix starting at age 'age' over
1055: 'nhstepm*hstepm*stepm' months (i.e. until
1056: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1057: nhstepm*hstepm matrices.
1058:
1059: Returns p3mat[i][j][h] after calling
1060: p3mat[i][j][h]=matprod2(newm,
1061: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1062: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1063: oldm);
1.226 brouard 1064:
1065: Important routines
1066:
1067: - func (or funcone), computes logit (pij) distinguishing
1068: o fixed variables (single or product dummies or quantitative);
1069: o varying variables by:
1070: (1) wave (single, product dummies, quantitative),
1071: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1072: % fixed dummy (treated) or quantitative (not done because time-consuming);
1073: % varying dummy (not done) or quantitative (not done);
1074: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1075: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1076: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1077: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1078: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1079:
1.226 brouard 1080:
1081:
1.324 brouard 1082: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1083: Institut national d'études démographiques, Paris.
1.126 brouard 1084: This software have been partly granted by Euro-REVES, a concerted action
1085: from the European Union.
1086: It is copyrighted identically to a GNU software product, ie programme and
1087: software can be distributed freely for non commercial use. Latest version
1088: can be accessed at http://euroreves.ined.fr/imach .
1089:
1090: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1091: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1092:
1093: **********************************************************************/
1094: /*
1095: main
1096: read parameterfile
1097: read datafile
1098: concatwav
1099: freqsummary
1100: if (mle >= 1)
1101: mlikeli
1102: print results files
1103: if mle==1
1104: computes hessian
1105: read end of parameter file: agemin, agemax, bage, fage, estepm
1106: begin-prev-date,...
1107: open gnuplot file
1108: open html file
1.145 brouard 1109: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1110: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1111: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1112: freexexit2 possible for memory heap.
1113:
1114: h Pij x | pij_nom ficrestpij
1115: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1116: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1117: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1118:
1119: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1120: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1121: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1122: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1123: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1124:
1.126 brouard 1125: forecasting if prevfcast==1 prevforecast call prevalence()
1126: health expectancies
1127: Variance-covariance of DFLE
1128: prevalence()
1129: movingaverage()
1130: varevsij()
1131: if popbased==1 varevsij(,popbased)
1132: total life expectancies
1133: Variance of period (stable) prevalence
1134: end
1135: */
1136:
1.187 brouard 1137: /* #define DEBUG */
1138: /* #define DEBUGBRENT */
1.203 brouard 1139: /* #define DEBUGLINMIN */
1140: /* #define DEBUGHESS */
1141: #define DEBUGHESSIJ
1.224 brouard 1142: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1143: #define POWELL /* Instead of NLOPT */
1.224 brouard 1144: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1145: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1146: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1147: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1148:
1149: #include <math.h>
1150: #include <stdio.h>
1151: #include <stdlib.h>
1152: #include <string.h>
1.226 brouard 1153: #include <ctype.h>
1.159 brouard 1154:
1155: #ifdef _WIN32
1156: #include <io.h>
1.172 brouard 1157: #include <windows.h>
1158: #include <tchar.h>
1.159 brouard 1159: #else
1.126 brouard 1160: #include <unistd.h>
1.159 brouard 1161: #endif
1.126 brouard 1162:
1163: #include <limits.h>
1164: #include <sys/types.h>
1.171 brouard 1165:
1166: #if defined(__GNUC__)
1167: #include <sys/utsname.h> /* Doesn't work on Windows */
1168: #endif
1169:
1.126 brouard 1170: #include <sys/stat.h>
1171: #include <errno.h>
1.159 brouard 1172: /* extern int errno; */
1.126 brouard 1173:
1.157 brouard 1174: /* #ifdef LINUX */
1175: /* #include <time.h> */
1176: /* #include "timeval.h" */
1177: /* #else */
1178: /* #include <sys/time.h> */
1179: /* #endif */
1180:
1.126 brouard 1181: #include <time.h>
1182:
1.136 brouard 1183: #ifdef GSL
1184: #include <gsl/gsl_errno.h>
1185: #include <gsl/gsl_multimin.h>
1186: #endif
1187:
1.167 brouard 1188:
1.162 brouard 1189: #ifdef NLOPT
1190: #include <nlopt.h>
1191: typedef struct {
1192: double (* function)(double [] );
1193: } myfunc_data ;
1194: #endif
1195:
1.126 brouard 1196: /* #include <libintl.h> */
1197: /* #define _(String) gettext (String) */
1198:
1.251 brouard 1199: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1200:
1201: #define GNUPLOTPROGRAM "gnuplot"
1202: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1203: #define FILENAMELENGTH 256
1.126 brouard 1204:
1205: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1206: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1207:
1.144 brouard 1208: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1209: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1210:
1211: #define NINTERVMAX 8
1.144 brouard 1212: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1213: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1214: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1215: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1216: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1217: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1218: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1219: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1220: /* #define AGESUP 130 */
1.288 brouard 1221: /* #define AGESUP 150 */
1222: #define AGESUP 200
1.268 brouard 1223: #define AGEINF 0
1.218 brouard 1224: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1225: #define AGEBASE 40
1.194 brouard 1226: #define AGEOVERFLOW 1.e20
1.164 brouard 1227: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1228: #ifdef _WIN32
1229: #define DIRSEPARATOR '\\'
1230: #define CHARSEPARATOR "\\"
1231: #define ODIRSEPARATOR '/'
1232: #else
1.126 brouard 1233: #define DIRSEPARATOR '/'
1234: #define CHARSEPARATOR "/"
1235: #define ODIRSEPARATOR '\\'
1236: #endif
1237:
1.331 ! brouard 1238: /* $Id: imach.c,v 1.330 2022/08/06 07:18:25 brouard Exp $ */
1.126 brouard 1239: /* $State: Exp $ */
1.196 brouard 1240: #include "version.h"
1241: char version[]=__IMACH_VERSION__;
1.323 brouard 1242: char copyright[]="July 2022,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, Nihon University 2021-202, INED 2000-2022";
1.331 ! brouard 1243: char fullversion[]="$Revision: 1.330 $ $Date: 2022/08/06 07:18:25 $";
1.126 brouard 1244: char strstart[80];
1245: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1246: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1247: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1248: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1249: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1250: int cptcovn=0; /**< cptcovn decodemodel: number of covariates k of the models excluding age*products =6 and age*age */
1251: int cptcovt=0; /**< cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
1252: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1.225 brouard 1253: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1254: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1255: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.330 brouard 1256: 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 1257: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1258: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1259: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1260: int nsd=0; /**< Total number of single dummy variables (output) */
1261: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1262: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1263: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1264: int ntveff=0; /**< ntveff number of effective time varying variables */
1265: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1266: int cptcov=0; /* Working variable */
1.290 brouard 1267: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1268: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1269: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1270: int nlstate=2; /* Number of live states */
1271: int ndeath=1; /* Number of dead states */
1.130 brouard 1272: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1273: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1274: int popbased=0;
1275:
1276: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1277: int maxwav=0; /* Maxim number of waves */
1278: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1279: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1280: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1281: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1282: int mle=1, weightopt=0;
1.126 brouard 1283: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1284: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1285: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1286: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1287: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1288: int selected(int kvar); /* Is covariate kvar selected for printing results */
1289:
1.130 brouard 1290: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1291: double **matprod2(); /* test */
1.126 brouard 1292: double **oldm, **newm, **savm; /* Working pointers to matrices */
1293: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1294: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1295:
1.136 brouard 1296: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1297: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1298: FILE *ficlog, *ficrespow;
1.130 brouard 1299: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1300: double fretone; /* Only one call to likelihood */
1.130 brouard 1301: long ipmx=0; /* Number of contributions */
1.126 brouard 1302: double sw; /* Sum of weights */
1303: char filerespow[FILENAMELENGTH];
1304: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1305: FILE *ficresilk;
1306: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1307: FILE *ficresprobmorprev;
1308: FILE *fichtm, *fichtmcov; /* Html File */
1309: FILE *ficreseij;
1310: char filerese[FILENAMELENGTH];
1311: FILE *ficresstdeij;
1312: char fileresstde[FILENAMELENGTH];
1313: FILE *ficrescveij;
1314: char filerescve[FILENAMELENGTH];
1315: FILE *ficresvij;
1316: char fileresv[FILENAMELENGTH];
1.269 brouard 1317:
1.126 brouard 1318: char title[MAXLINE];
1.234 brouard 1319: char model[MAXLINE]; /**< The model line */
1.217 brouard 1320: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1321: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1322: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1323: char command[FILENAMELENGTH];
1324: int outcmd=0;
1325:
1.217 brouard 1326: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1327: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1328: char filelog[FILENAMELENGTH]; /* Log file */
1329: char filerest[FILENAMELENGTH];
1330: char fileregp[FILENAMELENGTH];
1331: char popfile[FILENAMELENGTH];
1332:
1333: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1334:
1.157 brouard 1335: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1336: /* struct timezone tzp; */
1337: /* extern int gettimeofday(); */
1338: struct tm tml, *gmtime(), *localtime();
1339:
1340: extern time_t time();
1341:
1342: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1343: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1344: struct tm tm;
1345:
1.126 brouard 1346: char strcurr[80], strfor[80];
1347:
1348: char *endptr;
1349: long lval;
1350: double dval;
1351:
1352: #define NR_END 1
1353: #define FREE_ARG char*
1354: #define FTOL 1.0e-10
1355:
1356: #define NRANSI
1.240 brouard 1357: #define ITMAX 200
1358: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1359:
1360: #define TOL 2.0e-4
1361:
1362: #define CGOLD 0.3819660
1363: #define ZEPS 1.0e-10
1364: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1365:
1366: #define GOLD 1.618034
1367: #define GLIMIT 100.0
1368: #define TINY 1.0e-20
1369:
1370: static double maxarg1,maxarg2;
1371: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1372: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1373:
1374: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1375: #define rint(a) floor(a+0.5)
1.166 brouard 1376: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1377: #define mytinydouble 1.0e-16
1.166 brouard 1378: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1379: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1380: /* static double dsqrarg; */
1381: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1382: static double sqrarg;
1383: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1384: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1385: int agegomp= AGEGOMP;
1386:
1387: int imx;
1388: int stepm=1;
1389: /* Stepm, step in month: minimum step interpolation*/
1390:
1391: int estepm;
1392: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1393:
1394: int m,nb;
1395: long *num;
1.197 brouard 1396: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1397: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1398: covariate for which somebody answered excluding
1399: undefined. Usually 2: 0 and 1. */
1400: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1401: covariate for which somebody answered including
1402: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1403: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1404: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1405: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1406: double *ageexmed,*agecens;
1407: double dateintmean=0;
1.296 brouard 1408: double anprojd, mprojd, jprojd; /* For eventual projections */
1409: double anprojf, mprojf, jprojf;
1.126 brouard 1410:
1.296 brouard 1411: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1412: double anbackf, mbackf, jbackf;
1413: double jintmean,mintmean,aintmean;
1.126 brouard 1414: double *weight;
1415: int **s; /* Status */
1.141 brouard 1416: double *agedc;
1.145 brouard 1417: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1418: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1419: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1420: double **coqvar; /* Fixed quantitative covariate nqv */
1421: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1422: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1423: double idx;
1424: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1425: /* Some documentation */
1426: /* Design original data
1427: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1428: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1429: * ntv=3 nqtv=1
1.330 brouard 1430: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1431: * For time varying covariate, quanti or dummies
1432: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1433: * cotvar[wav][ntv+iv][i]= [3+(1 to nqtv)][i]=(V12) quanti
1434: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1435: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1436: * covar[k,i], value of kth fixed covariate dummy or quanti :
1437: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1438: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1439: * k= 1 2 3 4 5 6 7 8 9 10 11
1440: */
1441: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1442: /* 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
1443: # States 1=Coresidence, 2 Living alone, 3 Institution
1444: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1445: */
1.319 brouard 1446: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1447: /* k 1 2 3 4 5 6 7 8 9 */
1448: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 *//*0 for simple covariate (dummy, quantitative,*/
1449: /* fixed or varying), 1 for age product, 2 for*/
1450: /* product */
1451: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1452: /*(single or product without age), 2 dummy*/
1453: /* with age product, 3 quant with age product*/
1454: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1455: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1.330 brouard 1456: /*TnsdVar[Tvar] 1 2 3 */
1.319 brouard 1457: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1458: /*TvarsDind[k] 2 3 9 */ /* position K of single dummy cova */
1459: /* nsq 1 2 */ /* Counting single quantit tv */
1460: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1461: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1462: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1463: /* cptcovage 1 2 */ /* Counting cov*age in the model equation */
1464: /* Tage[cptcovage]=k 5 8 */ /* Position in the model of ith cov*age */
1465: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1466: /* 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 1467: /* 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 1468: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1469: /* Type */
1470: /* V 1 2 3 4 5 */
1471: /* F F V V V */
1472: /* D Q D D Q */
1473: /* */
1474: int *TvarsD;
1.330 brouard 1475: int *TnsdVar;
1.234 brouard 1476: int *TvarsDind;
1477: int *TvarsQ;
1478: int *TvarsQind;
1479:
1.318 brouard 1480: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1481: int nresult=0;
1.258 brouard 1482: int parameterline=0; /* # of the parameter (type) line */
1.318 brouard 1483: int TKresult[MAXRESULTLINESPONE];
1.330 brouard 1484: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
1.318 brouard 1485: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */
1486: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */
1.330 brouard 1487: int TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable or quanti value (output) */
1.318 brouard 1488: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For dummy variable , variable # (output) */
1489: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1490: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1491: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , variable # (output) */
1492:
1493: /* 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
1494: # States 1=Coresidence, 2 Living alone, 3 Institution
1495: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1496: */
1.234 brouard 1497: /* 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 1498: 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 */
1499: 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 */
1500: 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 */
1501: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1502: 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 */
1503: 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 1504: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1505: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1506: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1507: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1508: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1509: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1510: 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 */
1511: 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 */
1512:
1.230 brouard 1513: int *Tvarsel; /**< Selected covariates for output */
1514: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1515: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1516: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1517: 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 1518: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1519: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1520: int *Tage;
1.227 brouard 1521: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1522: 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 1523: 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*/
1524: 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 1525: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1526: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1527: int **Tvard;
1.330 brouard 1528: int **Tvardk;
1.227 brouard 1529: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1530: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1531: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1532: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1533: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1534: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1535: double *lsurv, *lpop, *tpop;
1536:
1.231 brouard 1537: #define FD 1; /* Fixed dummy covariate */
1538: #define FQ 2; /* Fixed quantitative covariate */
1539: #define FP 3; /* Fixed product covariate */
1540: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1541: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1542: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1543: #define VD 10; /* Varying dummy covariate */
1544: #define VQ 11; /* Varying quantitative covariate */
1545: #define VP 12; /* Varying product covariate */
1546: #define VPDD 13; /* Varying product dummy*dummy covariate */
1547: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1548: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1549: #define APFD 16; /* Age product * fixed dummy covariate */
1550: #define APFQ 17; /* Age product * fixed quantitative covariate */
1551: #define APVD 18; /* Age product * varying dummy covariate */
1552: #define APVQ 19; /* Age product * varying quantitative covariate */
1553:
1554: #define FTYPE 1; /* Fixed covariate */
1555: #define VTYPE 2; /* Varying covariate (loop in wave) */
1556: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1557:
1558: struct kmodel{
1559: int maintype; /* main type */
1560: int subtype; /* subtype */
1561: };
1562: struct kmodel modell[NCOVMAX];
1563:
1.143 brouard 1564: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1565: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1566:
1567: /**************** split *************************/
1568: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1569: {
1570: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1571: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1572: */
1573: char *ss; /* pointer */
1.186 brouard 1574: int l1=0, l2=0; /* length counters */
1.126 brouard 1575:
1576: l1 = strlen(path ); /* length of path */
1577: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1578: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1579: if ( ss == NULL ) { /* no directory, so determine current directory */
1580: strcpy( name, path ); /* we got the fullname name because no directory */
1581: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1582: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1583: /* get current working directory */
1584: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1585: #ifdef WIN32
1586: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1587: #else
1588: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1589: #endif
1.126 brouard 1590: return( GLOCK_ERROR_GETCWD );
1591: }
1592: /* got dirc from getcwd*/
1593: printf(" DIRC = %s \n",dirc);
1.205 brouard 1594: } else { /* strip directory from path */
1.126 brouard 1595: ss++; /* after this, the filename */
1596: l2 = strlen( ss ); /* length of filename */
1597: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1598: strcpy( name, ss ); /* save file name */
1599: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1600: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1601: printf(" DIRC2 = %s \n",dirc);
1602: }
1603: /* We add a separator at the end of dirc if not exists */
1604: l1 = strlen( dirc ); /* length of directory */
1605: if( dirc[l1-1] != DIRSEPARATOR ){
1606: dirc[l1] = DIRSEPARATOR;
1607: dirc[l1+1] = 0;
1608: printf(" DIRC3 = %s \n",dirc);
1609: }
1610: ss = strrchr( name, '.' ); /* find last / */
1611: if (ss >0){
1612: ss++;
1613: strcpy(ext,ss); /* save extension */
1614: l1= strlen( name);
1615: l2= strlen(ss)+1;
1616: strncpy( finame, name, l1-l2);
1617: finame[l1-l2]= 0;
1618: }
1619:
1620: return( 0 ); /* we're done */
1621: }
1622:
1623:
1624: /******************************************/
1625:
1626: void replace_back_to_slash(char *s, char*t)
1627: {
1628: int i;
1629: int lg=0;
1630: i=0;
1631: lg=strlen(t);
1632: for(i=0; i<= lg; i++) {
1633: (s[i] = t[i]);
1634: if (t[i]== '\\') s[i]='/';
1635: }
1636: }
1637:
1.132 brouard 1638: char *trimbb(char *out, char *in)
1.137 brouard 1639: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1640: char *s;
1641: s=out;
1642: while (*in != '\0'){
1.137 brouard 1643: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1644: in++;
1645: }
1646: *out++ = *in++;
1647: }
1648: *out='\0';
1649: return s;
1650: }
1651:
1.187 brouard 1652: /* char *substrchaine(char *out, char *in, char *chain) */
1653: /* { */
1654: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1655: /* char *s, *t; */
1656: /* t=in;s=out; */
1657: /* while ((*in != *chain) && (*in != '\0')){ */
1658: /* *out++ = *in++; */
1659: /* } */
1660:
1661: /* /\* *in matches *chain *\/ */
1662: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1663: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1664: /* } */
1665: /* in--; chain--; */
1666: /* while ( (*in != '\0')){ */
1667: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1668: /* *out++ = *in++; */
1669: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1670: /* } */
1671: /* *out='\0'; */
1672: /* out=s; */
1673: /* return out; */
1674: /* } */
1675: char *substrchaine(char *out, char *in, char *chain)
1676: {
1677: /* Substract chain 'chain' from 'in', return and output 'out' */
1678: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1679:
1680: char *strloc;
1681:
1682: strcpy (out, in);
1683: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1684: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1685: if(strloc != NULL){
1686: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1687: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1688: /* strcpy (strloc, strloc +strlen(chain));*/
1689: }
1690: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1691: return out;
1692: }
1693:
1694:
1.145 brouard 1695: char *cutl(char *blocc, char *alocc, char *in, char occ)
1696: {
1.187 brouard 1697: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1698: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1699: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1700: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1701: */
1.160 brouard 1702: char *s, *t;
1.145 brouard 1703: t=in;s=in;
1704: while ((*in != occ) && (*in != '\0')){
1705: *alocc++ = *in++;
1706: }
1707: if( *in == occ){
1708: *(alocc)='\0';
1709: s=++in;
1710: }
1711:
1712: if (s == t) {/* occ not found */
1713: *(alocc-(in-s))='\0';
1714: in=s;
1715: }
1716: while ( *in != '\0'){
1717: *blocc++ = *in++;
1718: }
1719:
1720: *blocc='\0';
1721: return t;
1722: }
1.137 brouard 1723: char *cutv(char *blocc, char *alocc, char *in, char occ)
1724: {
1.187 brouard 1725: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1726: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1727: gives blocc="abcdef2ghi" and alocc="j".
1728: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1729: */
1730: char *s, *t;
1731: t=in;s=in;
1732: while (*in != '\0'){
1733: while( *in == occ){
1734: *blocc++ = *in++;
1735: s=in;
1736: }
1737: *blocc++ = *in++;
1738: }
1739: if (s == t) /* occ not found */
1740: *(blocc-(in-s))='\0';
1741: else
1742: *(blocc-(in-s)-1)='\0';
1743: in=s;
1744: while ( *in != '\0'){
1745: *alocc++ = *in++;
1746: }
1747:
1748: *alocc='\0';
1749: return s;
1750: }
1751:
1.126 brouard 1752: int nbocc(char *s, char occ)
1753: {
1754: int i,j=0;
1755: int lg=20;
1756: i=0;
1757: lg=strlen(s);
1758: for(i=0; i<= lg; i++) {
1.234 brouard 1759: if (s[i] == occ ) j++;
1.126 brouard 1760: }
1761: return j;
1762: }
1763:
1.137 brouard 1764: /* void cutv(char *u,char *v, char*t, char occ) */
1765: /* { */
1766: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1767: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1768: /* gives u="abcdef2ghi" and v="j" *\/ */
1769: /* int i,lg,j,p=0; */
1770: /* i=0; */
1771: /* lg=strlen(t); */
1772: /* for(j=0; j<=lg-1; j++) { */
1773: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1774: /* } */
1.126 brouard 1775:
1.137 brouard 1776: /* for(j=0; j<p; j++) { */
1777: /* (u[j] = t[j]); */
1778: /* } */
1779: /* u[p]='\0'; */
1.126 brouard 1780:
1.137 brouard 1781: /* for(j=0; j<= lg; j++) { */
1782: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1783: /* } */
1784: /* } */
1.126 brouard 1785:
1.160 brouard 1786: #ifdef _WIN32
1787: char * strsep(char **pp, const char *delim)
1788: {
1789: char *p, *q;
1790:
1791: if ((p = *pp) == NULL)
1792: return 0;
1793: if ((q = strpbrk (p, delim)) != NULL)
1794: {
1795: *pp = q + 1;
1796: *q = '\0';
1797: }
1798: else
1799: *pp = 0;
1800: return p;
1801: }
1802: #endif
1803:
1.126 brouard 1804: /********************** nrerror ********************/
1805:
1806: void nrerror(char error_text[])
1807: {
1808: fprintf(stderr,"ERREUR ...\n");
1809: fprintf(stderr,"%s\n",error_text);
1810: exit(EXIT_FAILURE);
1811: }
1812: /*********************** vector *******************/
1813: double *vector(int nl, int nh)
1814: {
1815: double *v;
1816: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1817: if (!v) nrerror("allocation failure in vector");
1818: return v-nl+NR_END;
1819: }
1820:
1821: /************************ free vector ******************/
1822: void free_vector(double*v, int nl, int nh)
1823: {
1824: free((FREE_ARG)(v+nl-NR_END));
1825: }
1826:
1827: /************************ivector *******************************/
1828: int *ivector(long nl,long nh)
1829: {
1830: int *v;
1831: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1832: if (!v) nrerror("allocation failure in ivector");
1833: return v-nl+NR_END;
1834: }
1835:
1836: /******************free ivector **************************/
1837: void free_ivector(int *v, long nl, long nh)
1838: {
1839: free((FREE_ARG)(v+nl-NR_END));
1840: }
1841:
1842: /************************lvector *******************************/
1843: long *lvector(long nl,long nh)
1844: {
1845: long *v;
1846: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1847: if (!v) nrerror("allocation failure in ivector");
1848: return v-nl+NR_END;
1849: }
1850:
1851: /******************free lvector **************************/
1852: void free_lvector(long *v, long nl, long nh)
1853: {
1854: free((FREE_ARG)(v+nl-NR_END));
1855: }
1856:
1857: /******************* imatrix *******************************/
1858: int **imatrix(long nrl, long nrh, long ncl, long nch)
1859: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1860: {
1861: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1862: int **m;
1863:
1864: /* allocate pointers to rows */
1865: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1866: if (!m) nrerror("allocation failure 1 in matrix()");
1867: m += NR_END;
1868: m -= nrl;
1869:
1870:
1871: /* allocate rows and set pointers to them */
1872: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1873: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1874: m[nrl] += NR_END;
1875: m[nrl] -= ncl;
1876:
1877: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1878:
1879: /* return pointer to array of pointers to rows */
1880: return m;
1881: }
1882:
1883: /****************** free_imatrix *************************/
1884: void free_imatrix(m,nrl,nrh,ncl,nch)
1885: int **m;
1886: long nch,ncl,nrh,nrl;
1887: /* free an int matrix allocated by imatrix() */
1888: {
1889: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1890: free((FREE_ARG) (m+nrl-NR_END));
1891: }
1892:
1893: /******************* matrix *******************************/
1894: double **matrix(long nrl, long nrh, long ncl, long nch)
1895: {
1896: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1897: double **m;
1898:
1899: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1900: if (!m) nrerror("allocation failure 1 in matrix()");
1901: m += NR_END;
1902: m -= nrl;
1903:
1904: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1905: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1906: m[nrl] += NR_END;
1907: m[nrl] -= ncl;
1908:
1909: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1910: return m;
1.145 brouard 1911: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1912: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1913: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1914: */
1915: }
1916:
1917: /*************************free matrix ************************/
1918: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1919: {
1920: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1921: free((FREE_ARG)(m+nrl-NR_END));
1922: }
1923:
1924: /******************* ma3x *******************************/
1925: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1926: {
1927: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1928: double ***m;
1929:
1930: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1931: if (!m) nrerror("allocation failure 1 in matrix()");
1932: m += NR_END;
1933: m -= nrl;
1934:
1935: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1936: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1937: m[nrl] += NR_END;
1938: m[nrl] -= ncl;
1939:
1940: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1941:
1942: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1943: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1944: m[nrl][ncl] += NR_END;
1945: m[nrl][ncl] -= nll;
1946: for (j=ncl+1; j<=nch; j++)
1947: m[nrl][j]=m[nrl][j-1]+nlay;
1948:
1949: for (i=nrl+1; i<=nrh; i++) {
1950: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1951: for (j=ncl+1; j<=nch; j++)
1952: m[i][j]=m[i][j-1]+nlay;
1953: }
1954: return m;
1955: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1956: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1957: */
1958: }
1959:
1960: /*************************free ma3x ************************/
1961: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1962: {
1963: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1964: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1965: free((FREE_ARG)(m+nrl-NR_END));
1966: }
1967:
1968: /*************** function subdirf ***********/
1969: char *subdirf(char fileres[])
1970: {
1971: /* Caution optionfilefiname is hidden */
1972: strcpy(tmpout,optionfilefiname);
1973: strcat(tmpout,"/"); /* Add to the right */
1974: strcat(tmpout,fileres);
1975: return tmpout;
1976: }
1977:
1978: /*************** function subdirf2 ***********/
1979: char *subdirf2(char fileres[], char *preop)
1980: {
1.314 brouard 1981: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
1982: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 1983: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 1984: /* Caution optionfilefiname is hidden */
1985: strcpy(tmpout,optionfilefiname);
1986: strcat(tmpout,"/");
1987: strcat(tmpout,preop);
1988: strcat(tmpout,fileres);
1989: return tmpout;
1990: }
1991:
1992: /*************** function subdirf3 ***********/
1993: char *subdirf3(char fileres[], char *preop, char *preop2)
1994: {
1995:
1996: /* Caution optionfilefiname is hidden */
1997: strcpy(tmpout,optionfilefiname);
1998: strcat(tmpout,"/");
1999: strcat(tmpout,preop);
2000: strcat(tmpout,preop2);
2001: strcat(tmpout,fileres);
2002: return tmpout;
2003: }
1.213 brouard 2004:
2005: /*************** function subdirfext ***********/
2006: char *subdirfext(char fileres[], char *preop, char *postop)
2007: {
2008:
2009: strcpy(tmpout,preop);
2010: strcat(tmpout,fileres);
2011: strcat(tmpout,postop);
2012: return tmpout;
2013: }
1.126 brouard 2014:
1.213 brouard 2015: /*************** function subdirfext3 ***********/
2016: char *subdirfext3(char fileres[], char *preop, char *postop)
2017: {
2018:
2019: /* Caution optionfilefiname is hidden */
2020: strcpy(tmpout,optionfilefiname);
2021: strcat(tmpout,"/");
2022: strcat(tmpout,preop);
2023: strcat(tmpout,fileres);
2024: strcat(tmpout,postop);
2025: return tmpout;
2026: }
2027:
1.162 brouard 2028: char *asc_diff_time(long time_sec, char ascdiff[])
2029: {
2030: long sec_left, days, hours, minutes;
2031: days = (time_sec) / (60*60*24);
2032: sec_left = (time_sec) % (60*60*24);
2033: hours = (sec_left) / (60*60) ;
2034: sec_left = (sec_left) %(60*60);
2035: minutes = (sec_left) /60;
2036: sec_left = (sec_left) % (60);
2037: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2038: return ascdiff;
2039: }
2040:
1.126 brouard 2041: /***************** f1dim *************************/
2042: extern int ncom;
2043: extern double *pcom,*xicom;
2044: extern double (*nrfunc)(double []);
2045:
2046: double f1dim(double x)
2047: {
2048: int j;
2049: double f;
2050: double *xt;
2051:
2052: xt=vector(1,ncom);
2053: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2054: f=(*nrfunc)(xt);
2055: free_vector(xt,1,ncom);
2056: return f;
2057: }
2058:
2059: /*****************brent *************************/
2060: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2061: {
2062: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2063: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2064: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2065: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2066: * returned function value.
2067: */
1.126 brouard 2068: int iter;
2069: double a,b,d,etemp;
1.159 brouard 2070: double fu=0,fv,fw,fx;
1.164 brouard 2071: double ftemp=0.;
1.126 brouard 2072: double p,q,r,tol1,tol2,u,v,w,x,xm;
2073: double e=0.0;
2074:
2075: a=(ax < cx ? ax : cx);
2076: b=(ax > cx ? ax : cx);
2077: x=w=v=bx;
2078: fw=fv=fx=(*f)(x);
2079: for (iter=1;iter<=ITMAX;iter++) {
2080: xm=0.5*(a+b);
2081: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2082: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2083: printf(".");fflush(stdout);
2084: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2085: #ifdef DEBUGBRENT
1.126 brouard 2086: 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);
2087: 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);
2088: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2089: #endif
2090: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2091: *xmin=x;
2092: return fx;
2093: }
2094: ftemp=fu;
2095: if (fabs(e) > tol1) {
2096: r=(x-w)*(fx-fv);
2097: q=(x-v)*(fx-fw);
2098: p=(x-v)*q-(x-w)*r;
2099: q=2.0*(q-r);
2100: if (q > 0.0) p = -p;
2101: q=fabs(q);
2102: etemp=e;
2103: e=d;
2104: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2105: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2106: else {
1.224 brouard 2107: d=p/q;
2108: u=x+d;
2109: if (u-a < tol2 || b-u < tol2)
2110: d=SIGN(tol1,xm-x);
1.126 brouard 2111: }
2112: } else {
2113: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2114: }
2115: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2116: fu=(*f)(u);
2117: if (fu <= fx) {
2118: if (u >= x) a=x; else b=x;
2119: SHFT(v,w,x,u)
1.183 brouard 2120: SHFT(fv,fw,fx,fu)
2121: } else {
2122: if (u < x) a=u; else b=u;
2123: if (fu <= fw || w == x) {
1.224 brouard 2124: v=w;
2125: w=u;
2126: fv=fw;
2127: fw=fu;
1.183 brouard 2128: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2129: v=u;
2130: fv=fu;
1.183 brouard 2131: }
2132: }
1.126 brouard 2133: }
2134: nrerror("Too many iterations in brent");
2135: *xmin=x;
2136: return fx;
2137: }
2138:
2139: /****************** mnbrak ***********************/
2140:
2141: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2142: double (*func)(double))
1.183 brouard 2143: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2144: the downhill direction (defined by the function as evaluated at the initial points) and returns
2145: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2146: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2147: */
1.126 brouard 2148: double ulim,u,r,q, dum;
2149: double fu;
1.187 brouard 2150:
2151: double scale=10.;
2152: int iterscale=0;
2153:
2154: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2155: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2156:
2157:
2158: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2159: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2160: /* *bx = *ax - (*ax - *bx)/scale; */
2161: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2162: /* } */
2163:
1.126 brouard 2164: if (*fb > *fa) {
2165: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2166: SHFT(dum,*fb,*fa,dum)
2167: }
1.126 brouard 2168: *cx=(*bx)+GOLD*(*bx-*ax);
2169: *fc=(*func)(*cx);
1.183 brouard 2170: #ifdef DEBUG
1.224 brouard 2171: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2172: 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 2173: #endif
1.224 brouard 2174: 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 2175: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2176: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2177: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2178: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2179: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2180: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2181: fu=(*func)(u);
1.163 brouard 2182: #ifdef DEBUG
2183: /* f(x)=A(x-u)**2+f(u) */
2184: double A, fparabu;
2185: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2186: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2187: 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);
2188: 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 2189: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2190: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2191: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2192: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2193: #endif
1.184 brouard 2194: #ifdef MNBRAKORIGINAL
1.183 brouard 2195: #else
1.191 brouard 2196: /* if (fu > *fc) { */
2197: /* #ifdef DEBUG */
2198: /* printf("mnbrak4 fu > fc \n"); */
2199: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2200: /* #endif */
2201: /* /\* 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 *\\/ *\/ */
2202: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2203: /* dum=u; /\* Shifting c and u *\/ */
2204: /* u = *cx; */
2205: /* *cx = dum; */
2206: /* dum = fu; */
2207: /* fu = *fc; */
2208: /* *fc =dum; */
2209: /* } else { /\* end *\/ */
2210: /* #ifdef DEBUG */
2211: /* printf("mnbrak3 fu < fc \n"); */
2212: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2213: /* #endif */
2214: /* dum=u; /\* Shifting c and u *\/ */
2215: /* u = *cx; */
2216: /* *cx = dum; */
2217: /* dum = fu; */
2218: /* fu = *fc; */
2219: /* *fc =dum; */
2220: /* } */
1.224 brouard 2221: #ifdef DEBUGMNBRAK
2222: double A, fparabu;
2223: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2224: fparabu= *fa - A*(*ax-u)*(*ax-u);
2225: 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);
2226: 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 2227: #endif
1.191 brouard 2228: dum=u; /* Shifting c and u */
2229: u = *cx;
2230: *cx = dum;
2231: dum = fu;
2232: fu = *fc;
2233: *fc =dum;
1.183 brouard 2234: #endif
1.162 brouard 2235: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2236: #ifdef DEBUG
1.224 brouard 2237: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2238: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2239: #endif
1.126 brouard 2240: fu=(*func)(u);
2241: if (fu < *fc) {
1.183 brouard 2242: #ifdef DEBUG
1.224 brouard 2243: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2244: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2245: #endif
2246: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2247: SHFT(*fb,*fc,fu,(*func)(u))
2248: #ifdef DEBUG
2249: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2250: #endif
2251: }
1.162 brouard 2252: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2253: #ifdef DEBUG
1.224 brouard 2254: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2255: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2256: #endif
1.126 brouard 2257: u=ulim;
2258: fu=(*func)(u);
1.183 brouard 2259: } else { /* u could be left to b (if r > q parabola has a maximum) */
2260: #ifdef DEBUG
1.224 brouard 2261: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2262: 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 2263: #endif
1.126 brouard 2264: u=(*cx)+GOLD*(*cx-*bx);
2265: fu=(*func)(u);
1.224 brouard 2266: #ifdef DEBUG
2267: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2268: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2269: #endif
1.183 brouard 2270: } /* end tests */
1.126 brouard 2271: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2272: SHFT(*fa,*fb,*fc,fu)
2273: #ifdef DEBUG
1.224 brouard 2274: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2275: 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 2276: #endif
2277: } /* 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 2278: }
2279:
2280: /*************** linmin ************************/
1.162 brouard 2281: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2282: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2283: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2284: the value of func at the returned location p . This is actually all accomplished by calling the
2285: routines mnbrak and brent .*/
1.126 brouard 2286: int ncom;
2287: double *pcom,*xicom;
2288: double (*nrfunc)(double []);
2289:
1.224 brouard 2290: #ifdef LINMINORIGINAL
1.126 brouard 2291: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2292: #else
2293: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2294: #endif
1.126 brouard 2295: {
2296: double brent(double ax, double bx, double cx,
2297: double (*f)(double), double tol, double *xmin);
2298: double f1dim(double x);
2299: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2300: double *fc, double (*func)(double));
2301: int j;
2302: double xx,xmin,bx,ax;
2303: double fx,fb,fa;
1.187 brouard 2304:
1.203 brouard 2305: #ifdef LINMINORIGINAL
2306: #else
2307: double scale=10., axs, xxs; /* Scale added for infinity */
2308: #endif
2309:
1.126 brouard 2310: ncom=n;
2311: pcom=vector(1,n);
2312: xicom=vector(1,n);
2313: nrfunc=func;
2314: for (j=1;j<=n;j++) {
2315: pcom[j]=p[j];
1.202 brouard 2316: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2317: }
1.187 brouard 2318:
1.203 brouard 2319: #ifdef LINMINORIGINAL
2320: xx=1.;
2321: #else
2322: axs=0.0;
2323: xxs=1.;
2324: do{
2325: xx= xxs;
2326: #endif
1.187 brouard 2327: ax=0.;
2328: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2329: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2330: /* 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)) */
2331: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2332: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2333: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2334: /* 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 2335: #ifdef LINMINORIGINAL
2336: #else
2337: if (fx != fx){
1.224 brouard 2338: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2339: printf("|");
2340: fprintf(ficlog,"|");
1.203 brouard 2341: #ifdef DEBUGLINMIN
1.224 brouard 2342: 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 2343: #endif
2344: }
1.224 brouard 2345: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2346: #endif
2347:
1.191 brouard 2348: #ifdef DEBUGLINMIN
2349: 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 2350: 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 2351: #endif
1.224 brouard 2352: #ifdef LINMINORIGINAL
2353: #else
1.317 brouard 2354: if(fb == fx){ /* Flat function in the direction */
2355: xmin=xx;
1.224 brouard 2356: *flat=1;
1.317 brouard 2357: }else{
1.224 brouard 2358: *flat=0;
2359: #endif
2360: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2361: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2362: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2363: /* fmin = f(p[j] + xmin * xi[j]) */
2364: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2365: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2366: #ifdef DEBUG
1.224 brouard 2367: 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);
2368: 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);
2369: #endif
2370: #ifdef LINMINORIGINAL
2371: #else
2372: }
1.126 brouard 2373: #endif
1.191 brouard 2374: #ifdef DEBUGLINMIN
2375: printf("linmin end ");
1.202 brouard 2376: fprintf(ficlog,"linmin end ");
1.191 brouard 2377: #endif
1.126 brouard 2378: for (j=1;j<=n;j++) {
1.203 brouard 2379: #ifdef LINMINORIGINAL
2380: xi[j] *= xmin;
2381: #else
2382: #ifdef DEBUGLINMIN
2383: if(xxs <1.0)
2384: printf(" before xi[%d]=%12.8f", j,xi[j]);
2385: #endif
2386: 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) */
2387: #ifdef DEBUGLINMIN
2388: if(xxs <1.0)
2389: 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 );
2390: #endif
2391: #endif
1.187 brouard 2392: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2393: }
1.191 brouard 2394: #ifdef DEBUGLINMIN
1.203 brouard 2395: printf("\n");
1.191 brouard 2396: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2397: 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 2398: for (j=1;j<=n;j++) {
1.202 brouard 2399: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2400: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2401: if(j % ncovmodel == 0){
1.191 brouard 2402: printf("\n");
1.202 brouard 2403: fprintf(ficlog,"\n");
2404: }
1.191 brouard 2405: }
1.203 brouard 2406: #else
1.191 brouard 2407: #endif
1.126 brouard 2408: free_vector(xicom,1,n);
2409: free_vector(pcom,1,n);
2410: }
2411:
2412:
2413: /*************** powell ************************/
1.162 brouard 2414: /*
1.317 brouard 2415: Minimization of a function func of n variables. Input consists in an initial starting point
2416: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2417: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2418: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2419: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2420: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2421: */
1.224 brouard 2422: #ifdef LINMINORIGINAL
2423: #else
2424: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2425: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2426: #endif
1.126 brouard 2427: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2428: double (*func)(double []))
2429: {
1.224 brouard 2430: #ifdef LINMINORIGINAL
2431: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2432: double (*func)(double []));
1.224 brouard 2433: #else
1.241 brouard 2434: void linmin(double p[], double xi[], int n, double *fret,
2435: double (*func)(double []),int *flat);
1.224 brouard 2436: #endif
1.239 brouard 2437: int i,ibig,j,jk,k;
1.126 brouard 2438: double del,t,*pt,*ptt,*xit;
1.181 brouard 2439: double directest;
1.126 brouard 2440: double fp,fptt;
2441: double *xits;
2442: int niterf, itmp;
2443:
2444: pt=vector(1,n);
2445: ptt=vector(1,n);
2446: xit=vector(1,n);
2447: xits=vector(1,n);
2448: *fret=(*func)(p);
2449: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2450: rcurr_time = time(NULL);
1.126 brouard 2451: for (*iter=1;;++(*iter)) {
2452: ibig=0;
2453: del=0.0;
1.157 brouard 2454: rlast_time=rcurr_time;
2455: /* (void) gettimeofday(&curr_time,&tzp); */
2456: rcurr_time = time(NULL);
2457: curr_time = *localtime(&rcurr_time);
1.324 brouard 2458: 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);
2459: 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 2460: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.324 brouard 2461: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2462: for (i=1;i<=n;i++) {
1.126 brouard 2463: fprintf(ficrespow," %.12lf", p[i]);
2464: }
1.239 brouard 2465: fprintf(ficrespow,"\n");fflush(ficrespow);
2466: printf("\n#model= 1 + age ");
2467: fprintf(ficlog,"\n#model= 1 + age ");
2468: if(nagesqr==1){
1.241 brouard 2469: printf(" + age*age ");
2470: fprintf(ficlog," + age*age ");
1.239 brouard 2471: }
2472: for(j=1;j <=ncovmodel-2;j++){
2473: if(Typevar[j]==0) {
2474: printf(" + V%d ",Tvar[j]);
2475: fprintf(ficlog," + V%d ",Tvar[j]);
2476: }else if(Typevar[j]==1) {
2477: printf(" + V%d*age ",Tvar[j]);
2478: fprintf(ficlog," + V%d*age ",Tvar[j]);
2479: }else if(Typevar[j]==2) {
2480: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2481: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2482: }
2483: }
1.126 brouard 2484: printf("\n");
1.239 brouard 2485: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2486: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2487: fprintf(ficlog,"\n");
1.239 brouard 2488: for(i=1,jk=1; i <=nlstate; i++){
2489: for(k=1; k <=(nlstate+ndeath); k++){
2490: if (k != i) {
2491: printf("%d%d ",i,k);
2492: fprintf(ficlog,"%d%d ",i,k);
2493: for(j=1; j <=ncovmodel; j++){
2494: printf("%12.7f ",p[jk]);
2495: fprintf(ficlog,"%12.7f ",p[jk]);
2496: jk++;
2497: }
2498: printf("\n");
2499: fprintf(ficlog,"\n");
2500: }
2501: }
2502: }
1.241 brouard 2503: if(*iter <=3 && *iter >1){
1.157 brouard 2504: tml = *localtime(&rcurr_time);
2505: strcpy(strcurr,asctime(&tml));
2506: rforecast_time=rcurr_time;
1.126 brouard 2507: itmp = strlen(strcurr);
2508: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2509: strcurr[itmp-1]='\0';
1.162 brouard 2510: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2511: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2512: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2513: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2514: forecast_time = *localtime(&rforecast_time);
2515: strcpy(strfor,asctime(&forecast_time));
2516: itmp = strlen(strfor);
2517: if(strfor[itmp-1]=='\n')
2518: strfor[itmp-1]='\0';
2519: 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);
2520: 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 2521: }
2522: }
1.187 brouard 2523: for (i=1;i<=n;i++) { /* For each direction i */
2524: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2525: fptt=(*fret);
2526: #ifdef DEBUG
1.203 brouard 2527: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2528: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2529: #endif
1.203 brouard 2530: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2531: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2532: #ifdef LINMINORIGINAL
1.188 brouard 2533: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2534: #else
2535: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2536: flatdir[i]=flat; /* Function is vanishing in that direction i */
2537: #endif
2538: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2539: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2540: /* because that direction will be replaced unless the gain del is small */
2541: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2542: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2543: /* with the new direction. */
2544: del=fabs(fptt-(*fret));
2545: ibig=i;
1.126 brouard 2546: }
2547: #ifdef DEBUG
2548: printf("%d %.12e",i,(*fret));
2549: fprintf(ficlog,"%d %.12e",i,(*fret));
2550: for (j=1;j<=n;j++) {
1.224 brouard 2551: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2552: printf(" x(%d)=%.12e",j,xit[j]);
2553: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2554: }
2555: for(j=1;j<=n;j++) {
1.225 brouard 2556: printf(" p(%d)=%.12e",j,p[j]);
2557: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2558: }
2559: printf("\n");
2560: fprintf(ficlog,"\n");
2561: #endif
1.187 brouard 2562: } /* end loop on each direction i */
2563: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2564: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2565: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2566: for(j=1;j<=n;j++) {
2567: if(flatdir[j] >0){
2568: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2569: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2570: }
1.319 brouard 2571: /* printf("\n"); */
2572: /* fprintf(ficlog,"\n"); */
2573: }
1.243 brouard 2574: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2575: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2576: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2577: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2578: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2579: /* decreased of more than 3.84 */
2580: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2581: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2582: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2583:
1.188 brouard 2584: /* Starting the program with initial values given by a former maximization will simply change */
2585: /* the scales of the directions and the directions, because the are reset to canonical directions */
2586: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2587: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2588: #ifdef DEBUG
2589: int k[2],l;
2590: k[0]=1;
2591: k[1]=-1;
2592: printf("Max: %.12e",(*func)(p));
2593: fprintf(ficlog,"Max: %.12e",(*func)(p));
2594: for (j=1;j<=n;j++) {
2595: printf(" %.12e",p[j]);
2596: fprintf(ficlog," %.12e",p[j]);
2597: }
2598: printf("\n");
2599: fprintf(ficlog,"\n");
2600: for(l=0;l<=1;l++) {
2601: for (j=1;j<=n;j++) {
2602: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2603: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2604: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2605: }
2606: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2607: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2608: }
2609: #endif
2610:
2611: free_vector(xit,1,n);
2612: free_vector(xits,1,n);
2613: free_vector(ptt,1,n);
2614: free_vector(pt,1,n);
2615: return;
1.192 brouard 2616: } /* enough precision */
1.240 brouard 2617: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2618: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2619: ptt[j]=2.0*p[j]-pt[j];
2620: xit[j]=p[j]-pt[j];
2621: pt[j]=p[j];
2622: }
1.181 brouard 2623: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2624: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2625: if (*iter <=4) {
1.225 brouard 2626: #else
2627: #endif
1.224 brouard 2628: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2629: #else
1.161 brouard 2630: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2631: #endif
1.162 brouard 2632: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2633: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2634: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2635: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2636: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2637: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2638: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2639: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2640: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2641: /* Even if f3 <f1, directest can be negative and t >0 */
2642: /* mu² and del² are equal when f3=f1 */
2643: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2644: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2645: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2646: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2647: #ifdef NRCORIGINAL
2648: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2649: #else
2650: 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 2651: t= t- del*SQR(fp-fptt);
1.183 brouard 2652: #endif
1.202 brouard 2653: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2654: #ifdef DEBUG
1.181 brouard 2655: 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);
2656: 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 2657: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2658: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2659: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2660: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2661: 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);
2662: 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);
2663: #endif
1.183 brouard 2664: #ifdef POWELLORIGINAL
2665: if (t < 0.0) { /* Then we use it for new direction */
2666: #else
1.182 brouard 2667: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2668: 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 2669: 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 2670: 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 2671: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2672: }
1.181 brouard 2673: if (directest < 0.0) { /* Then we use it for new direction */
2674: #endif
1.191 brouard 2675: #ifdef DEBUGLINMIN
1.234 brouard 2676: printf("Before linmin in direction P%d-P0\n",n);
2677: for (j=1;j<=n;j++) {
2678: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2679: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2680: if(j % ncovmodel == 0){
2681: printf("\n");
2682: fprintf(ficlog,"\n");
2683: }
2684: }
1.224 brouard 2685: #endif
2686: #ifdef LINMINORIGINAL
1.234 brouard 2687: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2688: #else
1.234 brouard 2689: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2690: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2691: #endif
1.234 brouard 2692:
1.191 brouard 2693: #ifdef DEBUGLINMIN
1.234 brouard 2694: for (j=1;j<=n;j++) {
2695: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2696: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2697: if(j % ncovmodel == 0){
2698: printf("\n");
2699: fprintf(ficlog,"\n");
2700: }
2701: }
1.224 brouard 2702: #endif
1.234 brouard 2703: for (j=1;j<=n;j++) {
2704: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2705: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2706: }
1.224 brouard 2707: #ifdef LINMINORIGINAL
2708: #else
1.234 brouard 2709: for (j=1, flatd=0;j<=n;j++) {
2710: if(flatdir[j]>0)
2711: flatd++;
2712: }
2713: if(flatd >0){
1.255 brouard 2714: printf("%d flat directions: ",flatd);
2715: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2716: for (j=1;j<=n;j++) {
2717: if(flatdir[j]>0){
2718: printf("%d ",j);
2719: fprintf(ficlog,"%d ",j);
2720: }
2721: }
2722: printf("\n");
2723: fprintf(ficlog,"\n");
1.319 brouard 2724: #ifdef FLATSUP
2725: free_vector(xit,1,n);
2726: free_vector(xits,1,n);
2727: free_vector(ptt,1,n);
2728: free_vector(pt,1,n);
2729: return;
2730: #endif
1.234 brouard 2731: }
1.191 brouard 2732: #endif
1.234 brouard 2733: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2734: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2735:
1.126 brouard 2736: #ifdef DEBUG
1.234 brouard 2737: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2738: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2739: for(j=1;j<=n;j++){
2740: printf(" %lf",xit[j]);
2741: fprintf(ficlog," %lf",xit[j]);
2742: }
2743: printf("\n");
2744: fprintf(ficlog,"\n");
1.126 brouard 2745: #endif
1.192 brouard 2746: } /* end of t or directest negative */
1.224 brouard 2747: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2748: #else
1.234 brouard 2749: } /* end if (fptt < fp) */
1.192 brouard 2750: #endif
1.225 brouard 2751: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2752: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2753: #else
1.224 brouard 2754: #endif
1.234 brouard 2755: } /* loop iteration */
1.126 brouard 2756: }
1.234 brouard 2757:
1.126 brouard 2758: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2759:
1.235 brouard 2760: 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 2761: {
1.279 brouard 2762: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2763: * (and selected quantitative values in nres)
2764: * by left multiplying the unit
2765: * matrix by transitions matrix until convergence is reached with precision ftolpl
2766: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2767: * Wx is row vector: population in state 1, population in state 2, population dead
2768: * or prevalence in state 1, prevalence in state 2, 0
2769: * newm is the matrix after multiplications, its rows are identical at a factor.
2770: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2771: * Output is prlim.
2772: * Initial matrix pimij
2773: */
1.206 brouard 2774: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2775: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2776: /* 0, 0 , 1} */
2777: /*
2778: * and after some iteration: */
2779: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2780: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2781: /* 0, 0 , 1} */
2782: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2783: /* {0.51571254859325999, 0.4842874514067399, */
2784: /* 0.51326036147820708, 0.48673963852179264} */
2785: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2786:
1.126 brouard 2787: int i, ii,j,k;
1.209 brouard 2788: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2789: /* double **matprod2(); */ /* test */
1.218 brouard 2790: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2791: double **newm;
1.209 brouard 2792: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2793: int ncvloop=0;
1.288 brouard 2794: int first=0;
1.169 brouard 2795:
1.209 brouard 2796: min=vector(1,nlstate);
2797: max=vector(1,nlstate);
2798: meandiff=vector(1,nlstate);
2799:
1.218 brouard 2800: /* Starting with matrix unity */
1.126 brouard 2801: for (ii=1;ii<=nlstate+ndeath;ii++)
2802: for (j=1;j<=nlstate+ndeath;j++){
2803: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2804: }
1.169 brouard 2805:
2806: cov[1]=1.;
2807:
2808: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2809: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2810: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2811: ncvloop++;
1.126 brouard 2812: newm=savm;
2813: /* Covariates have to be included here again */
1.138 brouard 2814: cov[2]=agefin;
1.319 brouard 2815: if(nagesqr==1){
2816: cov[3]= agefin*agefin;
2817: }
1.234 brouard 2818: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2819: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
1.330 brouard 2820: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];
1.319 brouard 2821: /* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; */
1.235 brouard 2822: /* 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)); */
1.234 brouard 2823: }
2824: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2825: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.319 brouard 2826: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2827: /* cov[++k1]=Tqresult[nres][k]; */
1.235 brouard 2828: /* 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]); */
1.138 brouard 2829: }
1.237 brouard 2830: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.319 brouard 2831: if(Dummy[Tage[k]]==2){ /* dummy with age */
1.330 brouard 2832: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2];
1.319 brouard 2833: /* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
2834: } else if(Dummy[Tage[k]]==3){ /* quantitative with age */
2835: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2836: /* cov[++k1]=Tqresult[nres][k]; */
1.234 brouard 2837: }
1.235 brouard 2838: /* 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]); */
1.234 brouard 2839: }
1.237 brouard 2840: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2841: /* 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]); */
1.329 brouard 2842: if(Dummy[Tvard[k][1]]==0){
2843: if(Dummy[Tvard[k][2]]==0){
1.330 brouard 2844: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])];
1.319 brouard 2845: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.237 brouard 2846: }else{
1.330 brouard 2847: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k];
1.319 brouard 2848: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; */
1.237 brouard 2849: }
2850: }else{
1.329 brouard 2851: if(Dummy[Tvard[k][2]]==0){
1.330 brouard 2852: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]];
1.319 brouard 2853: /* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; */
1.237 brouard 2854: }else{
2855: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
1.319 brouard 2856: /* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
1.237 brouard 2857: }
2858: }
1.234 brouard 2859: }
1.138 brouard 2860: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2861: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2862: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2863: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2864: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 2865: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2866: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2867:
1.126 brouard 2868: savm=oldm;
2869: oldm=newm;
1.209 brouard 2870:
2871: for(j=1; j<=nlstate; j++){
2872: max[j]=0.;
2873: min[j]=1.;
2874: }
2875: for(i=1;i<=nlstate;i++){
2876: sumnew=0;
2877: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2878: for(j=1; j<=nlstate; j++){
2879: prlim[i][j]= newm[i][j]/(1-sumnew);
2880: max[j]=FMAX(max[j],prlim[i][j]);
2881: min[j]=FMIN(min[j],prlim[i][j]);
2882: }
2883: }
2884:
1.126 brouard 2885: maxmax=0.;
1.209 brouard 2886: for(j=1; j<=nlstate; j++){
2887: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2888: maxmax=FMAX(maxmax,meandiff[j]);
2889: /* 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 2890: } /* j loop */
1.203 brouard 2891: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2892: /* 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 2893: if(maxmax < ftolpl){
1.209 brouard 2894: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2895: free_vector(min,1,nlstate);
2896: free_vector(max,1,nlstate);
2897: free_vector(meandiff,1,nlstate);
1.126 brouard 2898: return prlim;
2899: }
1.288 brouard 2900: } /* agefin loop */
1.208 brouard 2901: /* After some age loop it doesn't converge */
1.288 brouard 2902: if(!first){
2903: first=1;
2904: 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 2905: 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);
2906: }else if (first >=1 && first <10){
2907: 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);
2908: first++;
2909: }else if (first ==10){
2910: 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);
2911: 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");
2912: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
2913: first++;
1.288 brouard 2914: }
2915:
1.209 brouard 2916: /* 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); */
2917: free_vector(min,1,nlstate);
2918: free_vector(max,1,nlstate);
2919: free_vector(meandiff,1,nlstate);
1.208 brouard 2920:
1.169 brouard 2921: return prlim; /* should not reach here */
1.126 brouard 2922: }
2923:
1.217 brouard 2924:
2925: /**** Back Prevalence limit (stable or period prevalence) ****************/
2926:
1.218 brouard 2927: /* 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) */
2928: /* 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 2929: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2930: {
1.264 brouard 2931: /* 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 2932: matrix by transitions matrix until convergence is reached with precision ftolpl */
2933: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2934: /* Wx is row vector: population in state 1, population in state 2, population dead */
2935: /* or prevalence in state 1, prevalence in state 2, 0 */
2936: /* newm is the matrix after multiplications, its rows are identical at a factor */
2937: /* Initial matrix pimij */
2938: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2939: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2940: /* 0, 0 , 1} */
2941: /*
2942: * and after some iteration: */
2943: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2944: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2945: /* 0, 0 , 1} */
2946: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2947: /* {0.51571254859325999, 0.4842874514067399, */
2948: /* 0.51326036147820708, 0.48673963852179264} */
2949: /* If we start from prlim again, prlim tends to a constant matrix */
2950:
2951: int i, ii,j,k;
1.247 brouard 2952: int first=0;
1.217 brouard 2953: double *min, *max, *meandiff, maxmax,sumnew=0.;
2954: /* double **matprod2(); */ /* test */
2955: double **out, cov[NCOVMAX+1], **bmij();
2956: double **newm;
1.218 brouard 2957: double **dnewm, **doldm, **dsavm; /* for use */
2958: double **oldm, **savm; /* for use */
2959:
1.217 brouard 2960: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2961: int ncvloop=0;
2962:
2963: min=vector(1,nlstate);
2964: max=vector(1,nlstate);
2965: meandiff=vector(1,nlstate);
2966:
1.266 brouard 2967: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2968: oldm=oldms; savm=savms;
2969:
2970: /* Starting with matrix unity */
2971: for (ii=1;ii<=nlstate+ndeath;ii++)
2972: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2973: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2974: }
2975:
2976: cov[1]=1.;
2977:
2978: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2979: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2980: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 2981: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2982: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2983: ncvloop++;
1.218 brouard 2984: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2985: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2986: /* Covariates have to be included here again */
2987: cov[2]=agefin;
1.319 brouard 2988: if(nagesqr==1){
1.217 brouard 2989: cov[3]= agefin*agefin;;
1.319 brouard 2990: }
1.242 brouard 2991: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2992: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
1.330 brouard 2993: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];
1.264 brouard 2994: /* 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)); */
1.242 brouard 2995: }
2996: /* for (k=1; k<=cptcovn;k++) { */
2997: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2998: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2999: /* /\* 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])]); *\/ */
3000: /* } */
3001: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3002: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3003: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3004: /* 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]); */
3005: }
3006: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
3007: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
3008: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
3009: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
3010: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.319 brouard 3011: /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age *\/ ERROR ???*/
3012: if(Dummy[Tage[k]]== 2){ /* dummy with age */
1.330 brouard 3013: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2];
1.319 brouard 3014: } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */
3015: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.242 brouard 3016: }
3017: /* 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]); */
3018: }
3019: for (k=1; k<=cptcovprod;k++){ /* For product without age */
3020: /* 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]); */
1.329 brouard 3021: if(Dummy[Tvard[k][1]]==0){
3022: if(Dummy[Tvard[k][2]]==0){
1.330 brouard 3023: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])];
1.242 brouard 3024: }else{
1.330 brouard 3025: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k];
1.242 brouard 3026: }
3027: }else{
1.329 brouard 3028: if(Dummy[Tvard[k][2]]==0){
1.330 brouard 3029: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]];
1.242 brouard 3030: }else{
3031: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
3032: }
3033: }
1.217 brouard 3034: }
3035:
3036: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3037: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3038: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3039: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3040: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3041: /* ij should be linked to the correct index of cov */
3042: /* age and covariate values ij are in 'cov', but we need to pass
3043: * ij for the observed prevalence at age and status and covariate
3044: * number: prevacurrent[(int)agefin][ii][ij]
3045: */
3046: /* 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 *\/ */
3047: /* 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 *\/ */
3048: 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 3049: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3050: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3051: /* for(i=1; i<=nlstate+ndeath; i++) { */
3052: /* printf("%d newm= ",i); */
3053: /* for(j=1;j<=nlstate+ndeath;j++) { */
3054: /* printf("%f ",newm[i][j]); */
3055: /* } */
3056: /* printf("oldm * "); */
3057: /* for(j=1;j<=nlstate+ndeath;j++) { */
3058: /* printf("%f ",oldm[i][j]); */
3059: /* } */
1.268 brouard 3060: /* printf(" bmmij "); */
1.266 brouard 3061: /* for(j=1;j<=nlstate+ndeath;j++) { */
3062: /* printf("%f ",pmmij[i][j]); */
3063: /* } */
3064: /* printf("\n"); */
3065: /* } */
3066: /* } */
1.217 brouard 3067: savm=oldm;
3068: oldm=newm;
1.266 brouard 3069:
1.217 brouard 3070: for(j=1; j<=nlstate; j++){
3071: max[j]=0.;
3072: min[j]=1.;
3073: }
3074: for(j=1; j<=nlstate; j++){
3075: for(i=1;i<=nlstate;i++){
1.234 brouard 3076: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3077: bprlim[i][j]= newm[i][j];
3078: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3079: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3080: }
3081: }
1.218 brouard 3082:
1.217 brouard 3083: maxmax=0.;
3084: for(i=1; i<=nlstate; i++){
1.318 brouard 3085: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3086: maxmax=FMAX(maxmax,meandiff[i]);
3087: /* 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 3088: } /* i loop */
1.217 brouard 3089: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3090: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3091: if(maxmax < ftolpl){
1.220 brouard 3092: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3093: free_vector(min,1,nlstate);
3094: free_vector(max,1,nlstate);
3095: free_vector(meandiff,1,nlstate);
3096: return bprlim;
3097: }
1.288 brouard 3098: } /* agefin loop */
1.217 brouard 3099: /* After some age loop it doesn't converge */
1.288 brouard 3100: if(!first){
1.247 brouard 3101: first=1;
3102: 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\
3103: 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);
3104: }
3105: 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 3106: 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);
3107: /* 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); */
3108: free_vector(min,1,nlstate);
3109: free_vector(max,1,nlstate);
3110: free_vector(meandiff,1,nlstate);
3111:
3112: return bprlim; /* should not reach here */
3113: }
3114:
1.126 brouard 3115: /*************** transition probabilities ***************/
3116:
3117: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3118: {
1.138 brouard 3119: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3120: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3121: model to the ncovmodel covariates (including constant and age).
3122: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3123: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3124: ncth covariate in the global vector x is given by the formula:
3125: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3126: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3127: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3128: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3129: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3130: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3131: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3132: */
3133: double s1, lnpijopii;
1.126 brouard 3134: /*double t34;*/
1.164 brouard 3135: int i,j, nc, ii, jj;
1.126 brouard 3136:
1.223 brouard 3137: for(i=1; i<= nlstate; i++){
3138: for(j=1; j<i;j++){
3139: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3140: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3141: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3142: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3143: }
3144: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3145: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3146: }
3147: for(j=i+1; j<=nlstate+ndeath;j++){
3148: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3149: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3150: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3151: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3152: }
3153: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3154: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3155: }
3156: }
1.218 brouard 3157:
1.223 brouard 3158: for(i=1; i<= nlstate; i++){
3159: s1=0;
3160: for(j=1; j<i; j++){
3161: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
1.330 brouard 3162: /* 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 3163: }
3164: for(j=i+1; j<=nlstate+ndeath; j++){
3165: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
1.330 brouard 3166: /* 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 3167: }
3168: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3169: ps[i][i]=1./(s1+1.);
3170: /* Computing other pijs */
3171: for(j=1; j<i; j++)
1.325 brouard 3172: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3173: for(j=i+1; j<=nlstate+ndeath; j++)
3174: ps[i][j]= exp(ps[i][j])*ps[i][i];
3175: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3176: } /* end i */
1.218 brouard 3177:
1.223 brouard 3178: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3179: for(jj=1; jj<= nlstate+ndeath; jj++){
3180: ps[ii][jj]=0;
3181: ps[ii][ii]=1;
3182: }
3183: }
1.294 brouard 3184:
3185:
1.223 brouard 3186: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3187: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3188: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3189: /* } */
3190: /* printf("\n "); */
3191: /* } */
3192: /* printf("\n ");printf("%lf ",cov[2]);*/
3193: /*
3194: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3195: goto end;*/
1.266 brouard 3196: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3197: }
3198:
1.218 brouard 3199: /*************** backward transition probabilities ***************/
3200:
3201: /* 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 ) */
3202: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3203: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3204: {
1.302 brouard 3205: /* 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 3206: * 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 3207: */
1.218 brouard 3208: int i, ii, j,k;
1.222 brouard 3209:
3210: double **out, **pmij();
3211: double sumnew=0.;
1.218 brouard 3212: double agefin;
1.292 brouard 3213: 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 3214: double **dnewm, **dsavm, **doldm;
3215: double **bbmij;
3216:
1.218 brouard 3217: doldm=ddoldms; /* global pointers */
1.222 brouard 3218: dnewm=ddnewms;
3219: dsavm=ddsavms;
1.318 brouard 3220:
3221: /* Debug */
3222: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3223: agefin=cov[2];
1.268 brouard 3224: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3225: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3226: the observed prevalence (with this covariate ij) at beginning of transition */
3227: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3228:
3229: /* P_x */
1.325 brouard 3230: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3231: /* outputs pmmij which is a stochastic matrix in row */
3232:
3233: /* Diag(w_x) */
1.292 brouard 3234: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3235: sumnew=0.;
1.269 brouard 3236: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3237: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3238: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3239: sumnew+=prevacurrent[(int)agefin][ii][ij];
3240: }
3241: if(sumnew >0.01){ /* At least some value in the prevalence */
3242: for (ii=1;ii<=nlstate+ndeath;ii++){
3243: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3244: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3245: }
3246: }else{
3247: for (ii=1;ii<=nlstate+ndeath;ii++){
3248: for (j=1;j<=nlstate+ndeath;j++)
3249: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3250: }
3251: /* if(sumnew <0.9){ */
3252: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3253: /* } */
3254: }
3255: k3=0.0; /* We put the last diagonal to 0 */
3256: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3257: doldm[ii][ii]= k3;
3258: }
3259: /* End doldm, At the end doldm is diag[(w_i)] */
3260:
1.292 brouard 3261: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3262: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3263:
1.292 brouard 3264: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3265: /* 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 3266: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3267: sumnew=0.;
1.222 brouard 3268: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3269: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3270: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3271: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3272: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3273: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3274: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3275: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3276: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3277: /* }else */
1.268 brouard 3278: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3279: } /*End ii */
3280: } /* 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 */
3281:
1.292 brouard 3282: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3283: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3284: /* end bmij */
1.266 brouard 3285: return ps; /*pointer is unchanged */
1.218 brouard 3286: }
1.217 brouard 3287: /*************** transition probabilities ***************/
3288:
1.218 brouard 3289: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3290: {
3291: /* According to parameters values stored in x and the covariate's values stored in cov,
3292: computes the probability to be observed in state j being in state i by appying the
3293: model to the ncovmodel covariates (including constant and age).
3294: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3295: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3296: ncth covariate in the global vector x is given by the formula:
3297: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3298: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3299: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3300: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3301: Outputs ps[i][j] the probability to be observed in j being in j according to
3302: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3303: */
3304: double s1, lnpijopii;
3305: /*double t34;*/
3306: int i,j, nc, ii, jj;
3307:
1.234 brouard 3308: for(i=1; i<= nlstate; i++){
3309: for(j=1; j<i;j++){
3310: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3311: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3312: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3313: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3314: }
3315: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3316: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3317: }
3318: for(j=i+1; j<=nlstate+ndeath;j++){
3319: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3320: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3321: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3322: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3323: }
3324: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3325: }
3326: }
3327:
3328: for(i=1; i<= nlstate; i++){
3329: s1=0;
3330: for(j=1; j<i; j++){
3331: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3332: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3333: }
3334: for(j=i+1; j<=nlstate+ndeath; j++){
3335: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3336: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3337: }
3338: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3339: ps[i][i]=1./(s1+1.);
3340: /* Computing other pijs */
3341: for(j=1; j<i; j++)
3342: ps[i][j]= exp(ps[i][j])*ps[i][i];
3343: for(j=i+1; j<=nlstate+ndeath; j++)
3344: ps[i][j]= exp(ps[i][j])*ps[i][i];
3345: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3346: } /* end i */
3347:
3348: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3349: for(jj=1; jj<= nlstate+ndeath; jj++){
3350: ps[ii][jj]=0;
3351: ps[ii][ii]=1;
3352: }
3353: }
1.296 brouard 3354: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3355: for(jj=1; jj<= nlstate+ndeath; jj++){
3356: s1=0.;
3357: for(ii=1; ii<= nlstate+ndeath; ii++){
3358: s1+=ps[ii][jj];
3359: }
3360: for(ii=1; ii<= nlstate; ii++){
3361: ps[ii][jj]=ps[ii][jj]/s1;
3362: }
3363: }
3364: /* Transposition */
3365: for(jj=1; jj<= nlstate+ndeath; jj++){
3366: for(ii=jj; ii<= nlstate+ndeath; ii++){
3367: s1=ps[ii][jj];
3368: ps[ii][jj]=ps[jj][ii];
3369: ps[jj][ii]=s1;
3370: }
3371: }
3372: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3373: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3374: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3375: /* } */
3376: /* printf("\n "); */
3377: /* } */
3378: /* printf("\n ");printf("%lf ",cov[2]);*/
3379: /*
3380: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3381: goto end;*/
3382: return ps;
1.217 brouard 3383: }
3384:
3385:
1.126 brouard 3386: /**************** Product of 2 matrices ******************/
3387:
1.145 brouard 3388: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3389: {
3390: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3391: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3392: /* in, b, out are matrice of pointers which should have been initialized
3393: before: only the contents of out is modified. The function returns
3394: a pointer to pointers identical to out */
1.145 brouard 3395: int i, j, k;
1.126 brouard 3396: for(i=nrl; i<= nrh; i++)
1.145 brouard 3397: for(k=ncolol; k<=ncoloh; k++){
3398: out[i][k]=0.;
3399: for(j=ncl; j<=nch; j++)
3400: out[i][k] +=in[i][j]*b[j][k];
3401: }
1.126 brouard 3402: return out;
3403: }
3404:
3405:
3406: /************* Higher Matrix Product ***************/
3407:
1.235 brouard 3408: 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 3409: {
1.218 brouard 3410: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3411: 'nhstepm*hstepm*stepm' months (i.e. until
3412: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3413: nhstepm*hstepm matrices.
3414: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3415: (typically every 2 years instead of every month which is too big
3416: for the memory).
3417: Model is determined by parameters x and covariates have to be
3418: included manually here.
3419:
3420: */
3421:
1.330 brouard 3422: int i, j, d, h, k, k1;
1.131 brouard 3423: double **out, cov[NCOVMAX+1];
1.126 brouard 3424: double **newm;
1.187 brouard 3425: double agexact;
1.214 brouard 3426: double agebegin, ageend;
1.126 brouard 3427:
3428: /* Hstepm could be zero and should return the unit matrix */
3429: for (i=1;i<=nlstate+ndeath;i++)
3430: for (j=1;j<=nlstate+ndeath;j++){
3431: oldm[i][j]=(i==j ? 1.0 : 0.0);
3432: po[i][j][0]=(i==j ? 1.0 : 0.0);
3433: }
3434: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3435: for(h=1; h <=nhstepm; h++){
3436: for(d=1; d <=hstepm; d++){
3437: newm=savm;
3438: /* Covariates have to be included here again */
3439: cov[1]=1.;
1.214 brouard 3440: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3441: cov[2]=agexact;
1.319 brouard 3442: if(nagesqr==1){
1.227 brouard 3443: cov[3]= agexact*agexact;
1.319 brouard 3444: }
1.330 brouard 3445: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3446: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3447: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
3448: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
3449: /* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) */
3450: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3451: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
1.319 brouard 3452: /* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 */
3453: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3454: /* k 1 2 3 4 5 6 7 8 9 */
3455: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
3456: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
3457: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
3458: /*TvarsDind[k] 2 3 9 */ /* position K of single dummy cova */
1.330 brouard 3459: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] */
3460: cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]];
3461: /* 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]])); */
3462: 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);
3463: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative variables */
3464: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
3465: cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]];
3466: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3467: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3468: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3469: 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]]);
3470: }else if( Dummy[k1]==2 ){ /* For dummy with age product */
3471: /* Tvar[k1] Variable in the age product age*V1 is 1 */
3472: /* [Tinvresult[nres][V1] is its value in the resultline nres */
3473: cov[2+nagesqr+k1]=Tinvresult[nres][Tvar[k1]];
3474: printf("DhPxij Dummy with age k1=%d Tvar[%d]=%d Tinvresult[nres][%d]=%d,cov[2+%d+%d]=%.3f\n",k1,k1,Tvar[k1],Tinvresult[nres][Tvar[k1]],nagesqr,k1,cov[2+nagesqr+k1]);
3475: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3476: /* for (k=1; k<=cptcovage;k++){ /\* For product with age V1+V1*age +V4 +age*V3 *\/ */
3477: /* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*/
3478: /* */
3479: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3480: /* k 1 2 3 4 5 6 7 8 9 */
3481: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
3482: /*cptcovage=2 1 2 */
3483: /*Tage[k]= 5 8 */
1.331 ! brouard 3484: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.330 brouard 3485: cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]];
3486: 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]]);
3487: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3488: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ *\/ */
3489: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
3490: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3491: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; */
3492: /* 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); */
3493: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3494: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3495: /* } */
3496: /* 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]); */
3497: }else if(Typevar[k1]==2 ){ /* For product (not with age) */
3498: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3499: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3500: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3501: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3502: /* /\*cptcovprod=1 1 2 *\/ */
3503: /* /\*Tprod[]= 4 7 *\/ */
3504: /* /\*Tvard[][1] 4 1 *\/ */
3505: /* /\*Tvard[][2] 3 2 *\/ */
3506:
3507: /* 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])]); */
3508: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
3509: cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
3510: 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,Tvard[k1][1], k1,Tvard[k1][2], TinvDoQresult[nres][Tvardk[k1][1]], TinvDoQresult[nres][Tvardk[k1][2]]);
3511: /* if(Dummy[Tvardk[k1][1]]==0){ */
3512: /* if(Dummy[Tvardk[k1][2]]==0){ /\* Product of dummies *\/ */
3513: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
3514: /* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; */
3515: /* 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]])]; */
3516: /* }else{ /\* Product of dummy by quantitative *\/ */
3517: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; */
3518: /* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; */
3519: /* } */
3520: /* }else{ /\* Product of quantitative by...*\/ */
3521: /* if(Dummy[Tvard[k][2]]==0){ /\* quant by dummy *\/ */
3522: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
3523: /* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; */
3524: /* }else{ /\* Product of two quant *\/ */
3525: /* /\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
3526: /* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; */
3527: /* } */
3528: /* }/\*end of products quantitative *\/ */
3529: }/*end of products */
3530: } /* End of loop on model equation */
1.235 brouard 3531: /* for (k=1; k<=cptcovn;k++) */
3532: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3533: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3534: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3535: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3536: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3537:
3538:
1.126 brouard 3539: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3540: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3541: /* right multiplication of oldm by the current matrix */
1.126 brouard 3542: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3543: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3544: /* if((int)age == 70){ */
3545: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3546: /* for(i=1; i<=nlstate+ndeath; i++) { */
3547: /* printf("%d pmmij ",i); */
3548: /* for(j=1;j<=nlstate+ndeath;j++) { */
3549: /* printf("%f ",pmmij[i][j]); */
3550: /* } */
3551: /* printf(" oldm "); */
3552: /* for(j=1;j<=nlstate+ndeath;j++) { */
3553: /* printf("%f ",oldm[i][j]); */
3554: /* } */
3555: /* printf("\n"); */
3556: /* } */
3557: /* } */
1.126 brouard 3558: savm=oldm;
3559: oldm=newm;
3560: }
3561: for(i=1; i<=nlstate+ndeath; i++)
3562: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3563: po[i][j][h]=newm[i][j];
3564: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3565: }
1.128 brouard 3566: /*printf("h=%d ",h);*/
1.126 brouard 3567: } /* end h */
1.267 brouard 3568: /* printf("\n H=%d \n",h); */
1.126 brouard 3569: return po;
3570: }
3571:
1.217 brouard 3572: /************* Higher Back Matrix Product ***************/
1.218 brouard 3573: /* 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 3574: 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 3575: {
1.266 brouard 3576: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3577: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3578: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3579: nhstepm*hstepm matrices.
3580: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3581: (typically every 2 years instead of every month which is too big
1.217 brouard 3582: for the memory).
1.218 brouard 3583: Model is determined by parameters x and covariates have to be
1.266 brouard 3584: included manually here. Then we use a call to bmij(x and cov)
3585: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3586: */
1.217 brouard 3587:
3588: int i, j, d, h, k;
1.266 brouard 3589: double **out, cov[NCOVMAX+1], **bmij();
3590: double **newm, ***newmm;
1.217 brouard 3591: double agexact;
3592: double agebegin, ageend;
1.222 brouard 3593: double **oldm, **savm;
1.217 brouard 3594:
1.266 brouard 3595: newmm=po; /* To be saved */
3596: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3597: /* Hstepm could be zero and should return the unit matrix */
3598: for (i=1;i<=nlstate+ndeath;i++)
3599: for (j=1;j<=nlstate+ndeath;j++){
3600: oldm[i][j]=(i==j ? 1.0 : 0.0);
3601: po[i][j][0]=(i==j ? 1.0 : 0.0);
3602: }
3603: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3604: for(h=1; h <=nhstepm; h++){
3605: for(d=1; d <=hstepm; d++){
3606: newm=savm;
3607: /* Covariates have to be included here again */
3608: cov[1]=1.;
1.271 brouard 3609: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3610: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3611: /* Debug */
3612: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3613: cov[2]=agexact;
3614: if(nagesqr==1)
1.222 brouard 3615: cov[3]= agexact*agexact;
1.325 brouard 3616: for (k=1; k<=nsd;k++){ /* For single dummy covariates only *//* cptcovn error */
1.266 brouard 3617: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3618: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
1.330 brouard 3619: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/* Bug valgrind */
1.266 brouard 3620: /* 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)); */
3621: }
1.267 brouard 3622: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3623: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3624: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3625: /* 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]); */
3626: }
1.319 brouard 3627: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 *//* For product with age */
3628: /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age error!!!*\/ */
3629: if(Dummy[Tage[k]]== 2){ /* dummy with age */
1.330 brouard 3630: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2];
1.319 brouard 3631: } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */
1.267 brouard 3632: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3633: }
3634: /* 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]); */
3635: }
3636: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.330 brouard 3637: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])];
1.329 brouard 3638: if(Dummy[Tvard[k][1]]==0){
3639: if(Dummy[Tvard[k][2]]==0){
1.330 brouard 3640: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])];
1.325 brouard 3641: }else{
1.330 brouard 3642: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k];
1.325 brouard 3643: }
3644: }else{
1.329 brouard 3645: if(Dummy[Tvard[k][2]]==0){
1.330 brouard 3646: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]];
1.325 brouard 3647: }else{
3648: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
3649: }
3650: }
1.267 brouard 3651: }
1.217 brouard 3652: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3653: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3654:
1.218 brouard 3655: /* Careful transposed matrix */
1.266 brouard 3656: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3657: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3658: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3659: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3660: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3661: /* if((int)age == 70){ */
3662: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3663: /* for(i=1; i<=nlstate+ndeath; i++) { */
3664: /* printf("%d pmmij ",i); */
3665: /* for(j=1;j<=nlstate+ndeath;j++) { */
3666: /* printf("%f ",pmmij[i][j]); */
3667: /* } */
3668: /* printf(" oldm "); */
3669: /* for(j=1;j<=nlstate+ndeath;j++) { */
3670: /* printf("%f ",oldm[i][j]); */
3671: /* } */
3672: /* printf("\n"); */
3673: /* } */
3674: /* } */
3675: savm=oldm;
3676: oldm=newm;
3677: }
3678: for(i=1; i<=nlstate+ndeath; i++)
3679: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3680: po[i][j][h]=newm[i][j];
1.268 brouard 3681: /* if(h==nhstepm) */
3682: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3683: }
1.268 brouard 3684: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3685: } /* end h */
1.268 brouard 3686: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3687: return po;
3688: }
3689:
3690:
1.162 brouard 3691: #ifdef NLOPT
3692: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3693: double fret;
3694: double *xt;
3695: int j;
3696: myfunc_data *d2 = (myfunc_data *) pd;
3697: /* xt = (p1-1); */
3698: xt=vector(1,n);
3699: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3700:
3701: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3702: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3703: printf("Function = %.12lf ",fret);
3704: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3705: printf("\n");
3706: free_vector(xt,1,n);
3707: return fret;
3708: }
3709: #endif
1.126 brouard 3710:
3711: /*************** log-likelihood *************/
3712: double func( double *x)
3713: {
1.226 brouard 3714: int i, ii, j, k, mi, d, kk;
3715: int ioffset=0;
3716: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3717: double **out;
3718: double lli; /* Individual log likelihood */
3719: int s1, s2;
1.228 brouard 3720: 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 3721: double bbh, survp;
3722: long ipmx;
3723: double agexact;
3724: /*extern weight */
3725: /* We are differentiating ll according to initial status */
3726: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3727: /*for(i=1;i<imx;i++)
3728: printf(" %d\n",s[4][i]);
3729: */
1.162 brouard 3730:
1.226 brouard 3731: ++countcallfunc;
1.162 brouard 3732:
1.226 brouard 3733: cov[1]=1.;
1.126 brouard 3734:
1.226 brouard 3735: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3736: ioffset=0;
1.226 brouard 3737: if(mle==1){
3738: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3739: /* Computes the values of the ncovmodel covariates of the model
3740: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3741: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3742: to be observed in j being in i according to the model.
3743: */
1.243 brouard 3744: ioffset=2+nagesqr ;
1.233 brouard 3745: /* Fixed */
1.319 brouard 3746: for (k=1; k<=ncovf;k++){ /* For each fixed covariate dummu or quant or prod */
3747: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
3748: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3749: /* 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 3750: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.319 brouard 3751: 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)*/
3752: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 3753: }
1.226 brouard 3754: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 3755: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 3756: has been calculated etc */
3757: /* For an individual i, wav[i] gives the number of effective waves */
3758: /* We compute the contribution to Likelihood of each effective transition
3759: mw[mi][i] is real wave of the mi th effectve wave */
3760: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3761: s2=s[mw[mi+1][i]][i];
3762: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3763: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3764: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3765: */
3766: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 3767: 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*/
3768: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? */
1.242 brouard 3769: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3770: }
3771: for (ii=1;ii<=nlstate+ndeath;ii++)
3772: for (j=1;j<=nlstate+ndeath;j++){
3773: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3774: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3775: }
3776: for(d=0; d<dh[mi][i]; d++){
3777: newm=savm;
3778: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3779: cov[2]=agexact;
3780: if(nagesqr==1)
3781: cov[3]= agexact*agexact; /* Should be changed here */
3782: for (kk=1; kk<=cptcovage;kk++) {
1.318 brouard 3783: if(!FixedV[Tvar[Tage[kk]]])
3784: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
3785: else
3786: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3787: }
3788: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3789: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3790: savm=oldm;
3791: oldm=newm;
3792: } /* end mult */
3793:
3794: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3795: /* But now since version 0.9 we anticipate for bias at large stepm.
3796: * If stepm is larger than one month (smallest stepm) and if the exact delay
3797: * (in months) between two waves is not a multiple of stepm, we rounded to
3798: * the nearest (and in case of equal distance, to the lowest) interval but now
3799: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3800: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3801: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3802: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3803: * -stepm/2 to stepm/2 .
3804: * For stepm=1 the results are the same as for previous versions of Imach.
3805: * For stepm > 1 the results are less biased than in previous versions.
3806: */
1.234 brouard 3807: s1=s[mw[mi][i]][i];
3808: s2=s[mw[mi+1][i]][i];
3809: bbh=(double)bh[mi][i]/(double)stepm;
3810: /* bias bh is positive if real duration
3811: * is higher than the multiple of stepm and negative otherwise.
3812: */
3813: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3814: if( s2 > nlstate){
3815: /* i.e. if s2 is a death state and if the date of death is known
3816: then the contribution to the likelihood is the probability to
3817: die between last step unit time and current step unit time,
3818: which is also equal to probability to die before dh
3819: minus probability to die before dh-stepm .
3820: In version up to 0.92 likelihood was computed
3821: as if date of death was unknown. Death was treated as any other
3822: health state: the date of the interview describes the actual state
3823: and not the date of a change in health state. The former idea was
3824: to consider that at each interview the state was recorded
3825: (healthy, disable or death) and IMaCh was corrected; but when we
3826: introduced the exact date of death then we should have modified
3827: the contribution of an exact death to the likelihood. This new
3828: contribution is smaller and very dependent of the step unit
3829: stepm. It is no more the probability to die between last interview
3830: and month of death but the probability to survive from last
3831: interview up to one month before death multiplied by the
3832: probability to die within a month. Thanks to Chris
3833: Jackson for correcting this bug. Former versions increased
3834: mortality artificially. The bad side is that we add another loop
3835: which slows down the processing. The difference can be up to 10%
3836: lower mortality.
3837: */
3838: /* If, at the beginning of the maximization mostly, the
3839: cumulative probability or probability to be dead is
3840: constant (ie = 1) over time d, the difference is equal to
3841: 0. out[s1][3] = savm[s1][3]: probability, being at state
3842: s1 at precedent wave, to be dead a month before current
3843: wave is equal to probability, being at state s1 at
3844: precedent wave, to be dead at mont of the current
3845: wave. Then the observed probability (that this person died)
3846: is null according to current estimated parameter. In fact,
3847: it should be very low but not zero otherwise the log go to
3848: infinity.
3849: */
1.183 brouard 3850: /* #ifdef INFINITYORIGINAL */
3851: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3852: /* #else */
3853: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3854: /* lli=log(mytinydouble); */
3855: /* else */
3856: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3857: /* #endif */
1.226 brouard 3858: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3859:
1.226 brouard 3860: } else if ( s2==-1 ) { /* alive */
3861: for (j=1,survp=0. ; j<=nlstate; j++)
3862: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3863: /*survp += out[s1][j]; */
3864: lli= log(survp);
3865: }
3866: else if (s2==-4) {
3867: for (j=3,survp=0. ; j<=nlstate; j++)
3868: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3869: lli= log(survp);
3870: }
3871: else if (s2==-5) {
3872: for (j=1,survp=0. ; j<=2; j++)
3873: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3874: lli= log(survp);
3875: }
3876: else{
3877: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3878: /* 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 */
3879: }
3880: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3881: /*if(lli ==000.0)*/
3882: /*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); */
3883: ipmx +=1;
3884: sw += weight[i];
3885: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3886: /* if (lli < log(mytinydouble)){ */
3887: /* 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); */
3888: /* 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]); */
3889: /* } */
3890: } /* end of wave */
3891: } /* end of individual */
3892: } else if(mle==2){
3893: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 3894: ioffset=2+nagesqr ;
3895: for (k=1; k<=ncovf;k++)
3896: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 3897: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 3898: for(k=1; k <= ncovv ; k++){
3899: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3900: }
1.226 brouard 3901: for (ii=1;ii<=nlstate+ndeath;ii++)
3902: for (j=1;j<=nlstate+ndeath;j++){
3903: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3904: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3905: }
3906: for(d=0; d<=dh[mi][i]; d++){
3907: newm=savm;
3908: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3909: cov[2]=agexact;
3910: if(nagesqr==1)
3911: cov[3]= agexact*agexact;
3912: for (kk=1; kk<=cptcovage;kk++) {
3913: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3914: }
3915: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3916: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3917: savm=oldm;
3918: oldm=newm;
3919: } /* end mult */
3920:
3921: s1=s[mw[mi][i]][i];
3922: s2=s[mw[mi+1][i]][i];
3923: bbh=(double)bh[mi][i]/(double)stepm;
3924: 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 */
3925: ipmx +=1;
3926: sw += weight[i];
3927: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3928: } /* end of wave */
3929: } /* end of individual */
3930: } else if(mle==3){ /* exponential inter-extrapolation */
3931: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3932: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3933: for(mi=1; mi<= wav[i]-1; mi++){
3934: for (ii=1;ii<=nlstate+ndeath;ii++)
3935: for (j=1;j<=nlstate+ndeath;j++){
3936: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3937: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3938: }
3939: for(d=0; d<dh[mi][i]; d++){
3940: newm=savm;
3941: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3942: cov[2]=agexact;
3943: if(nagesqr==1)
3944: cov[3]= agexact*agexact;
3945: for (kk=1; kk<=cptcovage;kk++) {
3946: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3947: }
3948: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3949: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3950: savm=oldm;
3951: oldm=newm;
3952: } /* end mult */
3953:
3954: s1=s[mw[mi][i]][i];
3955: s2=s[mw[mi+1][i]][i];
3956: bbh=(double)bh[mi][i]/(double)stepm;
3957: 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 */
3958: ipmx +=1;
3959: sw += weight[i];
3960: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3961: } /* end of wave */
3962: } /* end of individual */
3963: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3964: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3965: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3966: for(mi=1; mi<= wav[i]-1; mi++){
3967: for (ii=1;ii<=nlstate+ndeath;ii++)
3968: for (j=1;j<=nlstate+ndeath;j++){
3969: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3970: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3971: }
3972: for(d=0; d<dh[mi][i]; d++){
3973: newm=savm;
3974: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3975: cov[2]=agexact;
3976: if(nagesqr==1)
3977: cov[3]= agexact*agexact;
3978: for (kk=1; kk<=cptcovage;kk++) {
3979: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3980: }
1.126 brouard 3981:
1.226 brouard 3982: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3983: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3984: savm=oldm;
3985: oldm=newm;
3986: } /* end mult */
3987:
3988: s1=s[mw[mi][i]][i];
3989: s2=s[mw[mi+1][i]][i];
3990: if( s2 > nlstate){
3991: lli=log(out[s1][s2] - savm[s1][s2]);
3992: } else if ( s2==-1 ) { /* alive */
3993: for (j=1,survp=0. ; j<=nlstate; j++)
3994: survp += out[s1][j];
3995: lli= log(survp);
3996: }else{
3997: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3998: }
3999: ipmx +=1;
4000: sw += weight[i];
4001: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 4002: /* 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 4003: } /* end of wave */
4004: } /* end of individual */
4005: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4006: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4007: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4008: for(mi=1; mi<= wav[i]-1; mi++){
4009: for (ii=1;ii<=nlstate+ndeath;ii++)
4010: for (j=1;j<=nlstate+ndeath;j++){
4011: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4012: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4013: }
4014: for(d=0; d<dh[mi][i]; d++){
4015: newm=savm;
4016: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4017: cov[2]=agexact;
4018: if(nagesqr==1)
4019: cov[3]= agexact*agexact;
4020: for (kk=1; kk<=cptcovage;kk++) {
4021: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4022: }
1.126 brouard 4023:
1.226 brouard 4024: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4025: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4026: savm=oldm;
4027: oldm=newm;
4028: } /* end mult */
4029:
4030: s1=s[mw[mi][i]][i];
4031: s2=s[mw[mi+1][i]][i];
4032: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4033: ipmx +=1;
4034: sw += weight[i];
4035: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4036: /*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]);*/
4037: } /* end of wave */
4038: } /* end of individual */
4039: } /* End of if */
4040: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4041: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4042: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4043: return -l;
1.126 brouard 4044: }
4045:
4046: /*************** log-likelihood *************/
4047: double funcone( double *x)
4048: {
1.228 brouard 4049: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 4050: int i, ii, j, k, mi, d, kk;
1.228 brouard 4051: int ioffset=0;
1.131 brouard 4052: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4053: double **out;
4054: double lli; /* Individual log likelihood */
4055: double llt;
4056: int s1, s2;
1.228 brouard 4057: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4058:
1.126 brouard 4059: double bbh, survp;
1.187 brouard 4060: double agexact;
1.214 brouard 4061: double agebegin, ageend;
1.126 brouard 4062: /*extern weight */
4063: /* We are differentiating ll according to initial status */
4064: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4065: /*for(i=1;i<imx;i++)
4066: printf(" %d\n",s[4][i]);
4067: */
4068: cov[1]=1.;
4069:
4070: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4071: ioffset=0;
4072: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 4073: /* ioffset=2+nagesqr+cptcovage; */
4074: ioffset=2+nagesqr;
1.232 brouard 4075: /* Fixed */
1.224 brouard 4076: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4077: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.311 brouard 4078: 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 4079: 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)*/
4080: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4081: /* cov[2+6]=covar[Tvar[6]][i]; */
4082: /* cov[2+6]=covar[2][i]; V2 */
4083: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4084: /* cov[2+7]=covar[Tvar[7]][i]; */
4085: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4086: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4087: /* cov[2+9]=covar[Tvar[9]][i]; */
4088: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4089: }
1.232 brouard 4090: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4091: /* 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?)*\/ */
4092: /* } */
1.231 brouard 4093: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4094: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4095: /* } */
1.225 brouard 4096:
1.233 brouard 4097:
4098: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 4099: /* Wave varying (but not age varying) */
4100: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 4101: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
4102: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
4103: }
1.232 brouard 4104: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 4105: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4106: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
4107: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
4108: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
4109: /* 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 4110: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4111: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4112: /* /\* 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]); *\/ */
4113: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4114: /* } */
1.126 brouard 4115: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4116: for (j=1;j<=nlstate+ndeath;j++){
4117: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4118: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4119: }
1.214 brouard 4120:
4121: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4122: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4123: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4124: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4125: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4126: and mw[mi+1][i]. dh depends on stepm.*/
4127: newm=savm;
1.247 brouard 4128: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4129: cov[2]=agexact;
4130: if(nagesqr==1)
4131: cov[3]= agexact*agexact;
4132: for (kk=1; kk<=cptcovage;kk++) {
4133: if(!FixedV[Tvar[Tage[kk]]])
4134: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4135: else
4136: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
4137: }
4138: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4139: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4140: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4141: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4142: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4143: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4144: savm=oldm;
4145: oldm=newm;
1.126 brouard 4146: } /* end mult */
4147:
4148: s1=s[mw[mi][i]][i];
4149: s2=s[mw[mi+1][i]][i];
1.217 brouard 4150: /* if(s2==-1){ */
1.268 brouard 4151: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4152: /* /\* exit(1); *\/ */
4153: /* } */
1.126 brouard 4154: bbh=(double)bh[mi][i]/(double)stepm;
4155: /* bias is positive if real duration
4156: * is higher than the multiple of stepm and negative otherwise.
4157: */
4158: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4159: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4160: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4161: for (j=1,survp=0. ; j<=nlstate; j++)
4162: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4163: lli= log(survp);
1.126 brouard 4164: }else if (mle==1){
1.242 brouard 4165: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4166: } else if(mle==2){
1.242 brouard 4167: 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 4168: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4169: 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 4170: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4171: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4172: } else{ /* mle=0 back to 1 */
1.242 brouard 4173: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4174: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4175: } /* End of if */
4176: ipmx +=1;
4177: sw += weight[i];
4178: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 4179: /*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 4180: if(globpr){
1.246 brouard 4181: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4182: %11.6f %11.6f %11.6f ", \
1.242 brouard 4183: 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 4184: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 4185: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4186: llt +=ll[k]*gipmx/gsw;
4187: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
4188: }
4189: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 4190: }
1.232 brouard 4191: } /* end of wave */
4192: } /* end of individual */
4193: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4194: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4195: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4196: if(globpr==0){ /* First time we count the contributions and weights */
4197: gipmx=ipmx;
4198: gsw=sw;
4199: }
4200: return -l;
1.126 brouard 4201: }
4202:
4203:
4204: /*************** function likelione ***********/
1.292 brouard 4205: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4206: {
4207: /* This routine should help understanding what is done with
4208: the selection of individuals/waves and
4209: to check the exact contribution to the likelihood.
4210: Plotting could be done.
4211: */
4212: int k;
4213:
4214: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4215: strcpy(fileresilk,"ILK_");
1.202 brouard 4216: strcat(fileresilk,fileresu);
1.126 brouard 4217: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4218: printf("Problem with resultfile: %s\n", fileresilk);
4219: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4220: }
1.214 brouard 4221: 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");
4222: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4223: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4224: for(k=1; k<=nlstate; k++)
4225: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
4226: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
4227: }
4228:
1.292 brouard 4229: *fretone=(*func)(p);
1.126 brouard 4230: if(*globpri !=0){
4231: fclose(ficresilk);
1.205 brouard 4232: if (mle ==0)
4233: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4234: else if(mle >=1)
4235: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4236: 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 4237: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4238:
4239: for (k=1; k<= nlstate ; k++) {
1.211 brouard 4240: 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 4241: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4242: }
1.207 brouard 4243: 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 4244: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4245: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 4246: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4247: fflush(fichtm);
1.205 brouard 4248: }
1.126 brouard 4249: return;
4250: }
4251:
4252:
4253: /*********** Maximum Likelihood Estimation ***************/
4254:
4255: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4256: {
1.319 brouard 4257: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4258: double **xi;
4259: double fret;
4260: double fretone; /* Only one call to likelihood */
4261: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4262:
4263: #ifdef NLOPT
4264: int creturn;
4265: nlopt_opt opt;
4266: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4267: double *lb;
4268: double minf; /* the minimum objective value, upon return */
4269: double * p1; /* Shifted parameters from 0 instead of 1 */
4270: myfunc_data dinst, *d = &dinst;
4271: #endif
4272:
4273:
1.126 brouard 4274: xi=matrix(1,npar,1,npar);
4275: for (i=1;i<=npar;i++)
4276: for (j=1;j<=npar;j++)
4277: xi[i][j]=(i==j ? 1.0 : 0.0);
4278: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4279: strcpy(filerespow,"POW_");
1.126 brouard 4280: strcat(filerespow,fileres);
4281: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4282: printf("Problem with resultfile: %s\n", filerespow);
4283: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4284: }
4285: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4286: for (i=1;i<=nlstate;i++)
4287: for(j=1;j<=nlstate+ndeath;j++)
4288: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4289: fprintf(ficrespow,"\n");
1.162 brouard 4290: #ifdef POWELL
1.319 brouard 4291: #ifdef LINMINORIGINAL
4292: #else /* LINMINORIGINAL */
4293:
4294: flatdir=ivector(1,npar);
4295: for (j=1;j<=npar;j++) flatdir[j]=0;
4296: #endif /*LINMINORIGINAL */
4297:
4298: #ifdef FLATSUP
4299: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4300: /* reorganizing p by suppressing flat directions */
4301: for(i=1, jk=1; i <=nlstate; i++){
4302: for(k=1; k <=(nlstate+ndeath); k++){
4303: if (k != i) {
4304: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4305: if(flatdir[jk]==1){
4306: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4307: }
4308: for(j=1; j <=ncovmodel; j++){
4309: printf("%12.7f ",p[jk]);
4310: jk++;
4311: }
4312: printf("\n");
4313: }
4314: }
4315: }
4316: /* skipping */
4317: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4318: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4319: for(k=1; k <=(nlstate+ndeath); k++){
4320: if (k != i) {
4321: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4322: if(flatdir[jk]==1){
4323: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4324: for(j=1; j <=ncovmodel; jk++,j++){
4325: printf(" p[%d]=%12.7f",jk, p[jk]);
4326: /*q[jjk]=p[jk];*/
4327: }
4328: }else{
4329: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4330: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4331: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
4332: /*q[jjk]=p[jk];*/
4333: }
4334: }
4335: printf("\n");
4336: }
4337: fflush(stdout);
4338: }
4339: }
4340: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4341: #else /* FLATSUP */
1.126 brouard 4342: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 4343: #endif /* FLATSUP */
4344:
4345: #ifdef LINMINORIGINAL
4346: #else
4347: free_ivector(flatdir,1,npar);
4348: #endif /* LINMINORIGINAL*/
4349: #endif /* POWELL */
1.126 brouard 4350:
1.162 brouard 4351: #ifdef NLOPT
4352: #ifdef NEWUOA
4353: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4354: #else
4355: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4356: #endif
4357: lb=vector(0,npar-1);
4358: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4359: nlopt_set_lower_bounds(opt, lb);
4360: nlopt_set_initial_step1(opt, 0.1);
4361:
4362: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4363: d->function = func;
4364: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4365: nlopt_set_min_objective(opt, myfunc, d);
4366: nlopt_set_xtol_rel(opt, ftol);
4367: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4368: printf("nlopt failed! %d\n",creturn);
4369: }
4370: else {
4371: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4372: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4373: iter=1; /* not equal */
4374: }
4375: nlopt_destroy(opt);
4376: #endif
1.319 brouard 4377: #ifdef FLATSUP
4378: /* npared = npar -flatd/ncovmodel; */
4379: /* xired= matrix(1,npared,1,npared); */
4380: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
4381: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
4382: /* free_matrix(xire,1,npared,1,npared); */
4383: #else /* FLATSUP */
4384: #endif /* FLATSUP */
1.126 brouard 4385: free_matrix(xi,1,npar,1,npar);
4386: fclose(ficrespow);
1.203 brouard 4387: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4388: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4389: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4390:
4391: }
4392:
4393: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4394: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4395: {
4396: double **a,**y,*x,pd;
1.203 brouard 4397: /* double **hess; */
1.164 brouard 4398: int i, j;
1.126 brouard 4399: int *indx;
4400:
4401: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4402: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4403: void lubksb(double **a, int npar, int *indx, double b[]) ;
4404: void ludcmp(double **a, int npar, int *indx, double *d) ;
4405: double gompertz(double p[]);
1.203 brouard 4406: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4407:
4408: printf("\nCalculation of the hessian matrix. Wait...\n");
4409: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4410: for (i=1;i<=npar;i++){
1.203 brouard 4411: printf("%d-",i);fflush(stdout);
4412: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4413:
4414: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4415:
4416: /* printf(" %f ",p[i]);
4417: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4418: }
4419:
4420: for (i=1;i<=npar;i++) {
4421: for (j=1;j<=npar;j++) {
4422: if (j>i) {
1.203 brouard 4423: printf(".%d-%d",i,j);fflush(stdout);
4424: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4425: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4426:
4427: hess[j][i]=hess[i][j];
4428: /*printf(" %lf ",hess[i][j]);*/
4429: }
4430: }
4431: }
4432: printf("\n");
4433: fprintf(ficlog,"\n");
4434:
4435: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4436: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4437:
4438: a=matrix(1,npar,1,npar);
4439: y=matrix(1,npar,1,npar);
4440: x=vector(1,npar);
4441: indx=ivector(1,npar);
4442: for (i=1;i<=npar;i++)
4443: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4444: ludcmp(a,npar,indx,&pd);
4445:
4446: for (j=1;j<=npar;j++) {
4447: for (i=1;i<=npar;i++) x[i]=0;
4448: x[j]=1;
4449: lubksb(a,npar,indx,x);
4450: for (i=1;i<=npar;i++){
4451: matcov[i][j]=x[i];
4452: }
4453: }
4454:
4455: printf("\n#Hessian matrix#\n");
4456: fprintf(ficlog,"\n#Hessian matrix#\n");
4457: for (i=1;i<=npar;i++) {
4458: for (j=1;j<=npar;j++) {
1.203 brouard 4459: printf("%.6e ",hess[i][j]);
4460: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4461: }
4462: printf("\n");
4463: fprintf(ficlog,"\n");
4464: }
4465:
1.203 brouard 4466: /* printf("\n#Covariance matrix#\n"); */
4467: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4468: /* for (i=1;i<=npar;i++) { */
4469: /* for (j=1;j<=npar;j++) { */
4470: /* printf("%.6e ",matcov[i][j]); */
4471: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4472: /* } */
4473: /* printf("\n"); */
4474: /* fprintf(ficlog,"\n"); */
4475: /* } */
4476:
1.126 brouard 4477: /* Recompute Inverse */
1.203 brouard 4478: /* for (i=1;i<=npar;i++) */
4479: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4480: /* ludcmp(a,npar,indx,&pd); */
4481:
4482: /* printf("\n#Hessian matrix recomputed#\n"); */
4483:
4484: /* for (j=1;j<=npar;j++) { */
4485: /* for (i=1;i<=npar;i++) x[i]=0; */
4486: /* x[j]=1; */
4487: /* lubksb(a,npar,indx,x); */
4488: /* for (i=1;i<=npar;i++){ */
4489: /* y[i][j]=x[i]; */
4490: /* printf("%.3e ",y[i][j]); */
4491: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4492: /* } */
4493: /* printf("\n"); */
4494: /* fprintf(ficlog,"\n"); */
4495: /* } */
4496:
4497: /* Verifying the inverse matrix */
4498: #ifdef DEBUGHESS
4499: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4500:
1.203 brouard 4501: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4502: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4503:
4504: for (j=1;j<=npar;j++) {
4505: for (i=1;i<=npar;i++){
1.203 brouard 4506: printf("%.2f ",y[i][j]);
4507: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4508: }
4509: printf("\n");
4510: fprintf(ficlog,"\n");
4511: }
1.203 brouard 4512: #endif
1.126 brouard 4513:
4514: free_matrix(a,1,npar,1,npar);
4515: free_matrix(y,1,npar,1,npar);
4516: free_vector(x,1,npar);
4517: free_ivector(indx,1,npar);
1.203 brouard 4518: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4519:
4520:
4521: }
4522:
4523: /*************** hessian matrix ****************/
4524: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4525: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4526: int i;
4527: int l=1, lmax=20;
1.203 brouard 4528: double k1,k2, res, fx;
1.132 brouard 4529: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4530: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4531: int k=0,kmax=10;
4532: double l1;
4533:
4534: fx=func(x);
4535: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4536: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4537: l1=pow(10,l);
4538: delts=delt;
4539: for(k=1 ; k <kmax; k=k+1){
4540: delt = delta*(l1*k);
4541: p2[theta]=x[theta] +delt;
1.145 brouard 4542: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4543: p2[theta]=x[theta]-delt;
4544: k2=func(p2)-fx;
4545: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4546: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4547:
1.203 brouard 4548: #ifdef DEBUGHESSII
1.126 brouard 4549: 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);
4550: 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);
4551: #endif
4552: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4553: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4554: k=kmax;
4555: }
4556: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4557: k=kmax; l=lmax*10;
1.126 brouard 4558: }
4559: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4560: delts=delt;
4561: }
1.203 brouard 4562: } /* End loop k */
1.126 brouard 4563: }
4564: delti[theta]=delts;
4565: return res;
4566:
4567: }
4568:
1.203 brouard 4569: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4570: {
4571: int i;
1.164 brouard 4572: int l=1, lmax=20;
1.126 brouard 4573: double k1,k2,k3,k4,res,fx;
1.132 brouard 4574: double p2[MAXPARM+1];
1.203 brouard 4575: int k, kmax=1;
4576: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4577:
4578: int firstime=0;
1.203 brouard 4579:
1.126 brouard 4580: fx=func(x);
1.203 brouard 4581: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4582: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4583: p2[thetai]=x[thetai]+delti[thetai]*k;
4584: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4585: k1=func(p2)-fx;
4586:
1.203 brouard 4587: p2[thetai]=x[thetai]+delti[thetai]*k;
4588: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4589: k2=func(p2)-fx;
4590:
1.203 brouard 4591: p2[thetai]=x[thetai]-delti[thetai]*k;
4592: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4593: k3=func(p2)-fx;
4594:
1.203 brouard 4595: p2[thetai]=x[thetai]-delti[thetai]*k;
4596: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4597: k4=func(p2)-fx;
1.203 brouard 4598: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4599: if(k1*k2*k3*k4 <0.){
1.208 brouard 4600: firstime=1;
1.203 brouard 4601: kmax=kmax+10;
1.208 brouard 4602: }
4603: if(kmax >=10 || firstime ==1){
1.246 brouard 4604: 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);
4605: 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 4606: 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);
4607: 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);
4608: }
4609: #ifdef DEBUGHESSIJ
4610: v1=hess[thetai][thetai];
4611: v2=hess[thetaj][thetaj];
4612: cv12=res;
4613: /* Computing eigen value of Hessian matrix */
4614: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4615: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4616: if ((lc2 <0) || (lc1 <0) ){
4617: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4618: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4619: 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);
4620: 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);
4621: }
1.126 brouard 4622: #endif
4623: }
4624: return res;
4625: }
4626:
1.203 brouard 4627: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4628: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4629: /* { */
4630: /* int i; */
4631: /* int l=1, lmax=20; */
4632: /* double k1,k2,k3,k4,res,fx; */
4633: /* double p2[MAXPARM+1]; */
4634: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4635: /* int k=0,kmax=10; */
4636: /* double l1; */
4637:
4638: /* fx=func(x); */
4639: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4640: /* l1=pow(10,l); */
4641: /* delts=delt; */
4642: /* for(k=1 ; k <kmax; k=k+1){ */
4643: /* delt = delti*(l1*k); */
4644: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4645: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4646: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4647: /* k1=func(p2)-fx; */
4648:
4649: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4650: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4651: /* k2=func(p2)-fx; */
4652:
4653: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4654: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4655: /* k3=func(p2)-fx; */
4656:
4657: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4658: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4659: /* k4=func(p2)-fx; */
4660: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4661: /* #ifdef DEBUGHESSIJ */
4662: /* 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); */
4663: /* 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); */
4664: /* #endif */
4665: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4666: /* k=kmax; */
4667: /* } */
4668: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4669: /* k=kmax; l=lmax*10; */
4670: /* } */
4671: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4672: /* delts=delt; */
4673: /* } */
4674: /* } /\* End loop k *\/ */
4675: /* } */
4676: /* delti[theta]=delts; */
4677: /* return res; */
4678: /* } */
4679:
4680:
1.126 brouard 4681: /************** Inverse of matrix **************/
4682: void ludcmp(double **a, int n, int *indx, double *d)
4683: {
4684: int i,imax,j,k;
4685: double big,dum,sum,temp;
4686: double *vv;
4687:
4688: vv=vector(1,n);
4689: *d=1.0;
4690: for (i=1;i<=n;i++) {
4691: big=0.0;
4692: for (j=1;j<=n;j++)
4693: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4694: if (big == 0.0){
4695: printf(" Singular Hessian matrix at row %d:\n",i);
4696: for (j=1;j<=n;j++) {
4697: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4698: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4699: }
4700: fflush(ficlog);
4701: fclose(ficlog);
4702: nrerror("Singular matrix in routine ludcmp");
4703: }
1.126 brouard 4704: vv[i]=1.0/big;
4705: }
4706: for (j=1;j<=n;j++) {
4707: for (i=1;i<j;i++) {
4708: sum=a[i][j];
4709: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4710: a[i][j]=sum;
4711: }
4712: big=0.0;
4713: for (i=j;i<=n;i++) {
4714: sum=a[i][j];
4715: for (k=1;k<j;k++)
4716: sum -= a[i][k]*a[k][j];
4717: a[i][j]=sum;
4718: if ( (dum=vv[i]*fabs(sum)) >= big) {
4719: big=dum;
4720: imax=i;
4721: }
4722: }
4723: if (j != imax) {
4724: for (k=1;k<=n;k++) {
4725: dum=a[imax][k];
4726: a[imax][k]=a[j][k];
4727: a[j][k]=dum;
4728: }
4729: *d = -(*d);
4730: vv[imax]=vv[j];
4731: }
4732: indx[j]=imax;
4733: if (a[j][j] == 0.0) a[j][j]=TINY;
4734: if (j != n) {
4735: dum=1.0/(a[j][j]);
4736: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4737: }
4738: }
4739: free_vector(vv,1,n); /* Doesn't work */
4740: ;
4741: }
4742:
4743: void lubksb(double **a, int n, int *indx, double b[])
4744: {
4745: int i,ii=0,ip,j;
4746: double sum;
4747:
4748: for (i=1;i<=n;i++) {
4749: ip=indx[i];
4750: sum=b[ip];
4751: b[ip]=b[i];
4752: if (ii)
4753: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4754: else if (sum) ii=i;
4755: b[i]=sum;
4756: }
4757: for (i=n;i>=1;i--) {
4758: sum=b[i];
4759: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4760: b[i]=sum/a[i][i];
4761: }
4762: }
4763:
4764: void pstamp(FILE *fichier)
4765: {
1.196 brouard 4766: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4767: }
4768:
1.297 brouard 4769: void date2dmy(double date,double *day, double *month, double *year){
4770: double yp=0., yp1=0., yp2=0.;
4771:
4772: yp1=modf(date,&yp);/* extracts integral of date in yp and
4773: fractional in yp1 */
4774: *year=yp;
4775: yp2=modf((yp1*12),&yp);
4776: *month=yp;
4777: yp1=modf((yp2*30.5),&yp);
4778: *day=yp;
4779: if(*day==0) *day=1;
4780: if(*month==0) *month=1;
4781: }
4782:
1.253 brouard 4783:
4784:
1.126 brouard 4785: /************ Frequencies ********************/
1.251 brouard 4786: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4787: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4788: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4789: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4790:
1.265 brouard 4791: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4792: int iind=0, iage=0;
4793: int mi; /* Effective wave */
4794: int first;
4795: double ***freq; /* Frequencies */
1.268 brouard 4796: 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 */
4797: 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 4798: double *meanq, *stdq, *idq;
1.226 brouard 4799: double **meanqt;
4800: double *pp, **prop, *posprop, *pospropt;
4801: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4802: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4803: double agebegin, ageend;
4804:
4805: pp=vector(1,nlstate);
1.251 brouard 4806: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4807: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4808: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4809: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4810: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4811: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4812: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4813: meanqt=matrix(1,lastpass,1,nqtveff);
4814: strcpy(fileresp,"P_");
4815: strcat(fileresp,fileresu);
4816: /*strcat(fileresphtm,fileresu);*/
4817: if((ficresp=fopen(fileresp,"w"))==NULL) {
4818: printf("Problem with prevalence resultfile: %s\n", fileresp);
4819: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4820: exit(0);
4821: }
1.240 brouard 4822:
1.226 brouard 4823: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4824: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4825: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4826: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4827: fflush(ficlog);
4828: exit(70);
4829: }
4830: else{
4831: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4832: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4833: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4834: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4835: }
1.319 brouard 4836: 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 4837:
1.226 brouard 4838: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4839: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4840: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4841: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4842: fflush(ficlog);
4843: exit(70);
1.240 brouard 4844: } else{
1.226 brouard 4845: 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 4846: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4847: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4848: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4849: }
1.319 brouard 4850: 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 4851:
1.253 brouard 4852: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4853: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4854: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4855: j1=0;
1.126 brouard 4856:
1.227 brouard 4857: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4858: j=cptcoveff; /* Only dummy covariates of the model */
1.330 brouard 4859: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 4860: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4861:
4862:
1.226 brouard 4863: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4864: reference=low_education V1=0,V2=0
4865: med_educ V1=1 V2=0,
4866: high_educ V1=0 V2=1
1.330 brouard 4867: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 4868: */
1.249 brouard 4869: dateintsum=0;
4870: k2cpt=0;
4871:
1.253 brouard 4872: if(cptcoveff == 0 )
1.265 brouard 4873: nl=1; /* Constant and age model only */
1.253 brouard 4874: else
4875: nl=2;
1.265 brouard 4876:
4877: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4878: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.330 brouard 4879: * Loop on j1(1 to 2**cptcovn) covariate combination
1.265 brouard 4880: * freq[s1][s2][iage] =0.
4881: * Loop on iind
4882: * ++freq[s1][s2][iage] weighted
4883: * end iind
4884: * if covariate and j!0
4885: * headers Variable on one line
4886: * endif cov j!=0
4887: * header of frequency table by age
4888: * Loop on age
4889: * pp[s1]+=freq[s1][s2][iage] weighted
4890: * pos+=freq[s1][s2][iage] weighted
4891: * Loop on s1 initial state
4892: * fprintf(ficresp
4893: * end s1
4894: * end age
4895: * if j!=0 computes starting values
4896: * end compute starting values
4897: * end j1
4898: * end nl
4899: */
1.253 brouard 4900: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4901: if(nj==1)
4902: j=0; /* First pass for the constant */
1.265 brouard 4903: else{
1.330 brouard 4904: j=cptcovs; /* Other passes for the covariate values */
1.265 brouard 4905: }
1.251 brouard 4906: first=1;
1.265 brouard 4907: for (j1 = 1; j1 <= (int) pow(2,j); j1++){ /* Loop on all covariates combination of the model, excluding quantitatives, V4=0, V3=0 for example, fixed or varying covariates */
1.251 brouard 4908: posproptt=0.;
1.330 brouard 4909: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 4910: scanf("%d", i);*/
4911: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4912: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4913: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4914: freq[i][s2][m]=0;
1.251 brouard 4915:
4916: for (i=1; i<=nlstate; i++) {
1.240 brouard 4917: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4918: prop[i][m]=0;
4919: posprop[i]=0;
4920: pospropt[i]=0;
4921: }
1.283 brouard 4922: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4923: idq[z1]=0.;
4924: meanq[z1]=0.;
4925: stdq[z1]=0.;
1.283 brouard 4926: }
4927: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4928: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4929: /* meanqt[m][z1]=0.; */
4930: /* } */
4931: /* } */
1.251 brouard 4932: /* dateintsum=0; */
4933: /* k2cpt=0; */
4934:
1.265 brouard 4935: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4936: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4937: bool=1;
4938: if(j !=0){
4939: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.330 brouard 4940: if (cptcovn >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4941: for (z1=1; z1<=cptcovn; z1++) { /* loops on covariates in the model */
1.251 brouard 4942: /* if(Tvaraff[z1] ==-20){ */
4943: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4944: /* }else if(Tvaraff[z1] ==-10){ */
4945: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 4946: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
4947: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,Tvaraff[z1])]){ /* for combination j1 of covariates */
1.265 brouard 4948: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4949: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4950: /* 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",
4951: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4952: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4953: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4954: } /* Onlyf fixed */
4955: } /* end z1 */
4956: } /* cptcovn > 0 */
4957: } /* end any */
4958: }/* end j==0 */
1.265 brouard 4959: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4960: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4961: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4962: m=mw[mi][iind];
4963: if(j!=0){
4964: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.330 brouard 4965: for (z1=1; z1<=cptcovn; z1++) {
1.251 brouard 4966: if( Fixed[Tmodelind[z1]]==1){
4967: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
1.330 brouard 4968: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,Tvaraff[z1])]) /* iv=1 to ntv, right modality. If covariate's
1.251 brouard 4969: value is -1, we don't select. It differs from the
4970: constant and age model which counts them. */
4971: bool=0; /* not selected */
4972: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.330 brouard 4973: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,Tvaraff[z1])]) {
1.251 brouard 4974: bool=0;
4975: }
4976: }
4977: }
4978: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4979: } /* end j==0 */
4980: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4981: if(bool==1){ /*Selected */
1.251 brouard 4982: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4983: and mw[mi+1][iind]. dh depends on stepm. */
4984: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4985: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4986: if(m >=firstpass && m <=lastpass){
4987: k2=anint[m][iind]+(mint[m][iind]/12.);
4988: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4989: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4990: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4991: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4992: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4993: if (m<lastpass) {
4994: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4995: /* 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]); */
4996: if(s[m][iind]==-1)
4997: 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.));
4998: 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 4999: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5000: if(!isnan(covar[ncovcol+z1][iind])){
5001: idq[z1]=idq[z1]+weight[iind];
5002: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5003: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5004: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
5005: }
1.284 brouard 5006: }
1.251 brouard 5007: /* if((int)agev[m][iind] == 55) */
5008: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5009: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5010: 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 5011: }
1.251 brouard 5012: } /* end if between passes */
5013: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5014: dateintsum=dateintsum+k2; /* on all covariates ?*/
5015: k2cpt++;
5016: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5017: }
1.251 brouard 5018: }else{
5019: bool=1;
5020: }/* end bool 2 */
5021: } /* end m */
1.284 brouard 5022: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5023: /* idq[z1]=idq[z1]+weight[iind]; */
5024: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5025: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5026: /* } */
1.251 brouard 5027: } /* end bool */
5028: } /* end iind = 1 to imx */
1.319 brouard 5029: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5030: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5031:
5032:
5033: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.330 brouard 5034: if(cptcovn==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5035: pstamp(ficresp);
1.330 brouard 5036: if (cptcovn>0 && j!=0){
1.265 brouard 5037: pstamp(ficresp);
1.251 brouard 5038: printf( "\n#********** Variable ");
5039: fprintf(ficresp, "\n#********** Variable ");
5040: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5041: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5042: fprintf(ficlog, "\n#********** Variable ");
1.330 brouard 5043: for (z1=1; z1<=cptcovs; z1++){
1.251 brouard 5044: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5045: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5046: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5047: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5048: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5049: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5050: }else{
1.330 brouard 5051: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5052: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5053: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5054: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5055: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5056: }
5057: }
5058: printf( "**********\n#");
5059: fprintf(ficresp, "**********\n#");
5060: fprintf(ficresphtm, "**********</h3>\n");
5061: fprintf(ficresphtmfr, "**********</h3>\n");
5062: fprintf(ficlog, "**********\n");
5063: }
1.284 brouard 5064: /*
5065: Printing means of quantitative variables if any
5066: */
5067: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5068: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5069: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5070: if(weightopt==1){
5071: printf(" Weighted mean and standard deviation of");
5072: fprintf(ficlog," Weighted mean and standard deviation of");
5073: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5074: }
1.311 brouard 5075: /* mu = \frac{w x}{\sum w}
5076: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5077: */
5078: 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]));
5079: 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]));
5080: 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 5081: }
5082: /* for (z1=1; z1<= nqtveff; z1++) { */
5083: /* for(m=1;m<=lastpass;m++){ */
5084: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5085: /* } */
5086: /* } */
1.283 brouard 5087:
1.251 brouard 5088: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.330 brouard 5089: if((cptcovn==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5090: fprintf(ficresp, " Age");
1.330 brouard 5091: if(nj==2) for (z1=1; z1<=cptcovn; z1++) fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,Tvaraff[z1])]);
1.251 brouard 5092: for(i=1; i<=nlstate;i++) {
1.330 brouard 5093: if((cptcovn==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5094: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5095: }
1.330 brouard 5096: if((cptcovn==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5097: fprintf(ficresphtm, "\n");
5098:
5099: /* Header of frequency table by age */
5100: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5101: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5102: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5103: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5104: if(s2!=0 && m!=0)
5105: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5106: }
1.226 brouard 5107: }
1.251 brouard 5108: fprintf(ficresphtmfr, "\n");
5109:
5110: /* For each age */
5111: for(iage=iagemin; iage <= iagemax+3; iage++){
5112: fprintf(ficresphtm,"<tr>");
5113: if(iage==iagemax+1){
5114: fprintf(ficlog,"1");
5115: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5116: }else if(iage==iagemax+2){
5117: fprintf(ficlog,"0");
5118: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5119: }else if(iage==iagemax+3){
5120: fprintf(ficlog,"Total");
5121: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5122: }else{
1.240 brouard 5123: if(first==1){
1.251 brouard 5124: first=0;
5125: printf("See log file for details...\n");
5126: }
5127: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5128: fprintf(ficlog,"Age %d", iage);
5129: }
1.265 brouard 5130: for(s1=1; s1 <=nlstate ; s1++){
5131: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5132: pp[s1] += freq[s1][m][iage];
1.251 brouard 5133: }
1.265 brouard 5134: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5135: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5136: pos += freq[s1][m][iage];
5137: if(pp[s1]>=1.e-10){
1.251 brouard 5138: if(first==1){
1.265 brouard 5139: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5140: }
1.265 brouard 5141: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5142: }else{
5143: if(first==1)
1.265 brouard 5144: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5145: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5146: }
5147: }
5148:
1.265 brouard 5149: for(s1=1; s1 <=nlstate ; s1++){
5150: /* posprop[s1]=0; */
5151: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5152: pp[s1] += freq[s1][m][iage];
5153: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5154:
5155: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5156: pos += pp[s1]; /* pos is the total number of transitions until this age */
5157: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5158: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5159: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5160: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5161: }
5162:
5163: /* Writing ficresp */
1.330 brouard 5164: if(cptcovn==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5165: if( iage <= iagemax){
5166: fprintf(ficresp," %d",iage);
5167: }
5168: }else if( nj==2){
5169: if( iage <= iagemax){
5170: fprintf(ficresp," %d",iage);
1.330 brouard 5171: for (z1=1; z1<=cptcovn; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,Tvaraff[z1])]);
1.265 brouard 5172: }
1.240 brouard 5173: }
1.265 brouard 5174: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5175: if(pos>=1.e-5){
1.251 brouard 5176: if(first==1)
1.265 brouard 5177: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5178: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5179: }else{
5180: if(first==1)
1.265 brouard 5181: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5182: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5183: }
5184: if( iage <= iagemax){
5185: if(pos>=1.e-5){
1.330 brouard 5186: if(cptcovn==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5187: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5188: }else if( nj==2){
5189: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5190: }
5191: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5192: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5193: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5194: } else{
1.330 brouard 5195: if((cptcovn==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5196: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5197: }
1.240 brouard 5198: }
1.265 brouard 5199: pospropt[s1] +=posprop[s1];
5200: } /* end loop s1 */
1.251 brouard 5201: /* pospropt=0.; */
1.265 brouard 5202: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5203: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5204: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5205: if(first==1){
1.265 brouard 5206: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5207: }
1.265 brouard 5208: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5209: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5210: }
1.265 brouard 5211: if(s1!=0 && m!=0)
5212: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5213: }
1.265 brouard 5214: } /* end loop s1 */
1.251 brouard 5215: posproptt=0.;
1.265 brouard 5216: for(s1=1; s1 <=nlstate; s1++){
5217: posproptt += pospropt[s1];
1.251 brouard 5218: }
5219: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5220: fprintf(ficresphtm,"</tr>\n");
1.330 brouard 5221: if((cptcovn==0 && nj==1)|| nj==2 ) {
1.265 brouard 5222: if(iage <= iagemax)
5223: fprintf(ficresp,"\n");
1.240 brouard 5224: }
1.251 brouard 5225: if(first==1)
5226: printf("Others in log...\n");
5227: fprintf(ficlog,"\n");
5228: } /* end loop age iage */
1.265 brouard 5229:
1.251 brouard 5230: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5231: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5232: if(posproptt < 1.e-5){
1.265 brouard 5233: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5234: }else{
1.265 brouard 5235: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5236: }
1.226 brouard 5237: }
1.251 brouard 5238: fprintf(ficresphtm,"</tr>\n");
5239: fprintf(ficresphtm,"</table>\n");
5240: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5241: if(posproptt < 1.e-5){
1.251 brouard 5242: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5243: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5244: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5245: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5246: invalidvarcomb[j1]=1;
1.226 brouard 5247: }else{
1.251 brouard 5248: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
5249: invalidvarcomb[j1]=0;
1.226 brouard 5250: }
1.251 brouard 5251: fprintf(ficresphtmfr,"</table>\n");
5252: fprintf(ficlog,"\n");
5253: if(j!=0){
5254: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5255: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5256: for(k=1; k <=(nlstate+ndeath); k++){
5257: if (k != i) {
1.265 brouard 5258: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5259: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5260: if(j1==1){ /* All dummy covariates to zero */
5261: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5262: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5263: printf("%d%d ",i,k);
5264: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5265: 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]));
5266: 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]));
5267: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5268: }
1.253 brouard 5269: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5270: for(iage=iagemin; iage <= iagemax+3; iage++){
5271: x[iage]= (double)iage;
5272: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5273: /* 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 5274: }
1.268 brouard 5275: /* Some are not finite, but linreg will ignore these ages */
5276: no=0;
1.253 brouard 5277: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5278: pstart[s1]=b;
5279: pstart[s1-1]=a;
1.252 brouard 5280: }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 */
5281: 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]);
5282: 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 5283: 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 5284: printf("%d%d ",i,k);
5285: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5286: 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 5287: }else{ /* Other cases, like quantitative fixed or varying covariates */
5288: ;
5289: }
5290: /* printf("%12.7f )", param[i][jj][k]); */
5291: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5292: s1++;
1.251 brouard 5293: } /* end jj */
5294: } /* end k!= i */
5295: } /* end k */
1.265 brouard 5296: } /* end i, s1 */
1.251 brouard 5297: } /* end j !=0 */
5298: } /* end selected combination of covariate j1 */
5299: if(j==0){ /* We can estimate starting values from the occurences in each case */
5300: printf("#Freqsummary: Starting values for the constants:\n");
5301: fprintf(ficlog,"\n");
1.265 brouard 5302: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5303: for(k=1; k <=(nlstate+ndeath); k++){
5304: if (k != i) {
5305: printf("%d%d ",i,k);
5306: fprintf(ficlog,"%d%d ",i,k);
5307: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5308: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5309: if(jj==1){ /* Age has to be done */
1.265 brouard 5310: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5311: 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]));
5312: 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 5313: }
5314: /* printf("%12.7f )", param[i][jj][k]); */
5315: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5316: s1++;
1.250 brouard 5317: }
1.251 brouard 5318: printf("\n");
5319: fprintf(ficlog,"\n");
1.250 brouard 5320: }
5321: }
1.284 brouard 5322: } /* end of state i */
1.251 brouard 5323: printf("#Freqsummary\n");
5324: fprintf(ficlog,"\n");
1.265 brouard 5325: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5326: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5327: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5328: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5329: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5330: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5331: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5332: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5333: /* } */
5334: }
1.265 brouard 5335: } /* end loop s1 */
1.251 brouard 5336:
5337: printf("\n");
5338: fprintf(ficlog,"\n");
5339: } /* end j=0 */
1.249 brouard 5340: } /* end j */
1.252 brouard 5341:
1.253 brouard 5342: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5343: for(i=1, jk=1; i <=nlstate; i++){
5344: for(j=1; j <=nlstate+ndeath; j++){
5345: if(j!=i){
5346: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5347: printf("%1d%1d",i,j);
5348: fprintf(ficparo,"%1d%1d",i,j);
5349: for(k=1; k<=ncovmodel;k++){
5350: /* printf(" %lf",param[i][j][k]); */
5351: /* fprintf(ficparo," %lf",param[i][j][k]); */
5352: p[jk]=pstart[jk];
5353: printf(" %f ",pstart[jk]);
5354: fprintf(ficparo," %f ",pstart[jk]);
5355: jk++;
5356: }
5357: printf("\n");
5358: fprintf(ficparo,"\n");
5359: }
5360: }
5361: }
5362: } /* end mle=-2 */
1.226 brouard 5363: dateintmean=dateintsum/k2cpt;
1.296 brouard 5364: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5365:
1.226 brouard 5366: fclose(ficresp);
5367: fclose(ficresphtm);
5368: fclose(ficresphtmfr);
1.283 brouard 5369: free_vector(idq,1,nqfveff);
1.226 brouard 5370: free_vector(meanq,1,nqfveff);
1.284 brouard 5371: free_vector(stdq,1,nqfveff);
1.226 brouard 5372: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5373: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5374: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5375: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5376: free_vector(pospropt,1,nlstate);
5377: free_vector(posprop,1,nlstate);
1.251 brouard 5378: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5379: free_vector(pp,1,nlstate);
5380: /* End of freqsummary */
5381: }
1.126 brouard 5382:
1.268 brouard 5383: /* Simple linear regression */
5384: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5385:
5386: /* y=a+bx regression */
5387: double sumx = 0.0; /* sum of x */
5388: double sumx2 = 0.0; /* sum of x**2 */
5389: double sumxy = 0.0; /* sum of x * y */
5390: double sumy = 0.0; /* sum of y */
5391: double sumy2 = 0.0; /* sum of y**2 */
5392: double sume2 = 0.0; /* sum of square or residuals */
5393: double yhat;
5394:
5395: double denom=0;
5396: int i;
5397: int ne=*no;
5398:
5399: for ( i=ifi, ne=0;i<=ila;i++) {
5400: if(!isfinite(x[i]) || !isfinite(y[i])){
5401: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5402: continue;
5403: }
5404: ne=ne+1;
5405: sumx += x[i];
5406: sumx2 += x[i]*x[i];
5407: sumxy += x[i] * y[i];
5408: sumy += y[i];
5409: sumy2 += y[i]*y[i];
5410: denom = (ne * sumx2 - sumx*sumx);
5411: /* 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); */
5412: }
5413:
5414: denom = (ne * sumx2 - sumx*sumx);
5415: if (denom == 0) {
5416: // vertical, slope m is infinity
5417: *b = INFINITY;
5418: *a = 0;
5419: if (r) *r = 0;
5420: return 1;
5421: }
5422:
5423: *b = (ne * sumxy - sumx * sumy) / denom;
5424: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5425: if (r!=NULL) {
5426: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5427: sqrt((sumx2 - sumx*sumx/ne) *
5428: (sumy2 - sumy*sumy/ne));
5429: }
5430: *no=ne;
5431: for ( i=ifi, ne=0;i<=ila;i++) {
5432: if(!isfinite(x[i]) || !isfinite(y[i])){
5433: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5434: continue;
5435: }
5436: ne=ne+1;
5437: yhat = y[i] - *a -*b* x[i];
5438: sume2 += yhat * yhat ;
5439:
5440: denom = (ne * sumx2 - sumx*sumx);
5441: /* 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); */
5442: }
5443: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5444: *sa= *sb * sqrt(sumx2/ne);
5445:
5446: return 0;
5447: }
5448:
1.126 brouard 5449: /************ Prevalence ********************/
1.227 brouard 5450: 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)
5451: {
5452: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5453: in each health status at the date of interview (if between dateprev1 and dateprev2).
5454: We still use firstpass and lastpass as another selection.
5455: */
1.126 brouard 5456:
1.227 brouard 5457: int i, m, jk, j1, bool, z1,j, iv;
5458: int mi; /* Effective wave */
5459: int iage;
5460: double agebegin, ageend;
5461:
5462: double **prop;
5463: double posprop;
5464: double y2; /* in fractional years */
5465: int iagemin, iagemax;
5466: int first; /** to stop verbosity which is redirected to log file */
5467:
5468: iagemin= (int) agemin;
5469: iagemax= (int) agemax;
5470: /*pp=vector(1,nlstate);*/
1.251 brouard 5471: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5472: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5473: j1=0;
1.222 brouard 5474:
1.227 brouard 5475: /*j=cptcoveff;*/
5476: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5477:
1.288 brouard 5478: first=0;
1.227 brouard 5479: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5480: for (i=1; i<=nlstate; i++)
1.251 brouard 5481: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5482: prop[i][iage]=0.0;
5483: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5484: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5485: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5486:
5487: for (i=1; i<=imx; i++) { /* Each individual */
5488: bool=1;
5489: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5490: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5491: m=mw[mi][i];
5492: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5493: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5494: for (z1=1; z1<=cptcoveff; z1++){
5495: if( Fixed[Tmodelind[z1]]==1){
5496: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
1.330 brouard 5497: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,Tvaraff[z1])]) /* iv=1 to ntv, right modality */
1.227 brouard 5498: bool=0;
5499: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.330 brouard 5500: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,Tvaraff[z1])]) {
1.227 brouard 5501: bool=0;
5502: }
5503: }
5504: if(bool==1){ /* Otherwise we skip that wave/person */
5505: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5506: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5507: if(m >=firstpass && m <=lastpass){
5508: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5509: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5510: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5511: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5512: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5513: 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);
5514: exit(1);
5515: }
5516: if (s[m][i]>0 && s[m][i]<=nlstate) {
5517: /*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]]);*/
5518: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5519: prop[s[m][i]][iagemax+3] += weight[i];
5520: } /* end valid statuses */
5521: } /* end selection of dates */
5522: } /* end selection of waves */
5523: } /* end bool */
5524: } /* end wave */
5525: } /* end individual */
5526: for(i=iagemin; i <= iagemax+3; i++){
5527: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5528: posprop += prop[jk][i];
5529: }
5530:
5531: for(jk=1; jk <=nlstate ; jk++){
5532: if( i <= iagemax){
5533: if(posprop>=1.e-5){
5534: probs[i][jk][j1]= prop[jk][i]/posprop;
5535: } else{
1.288 brouard 5536: if(!first){
5537: first=1;
1.266 brouard 5538: 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]);
5539: }else{
1.288 brouard 5540: 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 5541: }
5542: }
5543: }
5544: }/* end jk */
5545: }/* end i */
1.222 brouard 5546: /*} *//* end i1 */
1.227 brouard 5547: } /* end j1 */
1.222 brouard 5548:
1.227 brouard 5549: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5550: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5551: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5552: } /* End of prevalence */
1.126 brouard 5553:
5554: /************* Waves Concatenation ***************/
5555:
5556: 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)
5557: {
1.298 brouard 5558: /* 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 5559: Death is a valid wave (if date is known).
5560: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5561: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 5562: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 5563: */
1.126 brouard 5564:
1.224 brouard 5565: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5566: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5567: double sum=0., jmean=0.;*/
1.224 brouard 5568: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5569: int j, k=0,jk, ju, jl;
5570: double sum=0.;
5571: first=0;
1.214 brouard 5572: firstwo=0;
1.217 brouard 5573: firsthree=0;
1.218 brouard 5574: firstfour=0;
1.164 brouard 5575: jmin=100000;
1.126 brouard 5576: jmax=-1;
5577: jmean=0.;
1.224 brouard 5578:
5579: /* Treating live states */
1.214 brouard 5580: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5581: mi=0; /* First valid wave */
1.227 brouard 5582: mli=0; /* Last valid wave */
1.309 brouard 5583: m=firstpass; /* Loop on waves */
5584: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 5585: 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 */
5586: mli=m-1;/* mw[++mi][i]=m-1; */
5587: }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 5588: 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 5589: mli=m;
1.224 brouard 5590: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5591: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5592: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5593: }
1.309 brouard 5594: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 5595: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5596: break;
1.224 brouard 5597: #else
1.317 brouard 5598: 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 5599: if(firsthree == 0){
1.302 brouard 5600: 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 5601: firsthree=1;
1.317 brouard 5602: }else if(firsthree >=1 && firsthree < 10){
5603: 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);
5604: firsthree++;
5605: }else if(firsthree == 10){
5606: printf("Information, too many Information flags: no more reported to log either\n");
5607: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
5608: firsthree++;
5609: }else{
5610: firsthree++;
1.227 brouard 5611: }
1.309 brouard 5612: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 5613: mli=m;
5614: }
5615: if(s[m][i]==-2){ /* Vital status is really unknown */
5616: nbwarn++;
1.309 brouard 5617: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 5618: 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);
5619: 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);
5620: }
5621: break;
5622: }
5623: break;
1.224 brouard 5624: #endif
1.227 brouard 5625: }/* End m >= lastpass */
1.126 brouard 5626: }/* end while */
1.224 brouard 5627:
1.227 brouard 5628: /* 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 5629: /* After last pass */
1.224 brouard 5630: /* Treating death states */
1.214 brouard 5631: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5632: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5633: /* } */
1.126 brouard 5634: mi++; /* Death is another wave */
5635: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5636: /* Only death is a correct wave */
1.126 brouard 5637: mw[mi][i]=m;
1.257 brouard 5638: } /* else not in a death state */
1.224 brouard 5639: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5640: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5641: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 5642: 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 5643: nbwarn++;
5644: if(firstfiv==0){
1.309 brouard 5645: 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 5646: firstfiv=1;
5647: }else{
1.309 brouard 5648: 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 5649: }
1.309 brouard 5650: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
5651: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 5652: nberr++;
5653: if(firstwo==0){
1.309 brouard 5654: 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 5655: firstwo=1;
5656: }
1.309 brouard 5657: 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 5658: }
1.257 brouard 5659: }else{ /* if date of interview is unknown */
1.227 brouard 5660: /* death is known but not confirmed by death status at any wave */
5661: if(firstfour==0){
1.309 brouard 5662: 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 5663: firstfour=1;
5664: }
1.309 brouard 5665: 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 5666: }
1.224 brouard 5667: } /* end if date of death is known */
5668: #endif
1.309 brouard 5669: wav[i]=mi; /* mi should be the last effective wave (or mli), */
5670: /* wav[i]=mw[mi][i]; */
1.126 brouard 5671: if(mi==0){
5672: nbwarn++;
5673: if(first==0){
1.227 brouard 5674: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5675: first=1;
1.126 brouard 5676: }
5677: if(first==1){
1.227 brouard 5678: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5679: }
5680: } /* end mi==0 */
5681: } /* End individuals */
1.214 brouard 5682: /* wav and mw are no more changed */
1.223 brouard 5683:
1.317 brouard 5684: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
5685: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
5686:
5687:
1.126 brouard 5688: for(i=1; i<=imx; i++){
5689: for(mi=1; mi<wav[i];mi++){
5690: if (stepm <=0)
1.227 brouard 5691: dh[mi][i]=1;
1.126 brouard 5692: else{
1.260 brouard 5693: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5694: if (agedc[i] < 2*AGESUP) {
5695: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5696: if(j==0) j=1; /* Survives at least one month after exam */
5697: else if(j<0){
5698: nberr++;
5699: 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]);
5700: j=1; /* Temporary Dangerous patch */
5701: 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);
5702: 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]);
5703: 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);
5704: }
5705: k=k+1;
5706: if (j >= jmax){
5707: jmax=j;
5708: ijmax=i;
5709: }
5710: if (j <= jmin){
5711: jmin=j;
5712: ijmin=i;
5713: }
5714: sum=sum+j;
5715: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5716: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5717: }
5718: }
5719: else{
5720: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5721: /* 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 5722:
1.227 brouard 5723: k=k+1;
5724: if (j >= jmax) {
5725: jmax=j;
5726: ijmax=i;
5727: }
5728: else if (j <= jmin){
5729: jmin=j;
5730: ijmin=i;
5731: }
5732: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5733: /*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]);*/
5734: if(j<0){
5735: nberr++;
5736: 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]);
5737: 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]);
5738: }
5739: sum=sum+j;
5740: }
5741: jk= j/stepm;
5742: jl= j -jk*stepm;
5743: ju= j -(jk+1)*stepm;
5744: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5745: if(jl==0){
5746: dh[mi][i]=jk;
5747: bh[mi][i]=0;
5748: }else{ /* We want a negative bias in order to only have interpolation ie
5749: * to avoid the price of an extra matrix product in likelihood */
5750: dh[mi][i]=jk+1;
5751: bh[mi][i]=ju;
5752: }
5753: }else{
5754: if(jl <= -ju){
5755: dh[mi][i]=jk;
5756: bh[mi][i]=jl; /* bias is positive if real duration
5757: * is higher than the multiple of stepm and negative otherwise.
5758: */
5759: }
5760: else{
5761: dh[mi][i]=jk+1;
5762: bh[mi][i]=ju;
5763: }
5764: if(dh[mi][i]==0){
5765: dh[mi][i]=1; /* At least one step */
5766: bh[mi][i]=ju; /* At least one step */
5767: /* 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);*/
5768: }
5769: } /* end if mle */
1.126 brouard 5770: }
5771: } /* end wave */
5772: }
5773: jmean=sum/k;
5774: 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 5775: 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 5776: }
1.126 brouard 5777:
5778: /*********** Tricode ****************************/
1.220 brouard 5779: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5780: {
5781: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5782: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5783: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5784: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5785: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5786: */
1.130 brouard 5787:
1.242 brouard 5788: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5789: int modmaxcovj=0; /* Modality max of covariates j */
5790: int cptcode=0; /* Modality max of covariates j */
5791: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5792:
5793:
1.242 brouard 5794: /* cptcoveff=0; */
5795: /* *cptcov=0; */
1.126 brouard 5796:
1.242 brouard 5797: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5798: for (k=1; k <= maxncov; k++)
5799: for(j=1; j<=2; j++)
5800: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5801:
1.242 brouard 5802: /* Loop on covariates without age and products and no quantitative variable */
5803: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5804: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5805: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5806: switch(Fixed[k]) {
5807: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 5808: modmaxcovj=0;
5809: modmincovj=0;
1.242 brouard 5810: 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*/
5811: ij=(int)(covar[Tvar[k]][i]);
5812: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5813: * If product of Vn*Vm, still boolean *:
5814: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5815: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5816: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5817: modality of the nth covariate of individual i. */
5818: if (ij > modmaxcovj)
5819: modmaxcovj=ij;
5820: else if (ij < modmincovj)
5821: modmincovj=ij;
1.287 brouard 5822: if (ij <0 || ij >1 ){
1.311 brouard 5823: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5824: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5825: fflush(ficlog);
5826: exit(1);
1.287 brouard 5827: }
5828: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5829: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5830: exit(1);
5831: }else
5832: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5833: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5834: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5835: /* getting the maximum value of the modality of the covariate
5836: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5837: female ies 1, then modmaxcovj=1.
5838: */
5839: } /* end for loop on individuals i */
5840: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5841: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5842: cptcode=modmaxcovj;
5843: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5844: /*for (i=0; i<=cptcode; i++) {*/
5845: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5846: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5847: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5848: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5849: if( j != -1){
5850: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5851: covariate for which somebody answered excluding
5852: undefined. Usually 2: 0 and 1. */
5853: }
5854: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5855: covariate for which somebody answered including
5856: undefined. Usually 3: -1, 0 and 1. */
5857: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5858: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5859: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5860:
1.242 brouard 5861: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5862: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5863: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5864: /* modmincovj=3; modmaxcovj = 7; */
5865: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5866: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5867: /* defining two dummy variables: variables V1_1 and V1_2.*/
5868: /* nbcode[Tvar[j]][ij]=k; */
5869: /* nbcode[Tvar[j]][1]=0; */
5870: /* nbcode[Tvar[j]][2]=1; */
5871: /* nbcode[Tvar[j]][3]=2; */
5872: /* To be continued (not working yet). */
5873: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5874:
5875: /* 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*/
5876: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5877: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5878: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5879: /*, could be restored in the future */
5880: 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 5881: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5882: break;
5883: }
5884: ij++;
1.287 brouard 5885: 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 5886: cptcode = ij; /* New max modality for covar j */
5887: } /* end of loop on modality i=-1 to 1 or more */
5888: break;
5889: case 1: /* Testing on varying covariate, could be simple and
5890: * should look at waves or product of fixed *
5891: * varying. No time to test -1, assuming 0 and 1 only */
5892: ij=0;
5893: for(i=0; i<=1;i++){
5894: nbcode[Tvar[k]][++ij]=i;
5895: }
5896: break;
5897: default:
5898: break;
5899: } /* end switch */
5900: } /* end dummy test */
1.311 brouard 5901: if(Dummy[k]==1 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5902: 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*/
5903: if(isnan(covar[Tvar[k]][i])){
5904: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5905: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5906: fflush(ficlog);
5907: exit(1);
5908: }
5909: }
5910: }
1.287 brouard 5911: } /* 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 5912:
5913: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5914: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5915: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5916: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5917: 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 */
5918: 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 */
5919: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5920: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5921:
5922: ij=0;
5923: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5924: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5925: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5926: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5927: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5928: /* If product not in single variable we don't print results */
5929: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5930: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5931: 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*/
5932: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5933: 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 */
5934: if(Fixed[k]!=0)
5935: anyvaryingduminmodel=1;
5936: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5937: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5938: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5939: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5940: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5941: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5942: }
5943: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5944: /* ij--; */
5945: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.330 brouard 5946: *cptcov=ij; /* cptcov= Number of total real effective covariates: effective (used as cptcoveff in other functions)
1.242 brouard 5947: * because they can be excluded from the model and real
5948: * if in the model but excluded because missing values, but how to get k from ij?*/
5949: for(j=ij+1; j<= cptcovt; j++){
5950: Tvaraff[j]=0;
5951: Tmodelind[j]=0;
5952: }
5953: for(j=ntveff+1; j<= cptcovt; j++){
5954: TmodelInvind[j]=0;
5955: }
5956: /* To be sorted */
5957: ;
5958: }
1.126 brouard 5959:
1.145 brouard 5960:
1.126 brouard 5961: /*********** Health Expectancies ****************/
5962:
1.235 brouard 5963: 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 5964:
5965: {
5966: /* Health expectancies, no variances */
1.329 brouard 5967: /* cij is the combination in the list of combination of dummy covariates */
5968: /* strstart is a string of time at start of computing */
1.164 brouard 5969: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5970: int nhstepma, nstepma; /* Decreasing with age */
5971: double age, agelim, hf;
5972: double ***p3mat;
5973: double eip;
5974:
1.238 brouard 5975: /* pstamp(ficreseij); */
1.126 brouard 5976: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5977: fprintf(ficreseij,"# Age");
5978: for(i=1; i<=nlstate;i++){
5979: for(j=1; j<=nlstate;j++){
5980: fprintf(ficreseij," e%1d%1d ",i,j);
5981: }
5982: fprintf(ficreseij," e%1d. ",i);
5983: }
5984: fprintf(ficreseij,"\n");
5985:
5986:
5987: if(estepm < stepm){
5988: printf ("Problem %d lower than %d\n",estepm, stepm);
5989: }
5990: else hstepm=estepm;
5991: /* We compute the life expectancy from trapezoids spaced every estepm months
5992: * This is mainly to measure the difference between two models: for example
5993: * if stepm=24 months pijx are given only every 2 years and by summing them
5994: * we are calculating an estimate of the Life Expectancy assuming a linear
5995: * progression in between and thus overestimating or underestimating according
5996: * to the curvature of the survival function. If, for the same date, we
5997: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5998: * to compare the new estimate of Life expectancy with the same linear
5999: * hypothesis. A more precise result, taking into account a more precise
6000: * curvature will be obtained if estepm is as small as stepm. */
6001:
6002: /* For example we decided to compute the life expectancy with the smallest unit */
6003: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6004: nhstepm is the number of hstepm from age to agelim
6005: nstepm is the number of stepm from age to agelin.
1.270 brouard 6006: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6007: and note for a fixed period like estepm months */
6008: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6009: survival function given by stepm (the optimization length). Unfortunately it
6010: means that if the survival funtion is printed only each two years of age and if
6011: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6012: results. So we changed our mind and took the option of the best precision.
6013: */
6014: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6015:
6016: agelim=AGESUP;
6017: /* If stepm=6 months */
6018: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6019: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6020:
6021: /* nhstepm age range expressed in number of stepm */
6022: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6023: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6024: /* if (stepm >= YEARM) hstepm=1;*/
6025: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6026: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6027:
6028: for (age=bage; age<=fage; age ++){
6029: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6030: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6031: /* if (stepm >= YEARM) hstepm=1;*/
6032: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6033:
6034: /* If stepm=6 months */
6035: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6036: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6037: /* 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 6038: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6039:
6040: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6041:
6042: printf("%d|",(int)age);fflush(stdout);
6043: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6044:
6045: /* Computing expectancies */
6046: for(i=1; i<=nlstate;i++)
6047: for(j=1; j<=nlstate;j++)
6048: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6049: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6050:
6051: /* 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]);*/
6052:
6053: }
6054:
6055: fprintf(ficreseij,"%3.0f",age );
6056: for(i=1; i<=nlstate;i++){
6057: eip=0;
6058: for(j=1; j<=nlstate;j++){
6059: eip +=eij[i][j][(int)age];
6060: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6061: }
6062: fprintf(ficreseij,"%9.4f", eip );
6063: }
6064: fprintf(ficreseij,"\n");
6065:
6066: }
6067: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6068: printf("\n");
6069: fprintf(ficlog,"\n");
6070:
6071: }
6072:
1.235 brouard 6073: 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 6074:
6075: {
6076: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6077: to initial status i, ei. .
1.126 brouard 6078: */
6079: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6080: int nhstepma, nstepma; /* Decreasing with age */
6081: double age, agelim, hf;
6082: double ***p3matp, ***p3matm, ***varhe;
6083: double **dnewm,**doldm;
6084: double *xp, *xm;
6085: double **gp, **gm;
6086: double ***gradg, ***trgradg;
6087: int theta;
6088:
6089: double eip, vip;
6090:
6091: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6092: xp=vector(1,npar);
6093: xm=vector(1,npar);
6094: dnewm=matrix(1,nlstate*nlstate,1,npar);
6095: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6096:
6097: pstamp(ficresstdeij);
6098: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6099: fprintf(ficresstdeij,"# Age");
6100: for(i=1; i<=nlstate;i++){
6101: for(j=1; j<=nlstate;j++)
6102: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6103: fprintf(ficresstdeij," e%1d. ",i);
6104: }
6105: fprintf(ficresstdeij,"\n");
6106:
6107: pstamp(ficrescveij);
6108: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6109: fprintf(ficrescveij,"# Age");
6110: for(i=1; i<=nlstate;i++)
6111: for(j=1; j<=nlstate;j++){
6112: cptj= (j-1)*nlstate+i;
6113: for(i2=1; i2<=nlstate;i2++)
6114: for(j2=1; j2<=nlstate;j2++){
6115: cptj2= (j2-1)*nlstate+i2;
6116: if(cptj2 <= cptj)
6117: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6118: }
6119: }
6120: fprintf(ficrescveij,"\n");
6121:
6122: if(estepm < stepm){
6123: printf ("Problem %d lower than %d\n",estepm, stepm);
6124: }
6125: else hstepm=estepm;
6126: /* We compute the life expectancy from trapezoids spaced every estepm months
6127: * This is mainly to measure the difference between two models: for example
6128: * if stepm=24 months pijx are given only every 2 years and by summing them
6129: * we are calculating an estimate of the Life Expectancy assuming a linear
6130: * progression in between and thus overestimating or underestimating according
6131: * to the curvature of the survival function. If, for the same date, we
6132: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6133: * to compare the new estimate of Life expectancy with the same linear
6134: * hypothesis. A more precise result, taking into account a more precise
6135: * curvature will be obtained if estepm is as small as stepm. */
6136:
6137: /* For example we decided to compute the life expectancy with the smallest unit */
6138: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6139: nhstepm is the number of hstepm from age to agelim
6140: nstepm is the number of stepm from age to agelin.
6141: Look at hpijx to understand the reason of that which relies in memory size
6142: and note for a fixed period like estepm months */
6143: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6144: survival function given by stepm (the optimization length). Unfortunately it
6145: means that if the survival funtion is printed only each two years of age and if
6146: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6147: results. So we changed our mind and took the option of the best precision.
6148: */
6149: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6150:
6151: /* If stepm=6 months */
6152: /* nhstepm age range expressed in number of stepm */
6153: agelim=AGESUP;
6154: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6155: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6156: /* if (stepm >= YEARM) hstepm=1;*/
6157: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6158:
6159: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6160: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6161: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6162: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6163: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6164: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6165:
6166: for (age=bage; age<=fage; age ++){
6167: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6168: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6169: /* if (stepm >= YEARM) hstepm=1;*/
6170: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6171:
1.126 brouard 6172: /* If stepm=6 months */
6173: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6174: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6175:
6176: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6177:
1.126 brouard 6178: /* Computing Variances of health expectancies */
6179: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6180: decrease memory allocation */
6181: for(theta=1; theta <=npar; theta++){
6182: for(i=1; i<=npar; i++){
1.222 brouard 6183: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6184: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6185: }
1.235 brouard 6186: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6187: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6188:
1.126 brouard 6189: for(j=1; j<= nlstate; j++){
1.222 brouard 6190: for(i=1; i<=nlstate; i++){
6191: for(h=0; h<=nhstepm-1; h++){
6192: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6193: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6194: }
6195: }
1.126 brouard 6196: }
1.218 brouard 6197:
1.126 brouard 6198: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6199: for(h=0; h<=nhstepm-1; h++){
6200: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6201: }
1.126 brouard 6202: }/* End theta */
6203:
6204:
6205: for(h=0; h<=nhstepm-1; h++)
6206: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6207: for(theta=1; theta <=npar; theta++)
6208: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6209:
1.218 brouard 6210:
1.222 brouard 6211: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6212: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6213: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6214:
1.222 brouard 6215: printf("%d|",(int)age);fflush(stdout);
6216: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6217: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6218: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6219: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6220: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6221: for(ij=1;ij<=nlstate*nlstate;ij++)
6222: for(ji=1;ji<=nlstate*nlstate;ji++)
6223: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6224: }
6225: }
1.320 brouard 6226: /* if((int)age ==50){ */
6227: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6228: /* } */
1.126 brouard 6229: /* Computing expectancies */
1.235 brouard 6230: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6231: for(i=1; i<=nlstate;i++)
6232: for(j=1; j<=nlstate;j++)
1.222 brouard 6233: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6234: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6235:
1.222 brouard 6236: /* 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 6237:
1.222 brouard 6238: }
1.269 brouard 6239:
6240: /* Standard deviation of expectancies ij */
1.126 brouard 6241: fprintf(ficresstdeij,"%3.0f",age );
6242: for(i=1; i<=nlstate;i++){
6243: eip=0.;
6244: vip=0.;
6245: for(j=1; j<=nlstate;j++){
1.222 brouard 6246: eip += eij[i][j][(int)age];
6247: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6248: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6249: 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 6250: }
6251: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6252: }
6253: fprintf(ficresstdeij,"\n");
1.218 brouard 6254:
1.269 brouard 6255: /* Variance of expectancies ij */
1.126 brouard 6256: fprintf(ficrescveij,"%3.0f",age );
6257: for(i=1; i<=nlstate;i++)
6258: for(j=1; j<=nlstate;j++){
1.222 brouard 6259: cptj= (j-1)*nlstate+i;
6260: for(i2=1; i2<=nlstate;i2++)
6261: for(j2=1; j2<=nlstate;j2++){
6262: cptj2= (j2-1)*nlstate+i2;
6263: if(cptj2 <= cptj)
6264: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6265: }
1.126 brouard 6266: }
6267: fprintf(ficrescveij,"\n");
1.218 brouard 6268:
1.126 brouard 6269: }
6270: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6271: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6272: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6273: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6274: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6275: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6276: printf("\n");
6277: fprintf(ficlog,"\n");
1.218 brouard 6278:
1.126 brouard 6279: free_vector(xm,1,npar);
6280: free_vector(xp,1,npar);
6281: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6282: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6283: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6284: }
1.218 brouard 6285:
1.126 brouard 6286: /************ Variance ******************/
1.235 brouard 6287: 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 6288: {
1.279 brouard 6289: /** Variance of health expectancies
6290: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6291: * double **newm;
6292: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6293: */
1.218 brouard 6294:
6295: /* int movingaverage(); */
6296: double **dnewm,**doldm;
6297: double **dnewmp,**doldmp;
6298: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6299: int first=0;
1.218 brouard 6300: int k;
6301: double *xp;
1.279 brouard 6302: double **gp, **gm; /**< for var eij */
6303: double ***gradg, ***trgradg; /**< for var eij */
6304: double **gradgp, **trgradgp; /**< for var p point j */
6305: double *gpp, *gmp; /**< for var p point j */
6306: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6307: double ***p3mat;
6308: double age,agelim, hf;
6309: /* double ***mobaverage; */
6310: int theta;
6311: char digit[4];
6312: char digitp[25];
6313:
6314: char fileresprobmorprev[FILENAMELENGTH];
6315:
6316: if(popbased==1){
6317: if(mobilav!=0)
6318: strcpy(digitp,"-POPULBASED-MOBILAV_");
6319: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6320: }
6321: else
6322: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6323:
1.218 brouard 6324: /* if (mobilav!=0) { */
6325: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6326: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
6327: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
6328: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
6329: /* } */
6330: /* } */
6331:
6332: strcpy(fileresprobmorprev,"PRMORPREV-");
6333: sprintf(digit,"%-d",ij);
6334: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
6335: strcat(fileresprobmorprev,digit); /* Tvar to be done */
6336: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
6337: strcat(fileresprobmorprev,fileresu);
6338: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
6339: printf("Problem with resultfile: %s\n", fileresprobmorprev);
6340: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
6341: }
6342: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6343: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6344: pstamp(ficresprobmorprev);
6345: 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 6346: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
6347: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
6348: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
6349: }
6350: for(j=1;j<=cptcoveff;j++)
1.330 brouard 6351: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,Tvaraff[j])]);
1.238 brouard 6352: fprintf(ficresprobmorprev,"\n");
6353:
1.218 brouard 6354: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
6355: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6356: fprintf(ficresprobmorprev," p.%-d SE",j);
6357: for(i=1; i<=nlstate;i++)
6358: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
6359: }
6360: fprintf(ficresprobmorprev,"\n");
6361:
6362: fprintf(ficgp,"\n# Routine varevsij");
6363: fprintf(ficgp,"\nunset title \n");
6364: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
6365: 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");
6366: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 6367:
1.218 brouard 6368: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6369: pstamp(ficresvij);
6370: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
6371: if(popbased==1)
6372: 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);
6373: else
6374: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6375: fprintf(ficresvij,"# Age");
6376: for(i=1; i<=nlstate;i++)
6377: for(j=1; j<=nlstate;j++)
6378: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6379: fprintf(ficresvij,"\n");
6380:
6381: xp=vector(1,npar);
6382: dnewm=matrix(1,nlstate,1,npar);
6383: doldm=matrix(1,nlstate,1,nlstate);
6384: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6385: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6386:
6387: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6388: gpp=vector(nlstate+1,nlstate+ndeath);
6389: gmp=vector(nlstate+1,nlstate+ndeath);
6390: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6391:
1.218 brouard 6392: if(estepm < stepm){
6393: printf ("Problem %d lower than %d\n",estepm, stepm);
6394: }
6395: else hstepm=estepm;
6396: /* For example we decided to compute the life expectancy with the smallest unit */
6397: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6398: nhstepm is the number of hstepm from age to agelim
6399: nstepm is the number of stepm from age to agelim.
6400: Look at function hpijx to understand why because of memory size limitations,
6401: we decided (b) to get a life expectancy respecting the most precise curvature of the
6402: survival function given by stepm (the optimization length). Unfortunately it
6403: means that if the survival funtion is printed every two years of age and if
6404: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6405: results. So we changed our mind and took the option of the best precision.
6406: */
6407: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6408: agelim = AGESUP;
6409: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6410: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6411: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6412: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6413: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6414: gp=matrix(0,nhstepm,1,nlstate);
6415: gm=matrix(0,nhstepm,1,nlstate);
6416:
6417:
6418: for(theta=1; theta <=npar; theta++){
6419: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6420: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6421: }
1.279 brouard 6422: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6423: * returns into prlim .
1.288 brouard 6424: */
1.242 brouard 6425: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6426:
6427: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6428: if (popbased==1) {
6429: if(mobilav ==0){
6430: for(i=1; i<=nlstate;i++)
6431: prlim[i][i]=probs[(int)age][i][ij];
6432: }else{ /* mobilav */
6433: for(i=1; i<=nlstate;i++)
6434: prlim[i][i]=mobaverage[(int)age][i][ij];
6435: }
6436: }
1.295 brouard 6437: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6438: */
6439: 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 6440: /**< 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 6441: * at horizon h in state j including mortality.
6442: */
1.218 brouard 6443: for(j=1; j<= nlstate; j++){
6444: for(h=0; h<=nhstepm; h++){
6445: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6446: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6447: }
6448: }
1.279 brouard 6449: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6450: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6451: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6452: */
6453: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6454: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6455: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6456: }
6457:
6458: /* Again with minus shift */
1.218 brouard 6459:
6460: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6461: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6462:
1.242 brouard 6463: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6464:
6465: if (popbased==1) {
6466: if(mobilav ==0){
6467: for(i=1; i<=nlstate;i++)
6468: prlim[i][i]=probs[(int)age][i][ij];
6469: }else{ /* mobilav */
6470: for(i=1; i<=nlstate;i++)
6471: prlim[i][i]=mobaverage[(int)age][i][ij];
6472: }
6473: }
6474:
1.235 brouard 6475: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6476:
6477: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6478: for(h=0; h<=nhstepm; h++){
6479: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6480: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6481: }
6482: }
6483: /* This for computing probability of death (h=1 means
6484: computed over hstepm matrices product = hstepm*stepm months)
6485: as a weighted average of prlim.
6486: */
6487: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6488: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6489: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6490: }
1.279 brouard 6491: /* end shifting computations */
6492:
6493: /**< Computing gradient matrix at horizon h
6494: */
1.218 brouard 6495: for(j=1; j<= nlstate; j++) /* vareij */
6496: for(h=0; h<=nhstepm; h++){
6497: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6498: }
1.279 brouard 6499: /**< Gradient of overall mortality p.3 (or p.j)
6500: */
6501: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6502: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6503: }
6504:
6505: } /* End theta */
1.279 brouard 6506:
6507: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6508: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6509:
6510: for(h=0; h<=nhstepm; h++) /* veij */
6511: for(j=1; j<=nlstate;j++)
6512: for(theta=1; theta <=npar; theta++)
6513: trgradg[h][j][theta]=gradg[h][theta][j];
6514:
6515: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6516: for(theta=1; theta <=npar; theta++)
6517: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6518: /**< as well as its transposed matrix
6519: */
1.218 brouard 6520:
6521: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6522: for(i=1;i<=nlstate;i++)
6523: for(j=1;j<=nlstate;j++)
6524: vareij[i][j][(int)age] =0.;
1.279 brouard 6525:
6526: /* Computing trgradg by matcov by gradg at age and summing over h
6527: * and k (nhstepm) formula 15 of article
6528: * Lievre-Brouard-Heathcote
6529: */
6530:
1.218 brouard 6531: for(h=0;h<=nhstepm;h++){
6532: for(k=0;k<=nhstepm;k++){
6533: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6534: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6535: for(i=1;i<=nlstate;i++)
6536: for(j=1;j<=nlstate;j++)
6537: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6538: }
6539: }
6540:
1.279 brouard 6541: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6542: * p.j overall mortality formula 49 but computed directly because
6543: * we compute the grad (wix pijx) instead of grad (pijx),even if
6544: * wix is independent of theta.
6545: */
1.218 brouard 6546: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6547: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6548: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6549: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6550: varppt[j][i]=doldmp[j][i];
6551: /* end ppptj */
6552: /* x centered again */
6553:
1.242 brouard 6554: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6555:
6556: if (popbased==1) {
6557: if(mobilav ==0){
6558: for(i=1; i<=nlstate;i++)
6559: prlim[i][i]=probs[(int)age][i][ij];
6560: }else{ /* mobilav */
6561: for(i=1; i<=nlstate;i++)
6562: prlim[i][i]=mobaverage[(int)age][i][ij];
6563: }
6564: }
6565:
6566: /* This for computing probability of death (h=1 means
6567: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6568: as a weighted average of prlim.
6569: */
1.235 brouard 6570: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6571: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6572: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6573: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6574: }
6575: /* end probability of death */
6576:
6577: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6578: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6579: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6580: for(i=1; i<=nlstate;i++){
6581: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6582: }
6583: }
6584: fprintf(ficresprobmorprev,"\n");
6585:
6586: fprintf(ficresvij,"%.0f ",age );
6587: for(i=1; i<=nlstate;i++)
6588: for(j=1; j<=nlstate;j++){
6589: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6590: }
6591: fprintf(ficresvij,"\n");
6592: free_matrix(gp,0,nhstepm,1,nlstate);
6593: free_matrix(gm,0,nhstepm,1,nlstate);
6594: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6595: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6596: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6597: } /* End age */
6598: free_vector(gpp,nlstate+1,nlstate+ndeath);
6599: free_vector(gmp,nlstate+1,nlstate+ndeath);
6600: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6601: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6602: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6603: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6604: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6605: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6606: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6607: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6608: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6609: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6610: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6611: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6612: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6613: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6614: 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);
6615: /* 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 6616: */
1.218 brouard 6617: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6618: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6619:
1.218 brouard 6620: free_vector(xp,1,npar);
6621: free_matrix(doldm,1,nlstate,1,nlstate);
6622: free_matrix(dnewm,1,nlstate,1,npar);
6623: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6624: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6625: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6626: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6627: fclose(ficresprobmorprev);
6628: fflush(ficgp);
6629: fflush(fichtm);
6630: } /* end varevsij */
1.126 brouard 6631:
6632: /************ Variance of prevlim ******************/
1.269 brouard 6633: 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 6634: {
1.205 brouard 6635: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6636: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6637:
1.268 brouard 6638: double **dnewmpar,**doldm;
1.126 brouard 6639: int i, j, nhstepm, hstepm;
6640: double *xp;
6641: double *gp, *gm;
6642: double **gradg, **trgradg;
1.208 brouard 6643: double **mgm, **mgp;
1.126 brouard 6644: double age,agelim;
6645: int theta;
6646:
6647: pstamp(ficresvpl);
1.288 brouard 6648: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6649: fprintf(ficresvpl,"# Age ");
6650: if(nresult >=1)
6651: fprintf(ficresvpl," Result# ");
1.126 brouard 6652: for(i=1; i<=nlstate;i++)
6653: fprintf(ficresvpl," %1d-%1d",i,i);
6654: fprintf(ficresvpl,"\n");
6655:
6656: xp=vector(1,npar);
1.268 brouard 6657: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6658: doldm=matrix(1,nlstate,1,nlstate);
6659:
6660: hstepm=1*YEARM; /* Every year of age */
6661: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6662: agelim = AGESUP;
6663: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6664: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6665: if (stepm >= YEARM) hstepm=1;
6666: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6667: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6668: mgp=matrix(1,npar,1,nlstate);
6669: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6670: gp=vector(1,nlstate);
6671: gm=vector(1,nlstate);
6672:
6673: for(theta=1; theta <=npar; theta++){
6674: for(i=1; i<=npar; i++){ /* Computes gradient */
6675: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6676: }
1.288 brouard 6677: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6678: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6679: /* else */
6680: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6681: for(i=1;i<=nlstate;i++){
1.126 brouard 6682: gp[i] = prlim[i][i];
1.208 brouard 6683: mgp[theta][i] = prlim[i][i];
6684: }
1.126 brouard 6685: for(i=1; i<=npar; i++) /* Computes gradient */
6686: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6687: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6688: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6689: /* else */
6690: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6691: for(i=1;i<=nlstate;i++){
1.126 brouard 6692: gm[i] = prlim[i][i];
1.208 brouard 6693: mgm[theta][i] = prlim[i][i];
6694: }
1.126 brouard 6695: for(i=1;i<=nlstate;i++)
6696: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6697: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6698: } /* End theta */
6699:
6700: trgradg =matrix(1,nlstate,1,npar);
6701:
6702: for(j=1; j<=nlstate;j++)
6703: for(theta=1; theta <=npar; theta++)
6704: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6705: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6706: /* printf("\nmgm mgp %d ",(int)age); */
6707: /* for(j=1; j<=nlstate;j++){ */
6708: /* printf(" %d ",j); */
6709: /* for(theta=1; theta <=npar; theta++) */
6710: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6711: /* printf("\n "); */
6712: /* } */
6713: /* } */
6714: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6715: /* printf("\n gradg %d ",(int)age); */
6716: /* for(j=1; j<=nlstate;j++){ */
6717: /* printf("%d ",j); */
6718: /* for(theta=1; theta <=npar; theta++) */
6719: /* printf("%d %lf ",theta,gradg[theta][j]); */
6720: /* printf("\n "); */
6721: /* } */
6722: /* } */
1.126 brouard 6723:
6724: for(i=1;i<=nlstate;i++)
6725: varpl[i][(int)age] =0.;
1.209 brouard 6726: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6727: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6728: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6729: }else{
1.268 brouard 6730: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6731: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6732: }
1.126 brouard 6733: for(i=1;i<=nlstate;i++)
6734: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6735:
6736: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6737: if(nresult >=1)
6738: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6739: for(i=1; i<=nlstate;i++){
1.126 brouard 6740: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6741: /* for(j=1;j<=nlstate;j++) */
6742: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6743: }
1.126 brouard 6744: fprintf(ficresvpl,"\n");
6745: free_vector(gp,1,nlstate);
6746: free_vector(gm,1,nlstate);
1.208 brouard 6747: free_matrix(mgm,1,npar,1,nlstate);
6748: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6749: free_matrix(gradg,1,npar,1,nlstate);
6750: free_matrix(trgradg,1,nlstate,1,npar);
6751: } /* End age */
6752:
6753: free_vector(xp,1,npar);
6754: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6755: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6756:
6757: }
6758:
6759:
6760: /************ Variance of backprevalence limit ******************/
1.269 brouard 6761: 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 6762: {
6763: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6764: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6765:
6766: double **dnewmpar,**doldm;
6767: int i, j, nhstepm, hstepm;
6768: double *xp;
6769: double *gp, *gm;
6770: double **gradg, **trgradg;
6771: double **mgm, **mgp;
6772: double age,agelim;
6773: int theta;
6774:
6775: pstamp(ficresvbl);
6776: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6777: fprintf(ficresvbl,"# Age ");
6778: if(nresult >=1)
6779: fprintf(ficresvbl," Result# ");
6780: for(i=1; i<=nlstate;i++)
6781: fprintf(ficresvbl," %1d-%1d",i,i);
6782: fprintf(ficresvbl,"\n");
6783:
6784: xp=vector(1,npar);
6785: dnewmpar=matrix(1,nlstate,1,npar);
6786: doldm=matrix(1,nlstate,1,nlstate);
6787:
6788: hstepm=1*YEARM; /* Every year of age */
6789: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6790: agelim = AGEINF;
6791: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6792: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6793: if (stepm >= YEARM) hstepm=1;
6794: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6795: gradg=matrix(1,npar,1,nlstate);
6796: mgp=matrix(1,npar,1,nlstate);
6797: mgm=matrix(1,npar,1,nlstate);
6798: gp=vector(1,nlstate);
6799: gm=vector(1,nlstate);
6800:
6801: for(theta=1; theta <=npar; theta++){
6802: for(i=1; i<=npar; i++){ /* Computes gradient */
6803: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6804: }
6805: if(mobilavproj > 0 )
6806: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6807: else
6808: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6809: for(i=1;i<=nlstate;i++){
6810: gp[i] = bprlim[i][i];
6811: mgp[theta][i] = bprlim[i][i];
6812: }
6813: for(i=1; i<=npar; i++) /* Computes gradient */
6814: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6815: if(mobilavproj > 0 )
6816: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6817: else
6818: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6819: for(i=1;i<=nlstate;i++){
6820: gm[i] = bprlim[i][i];
6821: mgm[theta][i] = bprlim[i][i];
6822: }
6823: for(i=1;i<=nlstate;i++)
6824: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6825: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6826: } /* End theta */
6827:
6828: trgradg =matrix(1,nlstate,1,npar);
6829:
6830: for(j=1; j<=nlstate;j++)
6831: for(theta=1; theta <=npar; theta++)
6832: trgradg[j][theta]=gradg[theta][j];
6833: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6834: /* printf("\nmgm mgp %d ",(int)age); */
6835: /* for(j=1; j<=nlstate;j++){ */
6836: /* printf(" %d ",j); */
6837: /* for(theta=1; theta <=npar; theta++) */
6838: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6839: /* printf("\n "); */
6840: /* } */
6841: /* } */
6842: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6843: /* printf("\n gradg %d ",(int)age); */
6844: /* for(j=1; j<=nlstate;j++){ */
6845: /* printf("%d ",j); */
6846: /* for(theta=1; theta <=npar; theta++) */
6847: /* printf("%d %lf ",theta,gradg[theta][j]); */
6848: /* printf("\n "); */
6849: /* } */
6850: /* } */
6851:
6852: for(i=1;i<=nlstate;i++)
6853: varbpl[i][(int)age] =0.;
6854: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6855: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6856: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6857: }else{
6858: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6859: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6860: }
6861: for(i=1;i<=nlstate;i++)
6862: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6863:
6864: fprintf(ficresvbl,"%.0f ",age );
6865: if(nresult >=1)
6866: fprintf(ficresvbl,"%d ",nres );
6867: for(i=1; i<=nlstate;i++)
6868: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6869: fprintf(ficresvbl,"\n");
6870: free_vector(gp,1,nlstate);
6871: free_vector(gm,1,nlstate);
6872: free_matrix(mgm,1,npar,1,nlstate);
6873: free_matrix(mgp,1,npar,1,nlstate);
6874: free_matrix(gradg,1,npar,1,nlstate);
6875: free_matrix(trgradg,1,nlstate,1,npar);
6876: } /* End age */
6877:
6878: free_vector(xp,1,npar);
6879: free_matrix(doldm,1,nlstate,1,npar);
6880: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6881:
6882: }
6883:
6884: /************ Variance of one-step probabilities ******************/
6885: 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 6886: {
6887: int i, j=0, k1, l1, tj;
6888: int k2, l2, j1, z1;
6889: int k=0, l;
6890: int first=1, first1, first2;
1.326 brouard 6891: int nres=0; /* New */
1.222 brouard 6892: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6893: double **dnewm,**doldm;
6894: double *xp;
6895: double *gp, *gm;
6896: double **gradg, **trgradg;
6897: double **mu;
6898: double age, cov[NCOVMAX+1];
6899: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6900: int theta;
6901: char fileresprob[FILENAMELENGTH];
6902: char fileresprobcov[FILENAMELENGTH];
6903: char fileresprobcor[FILENAMELENGTH];
6904: double ***varpij;
6905:
6906: strcpy(fileresprob,"PROB_");
6907: strcat(fileresprob,fileres);
6908: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6909: printf("Problem with resultfile: %s\n", fileresprob);
6910: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6911: }
6912: strcpy(fileresprobcov,"PROBCOV_");
6913: strcat(fileresprobcov,fileresu);
6914: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6915: printf("Problem with resultfile: %s\n", fileresprobcov);
6916: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6917: }
6918: strcpy(fileresprobcor,"PROBCOR_");
6919: strcat(fileresprobcor,fileresu);
6920: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6921: printf("Problem with resultfile: %s\n", fileresprobcor);
6922: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6923: }
6924: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6925: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6926: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6927: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6928: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6929: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6930: pstamp(ficresprob);
6931: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6932: fprintf(ficresprob,"# Age");
6933: pstamp(ficresprobcov);
6934: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6935: fprintf(ficresprobcov,"# Age");
6936: pstamp(ficresprobcor);
6937: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6938: fprintf(ficresprobcor,"# Age");
1.126 brouard 6939:
6940:
1.222 brouard 6941: for(i=1; i<=nlstate;i++)
6942: for(j=1; j<=(nlstate+ndeath);j++){
6943: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6944: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6945: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6946: }
6947: /* fprintf(ficresprob,"\n");
6948: fprintf(ficresprobcov,"\n");
6949: fprintf(ficresprobcor,"\n");
6950: */
6951: xp=vector(1,npar);
6952: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6953: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6954: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6955: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6956: first=1;
6957: fprintf(ficgp,"\n# Routine varprob");
6958: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6959: fprintf(fichtm,"\n");
6960:
1.288 brouard 6961: 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 6962: 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);
6963: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6964: and drawn. It helps understanding how is the covariance between two incidences.\
6965: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6966: 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 6967: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6968: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6969: standard deviations wide on each axis. <br>\
6970: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6971: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6972: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6973:
1.222 brouard 6974: cov[1]=1;
6975: /* tj=cptcoveff; */
1.225 brouard 6976: tj = (int) pow(2,cptcoveff);
1.222 brouard 6977: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6978: j1=0;
1.224 brouard 6979: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.326 brouard 6980: for(nres=1;nres <=1; nres++){ /* For each resultline */
6981: /* for(nres=1;nres <=nresult; nres++){ /\* For each resultline *\/ */
1.222 brouard 6982: if (cptcovn>0) {
6983: fprintf(ficresprob, "\n#********** Variable ");
1.330 brouard 6984: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,Tvaraff[z1])]);
1.222 brouard 6985: fprintf(ficresprob, "**********\n#\n");
6986: fprintf(ficresprobcov, "\n#********** Variable ");
1.330 brouard 6987: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,Tvaraff[z1])]);
1.222 brouard 6988: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6989:
1.222 brouard 6990: fprintf(ficgp, "\n#********** Variable ");
1.330 brouard 6991: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,Tvaraff[z1])]);
1.222 brouard 6992: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6993:
6994:
1.222 brouard 6995: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.319 brouard 6996: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); */
1.330 brouard 6997: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtmcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,Tvaraff[z1])]);
1.222 brouard 6998: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6999:
1.222 brouard 7000: fprintf(ficresprobcor, "\n#********** Variable ");
1.330 brouard 7001: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,Tvaraff[z1])]);
1.222 brouard 7002: fprintf(ficresprobcor, "**********\n#");
7003: if(invalidvarcomb[j1]){
7004: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7005: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7006: continue;
7007: }
7008: }
7009: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7010: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7011: gp=vector(1,(nlstate)*(nlstate+ndeath));
7012: gm=vector(1,(nlstate)*(nlstate+ndeath));
7013: for (age=bage; age<=fage; age ++){
7014: cov[2]=age;
7015: if(nagesqr==1)
7016: cov[3]= age*age;
1.326 brouard 7017: /* for (k=1; k<=cptcovn;k++) { */
7018: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; */
7019: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
7020: /* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates */
1.330 brouard 7021: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TvarsD[k])];
1.222 brouard 7022: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
7023: * 1 1 1 1 1
7024: * 2 2 1 1 1
7025: * 3 1 2 1 1
7026: */
7027: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
7028: }
1.319 brouard 7029: /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 */
7030: /* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] */
7031: /*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
1.326 brouard 7032: for (k=1; k<=cptcovage;k++){ /* For product with age */
7033: if(Dummy[Tage[k]]==2){ /* dummy with age */
1.330 brouard 7034: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,Tvar[Tage[k]])]*cov[2];
1.326 brouard 7035: /* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
7036: } else if(Dummy[Tage[k]]==3){ /* quantitative with age */
1.327 brouard 7037: 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]);
7038: exit(1);
7039: /* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\* Using the mean of quantitative variable Tvar[Tage[k]] /\* Tqresult[nres][k]; *\/ */
1.326 brouard 7040: /* cov[++k1]=Tqresult[nres][k]; */
7041: }
7042: /* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
7043: }
7044: for (k=1; k<=cptcovprod;k++){/* For product without age */
1.329 brouard 7045: if(Dummy[Tvard[k][1]]==0){
7046: if(Dummy[Tvard[k][2]]==0){
1.330 brouard 7047: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(j1,Tvard[k][2])];
1.326 brouard 7048: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
7049: }else{ /* Should we use the mean of the quantitative variables? */
1.330 brouard 7050: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,Tvard[k][1])] * Tqresult[nres][k];
1.326 brouard 7051: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; */
7052: }
7053: }else{
1.329 brouard 7054: if(Dummy[Tvard[k][2]]==0){
1.330 brouard 7055: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]];
1.326 brouard 7056: /* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; */
7057: }else{
7058: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
7059: /* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
7060: }
7061: }
7062: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
7063: }
7064: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7065: for(theta=1; theta <=npar; theta++){
7066: for(i=1; i<=npar; i++)
7067: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7068:
1.222 brouard 7069: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7070:
1.222 brouard 7071: k=0;
7072: for(i=1; i<= (nlstate); i++){
7073: for(j=1; j<=(nlstate+ndeath);j++){
7074: k=k+1;
7075: gp[k]=pmmij[i][j];
7076: }
7077: }
1.220 brouard 7078:
1.222 brouard 7079: for(i=1; i<=npar; i++)
7080: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7081:
1.222 brouard 7082: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7083: k=0;
7084: for(i=1; i<=(nlstate); i++){
7085: for(j=1; j<=(nlstate+ndeath);j++){
7086: k=k+1;
7087: gm[k]=pmmij[i][j];
7088: }
7089: }
1.220 brouard 7090:
1.222 brouard 7091: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7092: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7093: }
1.126 brouard 7094:
1.222 brouard 7095: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7096: for(theta=1; theta <=npar; theta++)
7097: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7098:
1.222 brouard 7099: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7100: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7101:
1.222 brouard 7102: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7103:
1.222 brouard 7104: k=0;
7105: for(i=1; i<=(nlstate); i++){
7106: for(j=1; j<=(nlstate+ndeath);j++){
7107: k=k+1;
7108: mu[k][(int) age]=pmmij[i][j];
7109: }
7110: }
7111: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7112: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7113: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7114:
1.222 brouard 7115: /*printf("\n%d ",(int)age);
7116: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7117: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7118: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7119: }*/
1.220 brouard 7120:
1.222 brouard 7121: fprintf(ficresprob,"\n%d ",(int)age);
7122: fprintf(ficresprobcov,"\n%d ",(int)age);
7123: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7124:
1.222 brouard 7125: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7126: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7127: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7128: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7129: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7130: }
7131: i=0;
7132: for (k=1; k<=(nlstate);k++){
7133: for (l=1; l<=(nlstate+ndeath);l++){
7134: i++;
7135: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7136: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7137: for (j=1; j<=i;j++){
7138: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7139: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7140: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7141: }
7142: }
7143: }/* end of loop for state */
7144: } /* end of loop for age */
7145: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7146: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7147: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7148: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7149:
7150: /* Confidence intervalle of pij */
7151: /*
7152: fprintf(ficgp,"\nunset parametric;unset label");
7153: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7154: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7155: 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);
7156: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7157: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7158: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7159: */
7160:
7161: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7162: first1=1;first2=2;
7163: for (k2=1; k2<=(nlstate);k2++){
7164: for (l2=1; l2<=(nlstate+ndeath);l2++){
7165: if(l2==k2) continue;
7166: j=(k2-1)*(nlstate+ndeath)+l2;
7167: for (k1=1; k1<=(nlstate);k1++){
7168: for (l1=1; l1<=(nlstate+ndeath);l1++){
7169: if(l1==k1) continue;
7170: i=(k1-1)*(nlstate+ndeath)+l1;
7171: if(i<=j) continue;
7172: for (age=bage; age<=fage; age ++){
7173: if ((int)age %5==0){
7174: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7175: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7176: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7177: mu1=mu[i][(int) age]/stepm*YEARM ;
7178: mu2=mu[j][(int) age]/stepm*YEARM;
7179: c12=cv12/sqrt(v1*v2);
7180: /* Computing eigen value of matrix of covariance */
7181: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7182: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7183: if ((lc2 <0) || (lc1 <0) ){
7184: if(first2==1){
7185: first1=0;
7186: 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);
7187: }
7188: 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);
7189: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7190: /* lc2=fabs(lc2); */
7191: }
1.220 brouard 7192:
1.222 brouard 7193: /* Eigen vectors */
1.280 brouard 7194: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7195: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7196: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7197: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7198: }else
7199: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7200: /*v21=sqrt(1.-v11*v11); *//* error */
7201: v21=(lc1-v1)/cv12*v11;
7202: v12=-v21;
7203: v22=v11;
7204: tnalp=v21/v11;
7205: if(first1==1){
7206: first1=0;
7207: 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);
7208: }
7209: 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);
7210: /*printf(fignu*/
7211: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7212: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7213: if(first==1){
7214: first=0;
7215: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7216: fprintf(ficgp,"\nset parametric;unset label");
7217: 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);
7218: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7219: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7220: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7221: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7222: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7223: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7224: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7225: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7226: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7227: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7228: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7229: 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 7230: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7231: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7232: }else{
7233: first=0;
7234: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7235: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7236: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7237: 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 7238: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7239: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7240: }/* if first */
7241: } /* age mod 5 */
7242: } /* end loop age */
7243: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7244: first=1;
7245: } /*l12 */
7246: } /* k12 */
7247: } /*l1 */
7248: }/* k1 */
1.326 brouard 7249: } /* loop on nres */
1.222 brouard 7250: } /* loop on combination of covariates j1 */
7251: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
7252: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
7253: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7254: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
7255: free_vector(xp,1,npar);
7256: fclose(ficresprob);
7257: fclose(ficresprobcov);
7258: fclose(ficresprobcor);
7259: fflush(ficgp);
7260: fflush(fichtmcov);
7261: }
1.126 brouard 7262:
7263:
7264: /******************* Printing html file ***********/
1.201 brouard 7265: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 7266: int lastpass, int stepm, int weightopt, char model[],\
7267: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 7268: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
7269: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
7270: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 7271: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 7272: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 7273: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
7274: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
7275: </ul>");
1.319 brouard 7276: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
7277: /* </ul>", model); */
1.214 brouard 7278: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
7279: 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",
7280: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
7281: fprintf(fichtm,"<li> - Observed 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 7282: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
7283: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 7284: fprintf(fichtm,"\
7285: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 7286: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 7287: fprintf(fichtm,"\
1.217 brouard 7288: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
7289: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
7290: fprintf(fichtm,"\
1.288 brouard 7291: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7292: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 7293: fprintf(fichtm,"\
1.288 brouard 7294: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 7295: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
7296: fprintf(fichtm,"\
1.211 brouard 7297: - (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 7298: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7299: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 7300: if(prevfcast==1){
7301: fprintf(fichtm,"\
7302: - Prevalence projections by age and states: \
1.201 brouard 7303: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 7304: }
1.126 brouard 7305:
7306:
1.225 brouard 7307: m=pow(2,cptcoveff);
1.222 brouard 7308: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7309:
1.317 brouard 7310: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 7311:
7312: jj1=0;
7313:
7314: fprintf(fichtm," \n<ul>");
7315: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7316: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7317: if(m != 1 && TKresult[nres]!= k1)
7318: continue;
7319: jj1++;
7320: if (cptcovn > 0) {
7321: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
7322: for (cpt=1; cpt<=cptcoveff;cpt++){
7323: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7324: }
7325: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7326: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7327: }
7328: fprintf(fichtm,"\">");
7329:
7330: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7331: fprintf(fichtm,"************ Results for covariates");
7332: for (cpt=1; cpt<=cptcoveff;cpt++){
7333: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7334: }
7335: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7336: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7337: }
7338: if(invalidvarcomb[k1]){
7339: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7340: continue;
7341: }
7342: fprintf(fichtm,"</a></li>");
7343: } /* cptcovn >0 */
7344: }
1.317 brouard 7345: fprintf(fichtm," \n</ul>");
1.264 brouard 7346:
1.222 brouard 7347: jj1=0;
1.237 brouard 7348:
7349: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 7350: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 7351: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7352: continue;
1.220 brouard 7353:
1.222 brouard 7354: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7355: jj1++;
7356: if (cptcovn > 0) {
1.264 brouard 7357: fprintf(fichtm,"\n<p><a name=\"rescov");
7358: for (cpt=1; cpt<=cptcoveff;cpt++){
7359: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7360: }
7361: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7362: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7363: }
7364: fprintf(fichtm,"\"</a>");
7365:
1.222 brouard 7366: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7367: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 7368: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7369: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
7370: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7371: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 7372: }
1.237 brouard 7373: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7374: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7375: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
7376: }
7377:
1.230 brouard 7378: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.321 brouard 7379: fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 7380: if(invalidvarcomb[k1]){
7381: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
7382: printf("\nCombination (%d) ignored because no cases \n",k1);
7383: continue;
7384: }
7385: }
7386: /* aij, bij */
1.259 brouard 7387: 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 7388: <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 7389: /* Pij */
1.241 brouard 7390: 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> \
7391: <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 7392: /* Quasi-incidences */
7393: 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 7394: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 7395: 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 7396: 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> \
7397: <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 7398: /* Survival functions (period) in state j */
7399: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7400: 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);
7401: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7402: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 7403: }
7404: /* State specific survival functions (period) */
7405: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7406: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
7407: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 7408: <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);
7409: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
7410: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 7411: }
1.288 brouard 7412: /* Period (forward stable) prevalence in each health state */
1.222 brouard 7413: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 7414: 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);
7415: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"P_"),subdirf2(optionfilefiname,"P_"));
7416: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 7417: }
1.296 brouard 7418: if(prevbcast==1){
1.288 brouard 7419: /* Backward prevalence in each health state */
1.222 brouard 7420: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7421: 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 7422: <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 7423: }
1.217 brouard 7424: }
1.222 brouard 7425: if(prevfcast==1){
1.288 brouard 7426: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7427: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 7428: 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);
7429: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
7430: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
7431: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 7432: }
7433: }
1.296 brouard 7434: if(prevbcast==1){
1.268 brouard 7435: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
7436: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 7437: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
7438: 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 \
7439: 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 7440: 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);
7441: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
7442: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 7443: }
7444: }
1.220 brouard 7445:
1.222 brouard 7446: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 7447: 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);
7448: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
7449: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 7450: }
7451: /* } /\* end i1 *\/ */
7452: }/* End k1 */
7453: fprintf(fichtm,"</ul>");
1.126 brouard 7454:
1.222 brouard 7455: fprintf(fichtm,"\
1.126 brouard 7456: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 7457: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 7458: - 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 7459: But because parameters are usually highly correlated (a higher incidence of disability \
7460: and a higher incidence of recovery can give very close observed transition) it might \
7461: be very useful to look not only at linear confidence intervals estimated from the \
7462: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
7463: (parameters) of the logistic regression, it might be more meaningful to visualize the \
7464: covariance matrix of the one-step probabilities. \
7465: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7466:
1.222 brouard 7467: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7468: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7469: fprintf(fichtm,"\
1.126 brouard 7470: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7471: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7472:
1.222 brouard 7473: fprintf(fichtm,"\
1.126 brouard 7474: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7475: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7476: fprintf(fichtm,"\
1.126 brouard 7477: - 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): \
7478: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7479: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7480: fprintf(fichtm,"\
1.126 brouard 7481: - (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): \
7482: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7483: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7484: fprintf(fichtm,"\
1.288 brouard 7485: - 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 7486: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7487: fprintf(fichtm,"\
1.128 brouard 7488: - 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 7489: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7490: fprintf(fichtm,"\
1.288 brouard 7491: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7492: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7493:
7494: /* if(popforecast==1) fprintf(fichtm,"\n */
7495: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7496: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7497: /* <br>",fileres,fileres,fileres,fileres); */
7498: /* else */
7499: /* 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 7500: fflush(fichtm);
1.126 brouard 7501:
1.225 brouard 7502: m=pow(2,cptcoveff);
1.222 brouard 7503: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7504:
1.317 brouard 7505: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
7506:
7507: jj1=0;
7508:
7509: fprintf(fichtm," \n<ul>");
7510: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7511: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7512: if(m != 1 && TKresult[nres]!= k1)
7513: continue;
7514: jj1++;
7515: if (cptcovn > 0) {
7516: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
7517: for (cpt=1; cpt<=cptcoveff;cpt++){
7518: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7519: }
7520: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7521: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7522: }
7523: fprintf(fichtm,"\">");
7524:
7525: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7526: fprintf(fichtm,"************ Results for covariates");
7527: for (cpt=1; cpt<=cptcoveff;cpt++){
7528: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7529: }
7530: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7531: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7532: }
7533: if(invalidvarcomb[k1]){
7534: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7535: continue;
7536: }
7537: fprintf(fichtm,"</a></li>");
7538: } /* cptcovn >0 */
7539: }
7540: fprintf(fichtm," \n</ul>");
7541:
1.222 brouard 7542: jj1=0;
1.237 brouard 7543:
1.241 brouard 7544: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7545: for(k1=1; k1<=m;k1++){
1.253 brouard 7546: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7547: continue;
1.222 brouard 7548: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7549: jj1++;
1.126 brouard 7550: if (cptcovn > 0) {
1.317 brouard 7551: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
7552: for (cpt=1; cpt<=cptcoveff;cpt++){
7553: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7554: }
7555: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7556: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7557: }
7558: fprintf(fichtm,"\"</a>");
7559:
1.126 brouard 7560: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.317 brouard 7561: for (cpt=1; cpt<=cptcoveff;cpt++){ /**< cptcoveff number of variables */
1.237 brouard 7562: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
1.317 brouard 7563: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
1.237 brouard 7564: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 7565: }
1.237 brouard 7566: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7567: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7568: }
7569:
1.321 brouard 7570: fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 7571:
1.222 brouard 7572: if(invalidvarcomb[k1]){
7573: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7574: continue;
7575: }
1.126 brouard 7576: }
7577: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7578: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 7579: 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);
7580: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
7581: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 7582: }
7583: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 7584: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 7585: true period expectancies (those weighted with period prevalences are also\
7586: drawn in addition to the population based expectancies computed using\
1.314 brouard 7587: 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);
7588: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
7589: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7590: /* } /\* end i1 *\/ */
7591: }/* End k1 */
1.241 brouard 7592: }/* End nres */
1.222 brouard 7593: fprintf(fichtm,"</ul>");
7594: fflush(fichtm);
1.126 brouard 7595: }
7596:
7597: /******************* Gnuplot file **************/
1.296 brouard 7598: 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 7599:
7600: char dirfileres[132],optfileres[132];
1.264 brouard 7601: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7602: 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 7603: int lv=0, vlv=0, kl=0;
1.130 brouard 7604: int ng=0;
1.201 brouard 7605: int vpopbased;
1.223 brouard 7606: int ioffset; /* variable offset for columns */
1.270 brouard 7607: int iyearc=1; /* variable column for year of projection */
7608: int iagec=1; /* variable column for age of projection */
1.235 brouard 7609: int nres=0; /* Index of resultline */
1.266 brouard 7610: int istart=1; /* For starting graphs in projections */
1.219 brouard 7611:
1.126 brouard 7612: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7613: /* printf("Problem with file %s",optionfilegnuplot); */
7614: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7615: /* } */
7616:
7617: /*#ifdef windows */
7618: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7619: /*#endif */
1.225 brouard 7620: m=pow(2,cptcoveff);
1.126 brouard 7621:
1.274 brouard 7622: /* diagram of the model */
7623: fprintf(ficgp,"\n#Diagram of the model \n");
7624: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7625: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7626: 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);
7627:
7628: 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);
7629: fprintf(ficgp,"\n#show arrow\nunset label\n");
7630: 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);
7631: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7632: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7633: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7634: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7635:
1.202 brouard 7636: /* Contribution to likelihood */
7637: /* Plot the probability implied in the likelihood */
1.223 brouard 7638: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7639: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7640: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7641: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7642: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7643: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7644: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7645: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7646: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7647: 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));
7648: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7649: 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));
7650: for (i=1; i<= nlstate ; i ++) {
7651: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7652: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7653: 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);
7654: for (j=2; j<= nlstate+ndeath ; j ++) {
7655: 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);
7656: }
7657: fprintf(ficgp,";\nset out; unset ylabel;\n");
7658: }
7659: /* 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 */
7660: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7661: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7662: fprintf(ficgp,"\nset out;unset log\n");
7663: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7664:
1.126 brouard 7665: strcpy(dirfileres,optionfilefiname);
7666: strcpy(optfileres,"vpl");
1.223 brouard 7667: /* 1eme*/
1.238 brouard 7668: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7669: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7670: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7671: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7672: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7673: continue;
7674: /* We are interested in selected combination by the resultline */
1.246 brouard 7675: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7676: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7677: strcpy(gplotlabel,"(");
1.238 brouard 7678: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7679: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7680: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7681: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7682: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7683: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7684: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7685: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7686: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7687: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7688: }
7689: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7690: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7691: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7692: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7693: }
7694: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7695: /* printf("\n#\n"); */
1.238 brouard 7696: fprintf(ficgp,"\n#\n");
7697: if(invalidvarcomb[k1]){
1.260 brouard 7698: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7699: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7700: continue;
7701: }
1.235 brouard 7702:
1.241 brouard 7703: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7704: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7705: /* 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 7706: fprintf(ficgp,"set title \"Alive state %d %s model=%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 7707: 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);
7708: /* 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); */
7709: /* k1-1 error should be nres-1*/
1.238 brouard 7710: for (i=1; i<= nlstate ; i ++) {
7711: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7712: else fprintf(ficgp," %%*lf (%%*lf)");
7713: }
1.288 brouard 7714: 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 7715: for (i=1; i<= nlstate ; i ++) {
7716: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7717: else fprintf(ficgp," %%*lf (%%*lf)");
7718: }
1.260 brouard 7719: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7720: for (i=1; i<= nlstate ; i ++) {
7721: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7722: else fprintf(ficgp," %%*lf (%%*lf)");
7723: }
1.265 brouard 7724: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7725:
7726: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7727: if(cptcoveff ==0){
1.271 brouard 7728: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7729: }else{
7730: kl=0;
7731: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7732: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7733: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7734: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7735: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7736: vlv= nbcode[Tvaraff[k]][lv];
7737: kl++;
7738: /* 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 *\/ */
7739: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7740: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7741: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7742: if(k==cptcoveff){
7743: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7744: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7745: }else{
7746: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7747: kl++;
7748: }
7749: } /* end covariate */
7750: } /* end if no covariate */
7751:
1.296 brouard 7752: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 7753: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7754: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7755: if(cptcoveff ==0){
1.245 brouard 7756: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7757: }else{
7758: kl=0;
7759: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7760: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7761: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7762: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7763: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7764: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7765: kl++;
1.238 brouard 7766: /* 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 *\/ */
7767: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7768: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7769: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7770: if(k==cptcoveff){
1.245 brouard 7771: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7772: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7773: }else{
7774: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7775: kl++;
7776: }
7777: } /* end covariate */
7778: } /* end if no covariate */
1.296 brouard 7779: if(prevbcast == 1){
1.268 brouard 7780: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7781: /* k1-1 error should be nres-1*/
7782: for (i=1; i<= nlstate ; i ++) {
7783: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7784: else fprintf(ficgp," %%*lf (%%*lf)");
7785: }
1.271 brouard 7786: 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 7787: for (i=1; i<= nlstate ; i ++) {
7788: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7789: else fprintf(ficgp," %%*lf (%%*lf)");
7790: }
1.276 brouard 7791: 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 7792: for (i=1; i<= nlstate ; i ++) {
7793: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7794: else fprintf(ficgp," %%*lf (%%*lf)");
7795: }
1.274 brouard 7796: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7797: } /* end if backprojcast */
1.296 brouard 7798: } /* end if prevbcast */
1.276 brouard 7799: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7800: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7801: } /* nres */
1.201 brouard 7802: } /* k1 */
7803: } /* cpt */
1.235 brouard 7804:
7805:
1.126 brouard 7806: /*2 eme*/
1.238 brouard 7807: for (k1=1; k1<= m ; k1 ++){
7808: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7809: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7810: continue;
7811: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7812: strcpy(gplotlabel,"(");
1.238 brouard 7813: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7814: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7815: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7816: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7817: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7818: vlv= nbcode[Tvaraff[k]][lv];
7819: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7820: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7821: }
1.237 brouard 7822: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7823: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7824: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7825: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7826: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7827: }
1.264 brouard 7828: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7829: fprintf(ficgp,"\n#\n");
1.223 brouard 7830: if(invalidvarcomb[k1]){
7831: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7832: continue;
7833: }
1.219 brouard 7834:
1.241 brouard 7835: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7836: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7837: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7838: if(vpopbased==0){
1.238 brouard 7839: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7840: }else
1.238 brouard 7841: fprintf(ficgp,"\nreplot ");
7842: for (i=1; i<= nlstate+1 ; i ++) {
7843: k=2*i;
1.261 brouard 7844: 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 7845: for (j=1; j<= nlstate+1 ; j ++) {
7846: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7847: else fprintf(ficgp," %%*lf (%%*lf)");
7848: }
7849: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7850: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7851: 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 7852: for (j=1; j<= nlstate+1 ; j ++) {
7853: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7854: else fprintf(ficgp," %%*lf (%%*lf)");
7855: }
7856: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7857: 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 7858: for (j=1; j<= nlstate+1 ; j ++) {
7859: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7860: else fprintf(ficgp," %%*lf (%%*lf)");
7861: }
7862: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7863: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7864: } /* state */
7865: } /* vpopbased */
1.264 brouard 7866: 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 7867: } /* end nres */
7868: } /* k1 end 2 eme*/
7869:
7870:
7871: /*3eme*/
7872: for (k1=1; k1<= m ; k1 ++){
7873: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7874: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7875: continue;
7876:
7877: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7878: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7879: strcpy(gplotlabel,"(");
1.238 brouard 7880: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7881: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7882: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7883: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7884: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7885: vlv= nbcode[Tvaraff[k]][lv];
7886: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7887: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7888: }
7889: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7890: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7891: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7892: }
1.264 brouard 7893: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7894: fprintf(ficgp,"\n#\n");
7895: if(invalidvarcomb[k1]){
7896: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7897: continue;
7898: }
7899:
7900: /* k=2+nlstate*(2*cpt-2); */
7901: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7902: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7903: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7904: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7905: 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 7906: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7907: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7908: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7909: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7910: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7911: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7912:
1.238 brouard 7913: */
7914: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7915: 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 7916: /* 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 7917:
1.238 brouard 7918: }
1.261 brouard 7919: 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 7920: }
1.264 brouard 7921: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7922: } /* end nres */
7923: } /* end kl 3eme */
1.126 brouard 7924:
1.223 brouard 7925: /* 4eme */
1.201 brouard 7926: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7927: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7928: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7929: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7930: continue;
1.238 brouard 7931: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7932: strcpy(gplotlabel,"(");
1.238 brouard 7933: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7934: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7935: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7936: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7937: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7938: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7939: vlv= nbcode[Tvaraff[k]][lv];
7940: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7941: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7942: }
7943: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7944: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7945: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7946: }
1.264 brouard 7947: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7948: fprintf(ficgp,"\n#\n");
7949: if(invalidvarcomb[k1]){
7950: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7951: continue;
1.223 brouard 7952: }
1.238 brouard 7953:
1.241 brouard 7954: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7955: 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 7956: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7957: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7958: k=3;
7959: for (i=1; i<= nlstate ; i ++){
7960: if(i==1){
7961: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7962: }else{
7963: fprintf(ficgp,", '' ");
7964: }
7965: l=(nlstate+ndeath)*(i-1)+1;
7966: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7967: for (j=2; j<= nlstate+ndeath ; j ++)
7968: fprintf(ficgp,"+$%d",k+l+j-1);
7969: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7970: } /* nlstate */
1.264 brouard 7971: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7972: } /* end cpt state*/
7973: } /* end nres */
7974: } /* end covariate k1 */
7975:
1.220 brouard 7976: /* 5eme */
1.201 brouard 7977: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7978: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7979: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7980: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7981: continue;
1.238 brouard 7982: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7983: strcpy(gplotlabel,"(");
1.238 brouard 7984: 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);
7985: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7986: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7987: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7988: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7989: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7990: vlv= nbcode[Tvaraff[k]][lv];
7991: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7992: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7993: }
7994: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7995: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7996: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7997: }
1.264 brouard 7998: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7999: fprintf(ficgp,"\n#\n");
8000: if(invalidvarcomb[k1]){
8001: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8002: continue;
8003: }
1.227 brouard 8004:
1.241 brouard 8005: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8006: 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 8007: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8008: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8009: k=3;
8010: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8011: if(j==1)
8012: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8013: else
8014: fprintf(ficgp,", '' ");
8015: l=(nlstate+ndeath)*(cpt-1) +j;
8016: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8017: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8018: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8019: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8020: } /* nlstate */
8021: fprintf(ficgp,", '' ");
8022: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8023: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8024: l=(nlstate+ndeath)*(cpt-1) +j;
8025: if(j < nlstate)
8026: fprintf(ficgp,"$%d +",k+l);
8027: else
8028: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8029: }
1.264 brouard 8030: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8031: } /* end cpt state*/
8032: } /* end covariate */
8033: } /* end nres */
1.227 brouard 8034:
1.220 brouard 8035: /* 6eme */
1.202 brouard 8036: /* CV preval stable (period) for each covariate */
1.237 brouard 8037: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8038: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8039: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8040: continue;
1.255 brouard 8041: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8042: strcpy(gplotlabel,"(");
1.288 brouard 8043: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 8044: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 8045: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
8046: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8047: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8048: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8049: vlv= nbcode[Tvaraff[k]][lv];
8050: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8051: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 8052: }
1.237 brouard 8053: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8054: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8055: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 8056: }
1.264 brouard 8057: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8058: fprintf(ficgp,"\n#\n");
1.223 brouard 8059: if(invalidvarcomb[k1]){
1.227 brouard 8060: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8061: continue;
1.223 brouard 8062: }
1.227 brouard 8063:
1.241 brouard 8064: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8065: 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 8066: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8067: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8068: k=3; /* Offset */
1.255 brouard 8069: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8070: if(i==1)
8071: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8072: else
8073: fprintf(ficgp,", '' ");
1.255 brouard 8074: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8075: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8076: for (j=2; j<= nlstate ; j ++)
8077: fprintf(ficgp,"+$%d",k+l+j-1);
8078: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8079: } /* nlstate */
1.264 brouard 8080: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8081: } /* end cpt state*/
8082: } /* end covariate */
1.227 brouard 8083:
8084:
1.220 brouard 8085: /* 7eme */
1.296 brouard 8086: if(prevbcast == 1){
1.288 brouard 8087: /* CV backward prevalence for each covariate */
1.237 brouard 8088: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8089: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8090: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8091: continue;
1.268 brouard 8092: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 8093: strcpy(gplotlabel,"(");
1.288 brouard 8094: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 8095: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
8096: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
8097: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8098: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 8099: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 8100: vlv= nbcode[Tvaraff[k]][lv];
8101: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8102: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 8103: }
1.237 brouard 8104: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8105: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8106: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 8107: }
1.264 brouard 8108: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8109: fprintf(ficgp,"\n#\n");
8110: if(invalidvarcomb[k1]){
8111: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8112: continue;
8113: }
8114:
1.241 brouard 8115: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 8116: 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 8117: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8118: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 8119: k=3; /* Offset */
1.268 brouard 8120: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 8121: if(i==1)
8122: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
8123: else
8124: fprintf(ficgp,", '' ");
8125: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 8126: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 8127: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
8128: /* 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 8129: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 8130: /* for (j=2; j<= nlstate ; j ++) */
8131: /* fprintf(ficgp,"+$%d",k+l+j-1); */
8132: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 8133: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 8134: } /* nlstate */
1.264 brouard 8135: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 8136: } /* end cpt state*/
8137: } /* end covariate */
1.296 brouard 8138: } /* End if prevbcast */
1.218 brouard 8139:
1.223 brouard 8140: /* 8eme */
1.218 brouard 8141: if(prevfcast==1){
1.288 brouard 8142: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 8143:
1.237 brouard 8144: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8145: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8146: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8147: continue;
1.211 brouard 8148: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 8149: strcpy(gplotlabel,"(");
1.288 brouard 8150: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 8151: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8152: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8153: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8154: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8155: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8156: vlv= nbcode[Tvaraff[k]][lv];
8157: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8158: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 8159: }
1.237 brouard 8160: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8161: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8162: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 8163: }
1.264 brouard 8164: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8165: fprintf(ficgp,"\n#\n");
8166: if(invalidvarcomb[k1]){
8167: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8168: continue;
8169: }
8170:
8171: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 8172: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 8173: 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 8174: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 8175: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 8176:
8177: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8178: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8179: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8180: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 8181: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8182: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8183: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8184: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 8185: if(i==istart){
1.227 brouard 8186: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
8187: }else{
8188: fprintf(ficgp,",\\\n '' ");
8189: }
8190: if(cptcoveff ==0){ /* No covariate */
8191: ioffset=2; /* Age is in 2 */
8192: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8193: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8194: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8195: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8196: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 8197: if(i==nlstate+1){
1.270 brouard 8198: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 8199: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8200: fprintf(ficgp,",\\\n '' ");
8201: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8202: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 8203: offyear, \
1.268 brouard 8204: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 8205: }else
1.227 brouard 8206: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
8207: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8208: }else{ /* more than 2 covariates */
1.270 brouard 8209: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8210: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8211: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8212: iyearc=ioffset-1;
8213: iagec=ioffset;
1.227 brouard 8214: fprintf(ficgp," u %d:(",ioffset);
8215: kl=0;
8216: strcpy(gplotcondition,"(");
8217: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
8218: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
8219: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8220: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8221: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8222: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
8223: kl++;
8224: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8225: kl++;
8226: if(k <cptcoveff && cptcoveff>1)
8227: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8228: }
8229: strcpy(gplotcondition+strlen(gplotcondition),")");
8230: /* 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 *\/ */
8231: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8232: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8233: /* '' 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*/
8234: if(i==nlstate+1){
1.270 brouard 8235: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
8236: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 8237: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8238: fprintf(ficgp," u %d:(",iagec);
8239: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
8240: iyearc, iagec, offyear, \
8241: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 8242: /* '' 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 8243: }else{
8244: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
8245: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8246: }
8247: } /* end if covariate */
8248: } /* nlstate */
1.264 brouard 8249: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 8250: } /* end cpt state*/
8251: } /* end covariate */
8252: } /* End if prevfcast */
1.227 brouard 8253:
1.296 brouard 8254: if(prevbcast==1){
1.268 brouard 8255: /* Back projection from cross-sectional to stable (mixed) for each covariate */
8256:
8257: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8258: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8259: if(m != 1 && TKresult[nres]!= k1)
8260: continue;
8261: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
8262: strcpy(gplotlabel,"(");
8263: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
8264: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8265: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8266: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8267: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8268: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8269: vlv= nbcode[Tvaraff[k]][lv];
8270: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8271: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8272: }
8273: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8274: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8275: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8276: }
8277: strcpy(gplotlabel+strlen(gplotlabel),")");
8278: fprintf(ficgp,"\n#\n");
8279: if(invalidvarcomb[k1]){
8280: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8281: continue;
8282: }
8283:
8284: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
8285: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
8286: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
8287: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
8288: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8289:
8290: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8291: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8292: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8293: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
8294: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8295: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8296: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8297: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8298: if(i==istart){
8299: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
8300: }else{
8301: fprintf(ficgp,",\\\n '' ");
8302: }
8303: if(cptcoveff ==0){ /* No covariate */
8304: ioffset=2; /* Age is in 2 */
8305: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8306: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8307: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8308: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8309: fprintf(ficgp," u %d:(", ioffset);
8310: if(i==nlstate+1){
1.270 brouard 8311: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 8312: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8313: fprintf(ficgp,",\\\n '' ");
8314: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8315: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 8316: offbyear, \
8317: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
8318: }else
8319: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
8320: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
8321: }else{ /* more than 2 covariates */
1.270 brouard 8322: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8323: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8324: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8325: iyearc=ioffset-1;
8326: iagec=ioffset;
1.268 brouard 8327: fprintf(ficgp," u %d:(",ioffset);
8328: kl=0;
8329: strcpy(gplotcondition,"(");
8330: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
8331: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
8332: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8333: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8334: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8335: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
8336: kl++;
8337: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8338: kl++;
8339: if(k <cptcoveff && cptcoveff>1)
8340: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8341: }
8342: strcpy(gplotcondition+strlen(gplotcondition),")");
8343: /* 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 *\/ */
8344: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8345: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8346: /* '' 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*/
8347: if(i==nlstate+1){
1.270 brouard 8348: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
8349: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 8350: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8351: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 8352: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 8353: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
8354: iyearc,iagec,offbyear, \
8355: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 8356: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
8357: }else{
8358: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
8359: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
8360: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
8361: }
8362: } /* end if covariate */
8363: } /* nlstate */
8364: fprintf(ficgp,"\nset out; unset label;\n");
8365: } /* end cpt state*/
8366: } /* end covariate */
1.296 brouard 8367: } /* End if prevbcast */
1.268 brouard 8368:
1.227 brouard 8369:
1.238 brouard 8370: /* 9eme writing MLE parameters */
8371: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 8372: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 8373: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 8374: for(k=1; k <=(nlstate+ndeath); k++){
8375: if (k != i) {
1.227 brouard 8376: fprintf(ficgp,"# current state %d\n",k);
8377: for(j=1; j <=ncovmodel; j++){
8378: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
8379: jk++;
8380: }
8381: fprintf(ficgp,"\n");
1.126 brouard 8382: }
8383: }
1.223 brouard 8384: }
1.187 brouard 8385: fprintf(ficgp,"##############\n#\n");
1.227 brouard 8386:
1.145 brouard 8387: /*goto avoid;*/
1.238 brouard 8388: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
8389: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 8390: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
8391: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
8392: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
8393: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
8394: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8395: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8396: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8397: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8398: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
8399: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8400: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
8401: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
8402: fprintf(ficgp,"#\n");
1.223 brouard 8403: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 8404: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 8405: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 8406: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 8407: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
8408: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 8409: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 8410: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8411: continue;
1.264 brouard 8412: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
8413: strcpy(gplotlabel,"(");
1.276 brouard 8414: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 8415: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8416: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8417: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8418: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8419: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8420: vlv= nbcode[Tvaraff[k]][lv];
8421: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8422: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8423: }
1.237 brouard 8424: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8425: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8426: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 8427: }
1.264 brouard 8428: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 8429: fprintf(ficgp,"\n#\n");
1.264 brouard 8430: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 8431: fprintf(ficgp,"\nset key outside ");
8432: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
8433: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 8434: fprintf(ficgp,"\nset ter svg size 640, 480 ");
8435: if (ng==1){
8436: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
8437: fprintf(ficgp,"\nunset log y");
8438: }else if (ng==2){
8439: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
8440: fprintf(ficgp,"\nset log y");
8441: }else if (ng==3){
8442: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
8443: fprintf(ficgp,"\nset log y");
8444: }else
8445: fprintf(ficgp,"\nunset title ");
8446: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
8447: i=1;
8448: for(k2=1; k2<=nlstate; k2++) {
8449: k3=i;
8450: for(k=1; k<=(nlstate+ndeath); k++) {
8451: if (k != k2){
8452: switch( ng) {
8453: case 1:
8454: if(nagesqr==0)
8455: fprintf(ficgp," p%d+p%d*x",i,i+1);
8456: else /* nagesqr =1 */
8457: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8458: break;
8459: case 2: /* ng=2 */
8460: if(nagesqr==0)
8461: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
8462: else /* nagesqr =1 */
8463: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8464: break;
8465: case 3:
8466: if(nagesqr==0)
8467: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
8468: else /* nagesqr =1 */
8469: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
8470: break;
8471: }
8472: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 8473: ijp=1; /* product no age */
8474: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
8475: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 8476: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 8477: switch(Typevar[j]){
8478: case 1:
8479: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8480: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
8481: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8482: if(DummyV[j]==0){/* Bug valgrind */
8483: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
8484: }else{ /* quantitative */
8485: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8486: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8487: }
8488: ij++;
1.268 brouard 8489: }
1.237 brouard 8490: }
1.329 brouard 8491: }
8492: break;
8493: case 2:
8494: if(cptcovprod >0){
8495: if(j==Tprod[ijp]) { /* */
8496: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8497: if(ijp <=cptcovprod) { /* Product */
8498: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8499: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8500: /* 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)]); */
8501: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8502: }else{ /* Vn is dummy and Vm is quanti */
8503: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8504: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8505: }
8506: }else{ /* Vn*Vm Vn is quanti */
8507: if(DummyV[Tvard[ijp][2]]==0){
8508: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8509: }else{ /* Both quanti */
8510: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8511: }
1.268 brouard 8512: }
1.329 brouard 8513: ijp++;
1.237 brouard 8514: }
1.329 brouard 8515: } /* end Tprod */
8516: }
8517: break;
8518: case 0:
8519: /* simple covariate */
1.264 brouard 8520: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 8521: if(Dummy[j]==0){
8522: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
8523: }else{ /* quantitative */
8524: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 8525: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 8526: }
1.329 brouard 8527: /* end simple */
8528: break;
8529: default:
8530: break;
8531: } /* end switch */
1.237 brouard 8532: } /* end j */
1.329 brouard 8533: }else{ /* k=k2 */
8534: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
8535: fprintf(ficgp," (1.");i=i-ncovmodel;
8536: }else
8537: i=i-ncovmodel;
1.223 brouard 8538: }
1.227 brouard 8539:
1.223 brouard 8540: if(ng != 1){
8541: fprintf(ficgp,")/(1");
1.227 brouard 8542:
1.264 brouard 8543: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8544: if(nagesqr==0)
1.264 brouard 8545: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8546: else /* nagesqr =1 */
1.264 brouard 8547: 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 8548:
1.223 brouard 8549: ij=1;
1.329 brouard 8550: ijp=1;
8551: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
8552: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
8553: switch(Typevar[j]){
8554: case 1:
8555: if(cptcovage >0){
8556: if(j==Tage[ij]) { /* Bug valgrind */
8557: if(ij <=cptcovage) { /* Bug valgrind */
8558: if(DummyV[j]==0){/* Bug valgrind */
8559: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
8560: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
8561: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
8562: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
8563: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8564: }else{ /* quantitative */
8565: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
8566: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8567: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
8568: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8569: }
8570: ij++;
8571: }
8572: }
8573: }
8574: break;
8575: case 2:
8576: if(cptcovprod >0){
8577: if(j==Tprod[ijp]) { /* */
8578: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8579: if(ijp <=cptcovprod) { /* Product */
8580: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8581: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8582: /* 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)]); */
8583: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8584: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
8585: }else{ /* Vn is dummy and Vm is quanti */
8586: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8587: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8588: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
8589: }
8590: }else{ /* Vn*Vm Vn is quanti */
8591: if(DummyV[Tvard[ijp][2]]==0){
8592: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8593: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
8594: }else{ /* Both quanti */
8595: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8596: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
8597: }
8598: }
8599: ijp++;
8600: }
8601: } /* end Tprod */
8602: } /* end if */
8603: break;
8604: case 0:
8605: /* simple covariate */
8606: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
8607: if(Dummy[j]==0){
8608: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
8609: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
8610: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
8611: }else{ /* quantitative */
8612: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
8613: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
8614: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8615: }
8616: /* end simple */
8617: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
8618: break;
8619: default:
8620: break;
8621: } /* end switch */
1.223 brouard 8622: }
8623: fprintf(ficgp,")");
8624: }
8625: fprintf(ficgp,")");
8626: if(ng ==2)
1.276 brouard 8627: 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 8628: else /* ng= 3 */
1.276 brouard 8629: 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 8630: }else{ /* end ng <> 1 */
1.223 brouard 8631: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8632: 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 8633: }
8634: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8635: fprintf(ficgp,",");
8636: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8637: fprintf(ficgp,",");
8638: i=i+ncovmodel;
8639: } /* end k */
8640: } /* end k2 */
1.276 brouard 8641: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8642: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8643: } /* end k1 */
1.223 brouard 8644: } /* end ng */
8645: /* avoid: */
8646: fflush(ficgp);
1.126 brouard 8647: } /* end gnuplot */
8648:
8649:
8650: /*************** Moving average **************/
1.219 brouard 8651: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8652: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8653:
1.222 brouard 8654: int i, cpt, cptcod;
8655: int modcovmax =1;
8656: int mobilavrange, mob;
8657: int iage=0;
1.288 brouard 8658: int firstA1=0, firstA2=0;
1.222 brouard 8659:
1.266 brouard 8660: double sum=0., sumr=0.;
1.222 brouard 8661: double age;
1.266 brouard 8662: double *sumnewp, *sumnewm, *sumnewmr;
8663: double *agemingood, *agemaxgood;
8664: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8665:
8666:
1.278 brouard 8667: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8668: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8669:
8670: sumnewp = vector(1,ncovcombmax);
8671: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8672: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8673: agemingood = vector(1,ncovcombmax);
1.266 brouard 8674: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8675: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8676: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8677:
8678: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8679: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8680: sumnewp[cptcod]=0.;
1.266 brouard 8681: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8682: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8683: }
8684: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8685:
1.266 brouard 8686: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8687: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8688: else mobilavrange=mobilav;
8689: for (age=bage; age<=fage; age++)
8690: for (i=1; i<=nlstate;i++)
8691: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8692: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8693: /* We keep the original values on the extreme ages bage, fage and for
8694: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8695: we use a 5 terms etc. until the borders are no more concerned.
8696: */
8697: for (mob=3;mob <=mobilavrange;mob=mob+2){
8698: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8699: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8700: sumnewm[cptcod]=0.;
8701: for (i=1; i<=nlstate;i++){
1.222 brouard 8702: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8703: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8704: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8705: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8706: }
8707: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8708: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8709: } /* end i */
8710: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8711: } /* end cptcod */
1.222 brouard 8712: }/* end age */
8713: }/* end mob */
1.266 brouard 8714: }else{
8715: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8716: return -1;
1.266 brouard 8717: }
8718:
8719: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8720: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8721: if(invalidvarcomb[cptcod]){
8722: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8723: continue;
8724: }
1.219 brouard 8725:
1.266 brouard 8726: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8727: sumnewm[cptcod]=0.;
8728: sumnewmr[cptcod]=0.;
8729: for (i=1; i<=nlstate;i++){
8730: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8731: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8732: }
8733: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8734: agemingoodr[cptcod]=age;
8735: }
8736: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8737: agemingood[cptcod]=age;
8738: }
8739: } /* age */
8740: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8741: sumnewm[cptcod]=0.;
1.266 brouard 8742: sumnewmr[cptcod]=0.;
1.222 brouard 8743: for (i=1; i<=nlstate;i++){
8744: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8745: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8746: }
8747: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8748: agemaxgoodr[cptcod]=age;
1.222 brouard 8749: }
8750: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8751: agemaxgood[cptcod]=age;
8752: }
8753: } /* age */
8754: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8755: /* but they will change */
1.288 brouard 8756: firstA1=0;firstA2=0;
1.266 brouard 8757: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8758: sumnewm[cptcod]=0.;
8759: sumnewmr[cptcod]=0.;
8760: for (i=1; i<=nlstate;i++){
8761: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8762: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8763: }
8764: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8765: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8766: agemaxgoodr[cptcod]=age; /* age min */
8767: for (i=1; i<=nlstate;i++)
8768: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8769: }else{ /* bad we change the value with the values of good ages */
8770: for (i=1; i<=nlstate;i++){
8771: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8772: } /* i */
8773: } /* end bad */
8774: }else{
8775: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8776: agemaxgood[cptcod]=age;
8777: }else{ /* bad we change the value with the values of good ages */
8778: for (i=1; i<=nlstate;i++){
8779: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8780: } /* i */
8781: } /* end bad */
8782: }/* end else */
8783: sum=0.;sumr=0.;
8784: for (i=1; i<=nlstate;i++){
8785: sum+=mobaverage[(int)age][i][cptcod];
8786: sumr+=probs[(int)age][i][cptcod];
8787: }
8788: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8789: if(!firstA1){
8790: firstA1=1;
8791: 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);
8792: }
8793: 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 8794: } /* end bad */
8795: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8796: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 8797: if(!firstA2){
8798: firstA2=1;
8799: 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);
8800: }
8801: 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 8802: } /* end bad */
8803: }/* age */
1.266 brouard 8804:
8805: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8806: sumnewm[cptcod]=0.;
1.266 brouard 8807: sumnewmr[cptcod]=0.;
1.222 brouard 8808: for (i=1; i<=nlstate;i++){
8809: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8810: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8811: }
8812: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8813: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8814: agemingoodr[cptcod]=age;
8815: for (i=1; i<=nlstate;i++)
8816: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8817: }else{ /* bad we change the value with the values of good ages */
8818: for (i=1; i<=nlstate;i++){
8819: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8820: } /* i */
8821: } /* end bad */
8822: }else{
8823: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8824: agemingood[cptcod]=age;
8825: }else{ /* bad */
8826: for (i=1; i<=nlstate;i++){
8827: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8828: } /* i */
8829: } /* end bad */
8830: }/* end else */
8831: sum=0.;sumr=0.;
8832: for (i=1; i<=nlstate;i++){
8833: sum+=mobaverage[(int)age][i][cptcod];
8834: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8835: }
1.266 brouard 8836: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8837: 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 8838: } /* end bad */
8839: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8840: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8841: 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 8842: } /* end bad */
8843: }/* age */
1.266 brouard 8844:
1.222 brouard 8845:
8846: for (age=bage; age<=fage; age++){
1.235 brouard 8847: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8848: sumnewp[cptcod]=0.;
8849: sumnewm[cptcod]=0.;
8850: for (i=1; i<=nlstate;i++){
8851: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8852: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8853: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8854: }
8855: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8856: }
8857: /* printf("\n"); */
8858: /* } */
1.266 brouard 8859:
1.222 brouard 8860: /* brutal averaging */
1.266 brouard 8861: /* for (i=1; i<=nlstate;i++){ */
8862: /* for (age=1; age<=bage; age++){ */
8863: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8864: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8865: /* } */
8866: /* for (age=fage; age<=AGESUP; age++){ */
8867: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8868: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8869: /* } */
8870: /* } /\* end i status *\/ */
8871: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8872: /* for (age=1; age<=AGESUP; age++){ */
8873: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8874: /* mobaverage[(int)age][i][cptcod]=0.; */
8875: /* } */
8876: /* } */
1.222 brouard 8877: }/* end cptcod */
1.266 brouard 8878: free_vector(agemaxgoodr,1, ncovcombmax);
8879: free_vector(agemaxgood,1, ncovcombmax);
8880: free_vector(agemingood,1, ncovcombmax);
8881: free_vector(agemingoodr,1, ncovcombmax);
8882: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8883: free_vector(sumnewm,1, ncovcombmax);
8884: free_vector(sumnewp,1, ncovcombmax);
8885: return 0;
8886: }/* End movingaverage */
1.218 brouard 8887:
1.126 brouard 8888:
1.296 brouard 8889:
1.126 brouard 8890: /************** Forecasting ******************/
1.296 brouard 8891: /* 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)*/
8892: 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){
8893: /* dateintemean, mean date of interviews
8894: dateprojd, year, month, day of starting projection
8895: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 8896: agemin, agemax range of age
8897: dateprev1 dateprev2 range of dates during which prevalence is computed
8898: */
1.296 brouard 8899: /* double anprojd, mprojd, jprojd; */
8900: /* double anprojf, mprojf, jprojf; */
1.267 brouard 8901: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8902: double agec; /* generic age */
1.296 brouard 8903: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 8904: double *popeffectif,*popcount;
8905: double ***p3mat;
1.218 brouard 8906: /* double ***mobaverage; */
1.126 brouard 8907: char fileresf[FILENAMELENGTH];
8908:
8909: agelim=AGESUP;
1.211 brouard 8910: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8911: in each health status at the date of interview (if between dateprev1 and dateprev2).
8912: We still use firstpass and lastpass as another selection.
8913: */
1.214 brouard 8914: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8915: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8916:
1.201 brouard 8917: strcpy(fileresf,"F_");
8918: strcat(fileresf,fileresu);
1.126 brouard 8919: if((ficresf=fopen(fileresf,"w"))==NULL) {
8920: printf("Problem with forecast resultfile: %s\n", fileresf);
8921: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8922: }
1.235 brouard 8923: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8924: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8925:
1.225 brouard 8926: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8927:
8928:
8929: stepsize=(int) (stepm+YEARM-1)/YEARM;
8930: if (stepm<=12) stepsize=1;
8931: if(estepm < stepm){
8932: printf ("Problem %d lower than %d\n",estepm, stepm);
8933: }
1.270 brouard 8934: else{
8935: hstepm=estepm;
8936: }
8937: if(estepm > stepm){ /* Yes every two year */
8938: stepsize=2;
8939: }
1.296 brouard 8940: hstepm=hstepm/stepm;
1.126 brouard 8941:
1.296 brouard 8942:
8943: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8944: /* fractional in yp1 *\/ */
8945: /* aintmean=yp; */
8946: /* yp2=modf((yp1*12),&yp); */
8947: /* mintmean=yp; */
8948: /* yp1=modf((yp2*30.5),&yp); */
8949: /* jintmean=yp; */
8950: /* if(jintmean==0) jintmean=1; */
8951: /* if(mintmean==0) mintmean=1; */
1.126 brouard 8952:
1.296 brouard 8953:
8954: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
8955: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
8956: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 8957: i1=pow(2,cptcoveff);
1.126 brouard 8958: if (cptcovn < 1){i1=1;}
8959:
1.296 brouard 8960: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 8961:
8962: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8963:
1.126 brouard 8964: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8965: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8966: for(k=1; k<=i1;k++){
1.253 brouard 8967: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8968: continue;
1.227 brouard 8969: if(invalidvarcomb[k]){
8970: printf("\nCombination (%d) projection ignored because no cases \n",k);
8971: continue;
8972: }
8973: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8974: for(j=1;j<=cptcoveff;j++) {
1.330 brouard 8975: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.227 brouard 8976: }
1.235 brouard 8977: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8978: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8979: }
1.227 brouard 8980: fprintf(ficresf," yearproj age");
8981: for(j=1; j<=nlstate+ndeath;j++){
8982: for(i=1; i<=nlstate;i++)
8983: fprintf(ficresf," p%d%d",i,j);
8984: fprintf(ficresf," wp.%d",j);
8985: }
1.296 brouard 8986: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 8987: fprintf(ficresf,"\n");
1.296 brouard 8988: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 8989: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8990: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8991: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8992: nhstepm = nhstepm/hstepm;
8993: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8994: oldm=oldms;savm=savms;
1.268 brouard 8995: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8996: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8997: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8998: for (h=0; h<=nhstepm; h++){
8999: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 9000: break;
9001: }
9002: }
9003: fprintf(ficresf,"\n");
9004: for(j=1;j<=cptcoveff;j++)
1.330 brouard 9005: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.296 brouard 9006: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 9007:
9008: for(j=1; j<=nlstate+ndeath;j++) {
9009: ppij=0.;
9010: for(i=1; i<=nlstate;i++) {
1.278 brouard 9011: if (mobilav>=1)
9012: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
9013: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
9014: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
9015: }
1.268 brouard 9016: fprintf(ficresf," %.3f", p3mat[i][j][h]);
9017: } /* end i */
9018: fprintf(ficresf," %.3f", ppij);
9019: }/* end j */
1.227 brouard 9020: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9021: } /* end agec */
1.266 brouard 9022: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
9023: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 9024: } /* end yearp */
9025: } /* end k */
1.219 brouard 9026:
1.126 brouard 9027: fclose(ficresf);
1.215 brouard 9028: printf("End of Computing forecasting \n");
9029: fprintf(ficlog,"End of Computing forecasting\n");
9030:
1.126 brouard 9031: }
9032:
1.269 brouard 9033: /************** Back Forecasting ******************/
1.296 brouard 9034: /* 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){ */
9035: 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){
9036: /* back1, year, month, day of starting backprojection
1.267 brouard 9037: agemin, agemax range of age
9038: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 9039: anback2 year of end of backprojection (same day and month as back1).
9040: prevacurrent and prev are prevalences.
1.267 brouard 9041: */
9042: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
9043: double agec; /* generic age */
1.302 brouard 9044: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 9045: double *popeffectif,*popcount;
9046: double ***p3mat;
9047: /* double ***mobaverage; */
9048: char fileresfb[FILENAMELENGTH];
9049:
1.268 brouard 9050: agelim=AGEINF;
1.267 brouard 9051: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9052: in each health status at the date of interview (if between dateprev1 and dateprev2).
9053: We still use firstpass and lastpass as another selection.
9054: */
9055: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9056: /* firstpass, lastpass, stepm, weightopt, model); */
9057:
9058: /*Do we need to compute prevalence again?*/
9059:
9060: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
9061:
9062: strcpy(fileresfb,"FB_");
9063: strcat(fileresfb,fileresu);
9064: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
9065: printf("Problem with back forecast resultfile: %s\n", fileresfb);
9066: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
9067: }
9068: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9069: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
9070:
9071: if (cptcoveff==0) ncodemax[cptcoveff]=1;
9072:
9073:
9074: stepsize=(int) (stepm+YEARM-1)/YEARM;
9075: if (stepm<=12) stepsize=1;
9076: if(estepm < stepm){
9077: printf ("Problem %d lower than %d\n",estepm, stepm);
9078: }
1.270 brouard 9079: else{
9080: hstepm=estepm;
9081: }
9082: if(estepm >= stepm){ /* Yes every two year */
9083: stepsize=2;
9084: }
1.267 brouard 9085:
9086: hstepm=hstepm/stepm;
1.296 brouard 9087: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9088: /* fractional in yp1 *\/ */
9089: /* aintmean=yp; */
9090: /* yp2=modf((yp1*12),&yp); */
9091: /* mintmean=yp; */
9092: /* yp1=modf((yp2*30.5),&yp); */
9093: /* jintmean=yp; */
9094: /* if(jintmean==0) jintmean=1; */
9095: /* if(mintmean==0) jintmean=1; */
1.267 brouard 9096:
9097: i1=pow(2,cptcoveff);
9098: if (cptcovn < 1){i1=1;}
9099:
1.296 brouard 9100: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
9101: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 9102:
9103: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
9104:
9105: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9106: for(k=1; k<=i1;k++){
9107: if(i1 != 1 && TKresult[nres]!= k)
9108: continue;
9109: if(invalidvarcomb[k]){
9110: printf("\nCombination (%d) projection ignored because no cases \n",k);
9111: continue;
9112: }
1.268 brouard 9113: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 9114: for(j=1;j<=cptcoveff;j++) {
1.330 brouard 9115: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.267 brouard 9116: }
9117: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
9118: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9119: }
9120: fprintf(ficresfb," yearbproj age");
9121: for(j=1; j<=nlstate+ndeath;j++){
9122: for(i=1; i<=nlstate;i++)
1.268 brouard 9123: fprintf(ficresfb," b%d%d",i,j);
9124: fprintf(ficresfb," b.%d",j);
1.267 brouard 9125: }
1.296 brouard 9126: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 9127: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
9128: fprintf(ficresfb,"\n");
1.296 brouard 9129: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 9130: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 9131: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
9132: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 9133: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 9134: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 9135: nhstepm = nhstepm/hstepm;
9136: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9137: oldm=oldms;savm=savms;
1.268 brouard 9138: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 9139: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 9140: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 9141: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
9142: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
9143: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 9144: for (h=0; h<=nhstepm; h++){
1.268 brouard 9145: if (h*hstepm/YEARM*stepm ==-yearp) {
9146: break;
9147: }
9148: }
9149: fprintf(ficresfb,"\n");
9150: for(j=1;j<=cptcoveff;j++)
1.330 brouard 9151: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.296 brouard 9152: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 9153: for(i=1; i<=nlstate+ndeath;i++) {
9154: ppij=0.;ppi=0.;
9155: for(j=1; j<=nlstate;j++) {
9156: /* if (mobilav==1) */
1.269 brouard 9157: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
9158: ppi=ppi+prevacurrent[(int)agec][j][k];
9159: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
9160: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 9161: /* else { */
9162: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
9163: /* } */
1.268 brouard 9164: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
9165: } /* end j */
9166: if(ppi <0.99){
9167: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9168: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
9169: }
9170: fprintf(ficresfb," %.3f", ppij);
9171: }/* end j */
1.267 brouard 9172: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9173: } /* end agec */
9174: } /* end yearp */
9175: } /* end k */
1.217 brouard 9176:
1.267 brouard 9177: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 9178:
1.267 brouard 9179: fclose(ficresfb);
9180: printf("End of Computing Back forecasting \n");
9181: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 9182:
1.267 brouard 9183: }
1.217 brouard 9184:
1.269 brouard 9185: /* Variance of prevalence limit: varprlim */
9186: 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 9187: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 9188:
9189: char fileresvpl[FILENAMELENGTH];
9190: FILE *ficresvpl;
9191: double **oldm, **savm;
9192: double **varpl; /* Variances of prevalence limits by age */
9193: int i1, k, nres, j ;
9194:
9195: strcpy(fileresvpl,"VPL_");
9196: strcat(fileresvpl,fileresu);
9197: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 9198: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 9199: exit(0);
9200: }
1.288 brouard 9201: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
9202: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 9203:
9204: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
9205: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
9206:
9207: i1=pow(2,cptcoveff);
9208: if (cptcovn < 1){i1=1;}
9209:
9210: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9211: for(k=1; k<=i1;k++){
9212: if(i1 != 1 && TKresult[nres]!= k)
9213: continue;
9214: fprintf(ficresvpl,"\n#****** ");
9215: printf("\n#****** ");
9216: fprintf(ficlog,"\n#****** ");
9217: for(j=1;j<=cptcoveff;j++) {
1.330 brouard 9218: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
9219: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
9220: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.269 brouard 9221: }
9222: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
9223: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9224: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9225: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9226: }
9227: fprintf(ficresvpl,"******\n");
9228: printf("******\n");
9229: fprintf(ficlog,"******\n");
9230:
9231: varpl=matrix(1,nlstate,(int) bage, (int) fage);
9232: oldm=oldms;savm=savms;
9233: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
9234: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
9235: /*}*/
9236: }
9237:
9238: fclose(ficresvpl);
1.288 brouard 9239: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
9240: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 9241:
9242: }
9243: /* Variance of back prevalence: varbprlim */
9244: 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){
9245: /*------- Variance of back (stable) prevalence------*/
9246:
9247: char fileresvbl[FILENAMELENGTH];
9248: FILE *ficresvbl;
9249:
9250: double **oldm, **savm;
9251: double **varbpl; /* Variances of back prevalence limits by age */
9252: int i1, k, nres, j ;
9253:
9254: strcpy(fileresvbl,"VBL_");
9255: strcat(fileresvbl,fileresu);
9256: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
9257: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
9258: exit(0);
9259: }
9260: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
9261: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
9262:
9263:
9264: i1=pow(2,cptcoveff);
9265: if (cptcovn < 1){i1=1;}
9266:
9267: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9268: for(k=1; k<=i1;k++){
9269: if(i1 != 1 && TKresult[nres]!= k)
9270: continue;
9271: fprintf(ficresvbl,"\n#****** ");
9272: printf("\n#****** ");
9273: fprintf(ficlog,"\n#****** ");
9274: for(j=1;j<=cptcoveff;j++) {
1.330 brouard 9275: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
9276: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
9277: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.269 brouard 9278: }
9279: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
9280: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9281: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9282: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9283: }
9284: fprintf(ficresvbl,"******\n");
9285: printf("******\n");
9286: fprintf(ficlog,"******\n");
9287:
9288: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
9289: oldm=oldms;savm=savms;
9290:
9291: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
9292: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
9293: /*}*/
9294: }
9295:
9296: fclose(ficresvbl);
9297: printf("done variance-covariance of back prevalence\n");fflush(stdout);
9298: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
9299:
9300: } /* End of varbprlim */
9301:
1.126 brouard 9302: /************** Forecasting *****not tested NB*************/
1.227 brouard 9303: /* 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 9304:
1.227 brouard 9305: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
9306: /* int *popage; */
9307: /* double calagedatem, agelim, kk1, kk2; */
9308: /* double *popeffectif,*popcount; */
9309: /* double ***p3mat,***tabpop,***tabpopprev; */
9310: /* /\* double ***mobaverage; *\/ */
9311: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 9312:
1.227 brouard 9313: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9314: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9315: /* agelim=AGESUP; */
9316: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 9317:
1.227 brouard 9318: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 9319:
9320:
1.227 brouard 9321: /* strcpy(filerespop,"POP_"); */
9322: /* strcat(filerespop,fileresu); */
9323: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
9324: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
9325: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
9326: /* } */
9327: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
9328: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 9329:
1.227 brouard 9330: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 9331:
1.227 brouard 9332: /* /\* if (mobilav!=0) { *\/ */
9333: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
9334: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
9335: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9336: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9337: /* /\* } *\/ */
9338: /* /\* } *\/ */
1.126 brouard 9339:
1.227 brouard 9340: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
9341: /* if (stepm<=12) stepsize=1; */
1.126 brouard 9342:
1.227 brouard 9343: /* agelim=AGESUP; */
1.126 brouard 9344:
1.227 brouard 9345: /* hstepm=1; */
9346: /* hstepm=hstepm/stepm; */
1.218 brouard 9347:
1.227 brouard 9348: /* if (popforecast==1) { */
9349: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
9350: /* printf("Problem with population file : %s\n",popfile);exit(0); */
9351: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
9352: /* } */
9353: /* popage=ivector(0,AGESUP); */
9354: /* popeffectif=vector(0,AGESUP); */
9355: /* popcount=vector(0,AGESUP); */
1.126 brouard 9356:
1.227 brouard 9357: /* i=1; */
9358: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 9359:
1.227 brouard 9360: /* imx=i; */
9361: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
9362: /* } */
1.218 brouard 9363:
1.227 brouard 9364: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
9365: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
9366: /* k=k+1; */
9367: /* fprintf(ficrespop,"\n#******"); */
9368: /* for(j=1;j<=cptcoveff;j++) { */
9369: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
9370: /* } */
9371: /* fprintf(ficrespop,"******\n"); */
9372: /* fprintf(ficrespop,"# Age"); */
9373: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
9374: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 9375:
1.227 brouard 9376: /* for (cpt=0; cpt<=0;cpt++) { */
9377: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 9378:
1.227 brouard 9379: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9380: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9381: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9382:
1.227 brouard 9383: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9384: /* oldm=oldms;savm=savms; */
9385: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 9386:
1.227 brouard 9387: /* for (h=0; h<=nhstepm; h++){ */
9388: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9389: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9390: /* } */
9391: /* for(j=1; j<=nlstate+ndeath;j++) { */
9392: /* kk1=0.;kk2=0; */
9393: /* for(i=1; i<=nlstate;i++) { */
9394: /* if (mobilav==1) */
9395: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
9396: /* else { */
9397: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
9398: /* } */
9399: /* } */
9400: /* if (h==(int)(calagedatem+12*cpt)){ */
9401: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
9402: /* /\*fprintf(ficrespop," %.3f", kk1); */
9403: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
9404: /* } */
9405: /* } */
9406: /* for(i=1; i<=nlstate;i++){ */
9407: /* kk1=0.; */
9408: /* for(j=1; j<=nlstate;j++){ */
9409: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
9410: /* } */
9411: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
9412: /* } */
1.218 brouard 9413:
1.227 brouard 9414: /* if (h==(int)(calagedatem+12*cpt)) */
9415: /* for(j=1; j<=nlstate;j++) */
9416: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
9417: /* } */
9418: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9419: /* } */
9420: /* } */
1.218 brouard 9421:
1.227 brouard 9422: /* /\******\/ */
1.218 brouard 9423:
1.227 brouard 9424: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
9425: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
9426: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9427: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9428: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9429:
1.227 brouard 9430: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9431: /* oldm=oldms;savm=savms; */
9432: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
9433: /* for (h=0; h<=nhstepm; h++){ */
9434: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9435: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9436: /* } */
9437: /* for(j=1; j<=nlstate+ndeath;j++) { */
9438: /* kk1=0.;kk2=0; */
9439: /* for(i=1; i<=nlstate;i++) { */
9440: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
9441: /* } */
9442: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
9443: /* } */
9444: /* } */
9445: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9446: /* } */
9447: /* } */
9448: /* } */
9449: /* } */
1.218 brouard 9450:
1.227 brouard 9451: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 9452:
1.227 brouard 9453: /* if (popforecast==1) { */
9454: /* free_ivector(popage,0,AGESUP); */
9455: /* free_vector(popeffectif,0,AGESUP); */
9456: /* free_vector(popcount,0,AGESUP); */
9457: /* } */
9458: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9459: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9460: /* fclose(ficrespop); */
9461: /* } /\* End of popforecast *\/ */
1.218 brouard 9462:
1.126 brouard 9463: int fileappend(FILE *fichier, char *optionfich)
9464: {
9465: if((fichier=fopen(optionfich,"a"))==NULL) {
9466: printf("Problem with file: %s\n", optionfich);
9467: fprintf(ficlog,"Problem with file: %s\n", optionfich);
9468: return (0);
9469: }
9470: fflush(fichier);
9471: return (1);
9472: }
9473:
9474:
9475: /**************** function prwizard **********************/
9476: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
9477: {
9478:
9479: /* Wizard to print covariance matrix template */
9480:
1.164 brouard 9481: char ca[32], cb[32];
9482: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 9483: int numlinepar;
9484:
9485: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9486: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9487: for(i=1; i <=nlstate; i++){
9488: jj=0;
9489: for(j=1; j <=nlstate+ndeath; j++){
9490: if(j==i) continue;
9491: jj++;
9492: /*ca[0]= k+'a'-1;ca[1]='\0';*/
9493: printf("%1d%1d",i,j);
9494: fprintf(ficparo,"%1d%1d",i,j);
9495: for(k=1; k<=ncovmodel;k++){
9496: /* printf(" %lf",param[i][j][k]); */
9497: /* fprintf(ficparo," %lf",param[i][j][k]); */
9498: printf(" 0.");
9499: fprintf(ficparo," 0.");
9500: }
9501: printf("\n");
9502: fprintf(ficparo,"\n");
9503: }
9504: }
9505: printf("# Scales (for hessian or gradient estimation)\n");
9506: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
9507: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
9508: for(i=1; i <=nlstate; i++){
9509: jj=0;
9510: for(j=1; j <=nlstate+ndeath; j++){
9511: if(j==i) continue;
9512: jj++;
9513: fprintf(ficparo,"%1d%1d",i,j);
9514: printf("%1d%1d",i,j);
9515: fflush(stdout);
9516: for(k=1; k<=ncovmodel;k++){
9517: /* printf(" %le",delti3[i][j][k]); */
9518: /* fprintf(ficparo," %le",delti3[i][j][k]); */
9519: printf(" 0.");
9520: fprintf(ficparo," 0.");
9521: }
9522: numlinepar++;
9523: printf("\n");
9524: fprintf(ficparo,"\n");
9525: }
9526: }
9527: printf("# Covariance matrix\n");
9528: /* # 121 Var(a12)\n\ */
9529: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9530: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
9531: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
9532: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
9533: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
9534: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
9535: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9536: fflush(stdout);
9537: fprintf(ficparo,"# Covariance matrix\n");
9538: /* # 121 Var(a12)\n\ */
9539: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9540: /* # ...\n\ */
9541: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9542:
9543: for(itimes=1;itimes<=2;itimes++){
9544: jj=0;
9545: for(i=1; i <=nlstate; i++){
9546: for(j=1; j <=nlstate+ndeath; j++){
9547: if(j==i) continue;
9548: for(k=1; k<=ncovmodel;k++){
9549: jj++;
9550: ca[0]= k+'a'-1;ca[1]='\0';
9551: if(itimes==1){
9552: printf("#%1d%1d%d",i,j,k);
9553: fprintf(ficparo,"#%1d%1d%d",i,j,k);
9554: }else{
9555: printf("%1d%1d%d",i,j,k);
9556: fprintf(ficparo,"%1d%1d%d",i,j,k);
9557: /* printf(" %.5le",matcov[i][j]); */
9558: }
9559: ll=0;
9560: for(li=1;li <=nlstate; li++){
9561: for(lj=1;lj <=nlstate+ndeath; lj++){
9562: if(lj==li) continue;
9563: for(lk=1;lk<=ncovmodel;lk++){
9564: ll++;
9565: if(ll<=jj){
9566: cb[0]= lk +'a'-1;cb[1]='\0';
9567: if(ll<jj){
9568: if(itimes==1){
9569: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9570: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9571: }else{
9572: printf(" 0.");
9573: fprintf(ficparo," 0.");
9574: }
9575: }else{
9576: if(itimes==1){
9577: printf(" Var(%s%1d%1d)",ca,i,j);
9578: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
9579: }else{
9580: printf(" 0.");
9581: fprintf(ficparo," 0.");
9582: }
9583: }
9584: }
9585: } /* end lk */
9586: } /* end lj */
9587: } /* end li */
9588: printf("\n");
9589: fprintf(ficparo,"\n");
9590: numlinepar++;
9591: } /* end k*/
9592: } /*end j */
9593: } /* end i */
9594: } /* end itimes */
9595:
9596: } /* end of prwizard */
9597: /******************* Gompertz Likelihood ******************************/
9598: double gompertz(double x[])
9599: {
1.302 brouard 9600: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 9601: int i,n=0; /* n is the size of the sample */
9602:
1.220 brouard 9603: for (i=1;i<=imx ; i++) {
1.126 brouard 9604: sump=sump+weight[i];
9605: /* sump=sump+1;*/
9606: num=num+1;
9607: }
1.302 brouard 9608: L=0.0;
9609: /* agegomp=AGEGOMP; */
1.126 brouard 9610: /* for (i=0; i<=imx; i++)
9611: 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]);*/
9612:
1.302 brouard 9613: for (i=1;i<=imx ; i++) {
9614: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
9615: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
9616: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
9617: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
9618: * +
9619: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
9620: */
9621: if (wav[i] > 1 || agedc[i] < AGESUP) {
9622: if (cens[i] == 1){
9623: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9624: } else if (cens[i] == 0){
1.126 brouard 9625: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 9626: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
9627: } else
9628: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 9629: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 9630: L=L+A*weight[i];
1.126 brouard 9631: /* 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 9632: }
9633: }
1.126 brouard 9634:
1.302 brouard 9635: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 9636:
9637: return -2*L*num/sump;
9638: }
9639:
1.136 brouard 9640: #ifdef GSL
9641: /******************* Gompertz_f Likelihood ******************************/
9642: double gompertz_f(const gsl_vector *v, void *params)
9643: {
1.302 brouard 9644: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 9645: double *x= (double *) v->data;
9646: int i,n=0; /* n is the size of the sample */
9647:
9648: for (i=0;i<=imx-1 ; i++) {
9649: sump=sump+weight[i];
9650: /* sump=sump+1;*/
9651: num=num+1;
9652: }
9653:
9654:
9655: /* for (i=0; i<=imx; i++)
9656: 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]);*/
9657: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9658: for (i=1;i<=imx ; i++)
9659: {
9660: if (cens[i] == 1 && wav[i]>1)
9661: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9662:
9663: if (cens[i] == 0 && wav[i]>1)
9664: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9665: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9666:
9667: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9668: if (wav[i] > 1 ) { /* ??? */
9669: LL=LL+A*weight[i];
9670: /* 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]);*/
9671: }
9672: }
9673:
9674: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9675: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9676:
9677: return -2*LL*num/sump;
9678: }
9679: #endif
9680:
1.126 brouard 9681: /******************* Printing html file ***********/
1.201 brouard 9682: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9683: int lastpass, int stepm, int weightopt, char model[],\
9684: int imx, double p[],double **matcov,double agemortsup){
9685: int i,k;
9686:
9687: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9688: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9689: for (i=1;i<=2;i++)
9690: 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 9691: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9692: fprintf(fichtm,"</ul>");
9693:
9694: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9695:
9696: 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>");
9697:
9698: for (k=agegomp;k<(agemortsup-2);k++)
9699: 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]);
9700:
9701:
9702: fflush(fichtm);
9703: }
9704:
9705: /******************* Gnuplot file **************/
1.201 brouard 9706: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9707:
9708: char dirfileres[132],optfileres[132];
1.164 brouard 9709:
1.126 brouard 9710: int ng;
9711:
9712:
9713: /*#ifdef windows */
9714: fprintf(ficgp,"cd \"%s\" \n",pathc);
9715: /*#endif */
9716:
9717:
9718: strcpy(dirfileres,optionfilefiname);
9719: strcpy(optfileres,"vpl");
1.199 brouard 9720: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9721: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9722: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9723: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9724: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9725:
9726: }
9727:
1.136 brouard 9728: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9729: {
1.126 brouard 9730:
1.136 brouard 9731: /*-------- data file ----------*/
9732: FILE *fic;
9733: char dummy[]=" ";
1.240 brouard 9734: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9735: int lstra;
1.136 brouard 9736: int linei, month, year,iout;
1.302 brouard 9737: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 9738: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9739: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9740: char *stratrunc;
1.223 brouard 9741:
1.240 brouard 9742: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9743: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.328 brouard 9744: for(v=1;v<NCOVMAX;v++){
9745: DummyV[v]=0;
9746: FixedV[v]=0;
9747: }
1.126 brouard 9748:
1.240 brouard 9749: for(v=1; v <=ncovcol;v++){
9750: DummyV[v]=0;
9751: FixedV[v]=0;
9752: }
9753: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9754: DummyV[v]=1;
9755: FixedV[v]=0;
9756: }
9757: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9758: DummyV[v]=0;
9759: FixedV[v]=1;
9760: }
9761: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9762: DummyV[v]=1;
9763: FixedV[v]=1;
9764: }
9765: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9766: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9767: 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]);
9768: }
1.126 brouard 9769:
1.136 brouard 9770: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9771: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9772: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9773: }
1.126 brouard 9774:
1.302 brouard 9775: /* Is it a BOM UTF-8 Windows file? */
9776: /* First data line */
9777: linei=0;
9778: while(fgets(line, MAXLINE, fic)) {
9779: noffset=0;
9780: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
9781: {
9782: noffset=noffset+3;
9783: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
9784: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
9785: fflush(ficlog); return 1;
9786: }
9787: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
9788: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
9789: {
9790: noffset=noffset+2;
1.304 brouard 9791: 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);
9792: 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 9793: fflush(ficlog); return 1;
9794: }
9795: else if( line[0] == 0 && line[1] == 0)
9796: {
9797: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
9798: noffset=noffset+4;
1.304 brouard 9799: 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);
9800: 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 9801: fflush(ficlog); return 1;
9802: }
9803: } else{
9804: ;/*printf(" Not a BOM file\n");*/
9805: }
9806: /* If line starts with a # it is a comment */
9807: if (line[noffset] == '#') {
9808: linei=linei+1;
9809: break;
9810: }else{
9811: break;
9812: }
9813: }
9814: fclose(fic);
9815: if((fic=fopen(datafile,"r"))==NULL) {
9816: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9817: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
9818: }
9819: /* Not a Bom file */
9820:
1.136 brouard 9821: i=1;
9822: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9823: linei=linei+1;
9824: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9825: if(line[j] == '\t')
9826: line[j] = ' ';
9827: }
9828: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9829: ;
9830: };
9831: line[j+1]=0; /* Trims blanks at end of line */
9832: if(line[0]=='#'){
9833: fprintf(ficlog,"Comment line\n%s\n",line);
9834: printf("Comment line\n%s\n",line);
9835: continue;
9836: }
9837: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9838: strcpy(line, linetmp);
1.223 brouard 9839:
9840: /* Loops on waves */
9841: for (j=maxwav;j>=1;j--){
9842: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9843: cutv(stra, strb, line, ' ');
9844: if(strb[0]=='.') { /* Missing value */
9845: lval=-1;
9846: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9847: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9848: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9849: 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);
9850: 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);
9851: return 1;
9852: }
9853: }else{
9854: errno=0;
9855: /* what_kind_of_number(strb); */
9856: dval=strtod(strb,&endptr);
9857: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9858: /* if(strb != endptr && *endptr == '\0') */
9859: /* dval=dlval; */
9860: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9861: if( strb[0]=='\0' || (*endptr != '\0')){
9862: 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);
9863: 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);
9864: return 1;
9865: }
9866: cotqvar[j][iv][i]=dval;
9867: cotvar[j][ntv+iv][i]=dval;
9868: }
9869: strcpy(line,stra);
1.223 brouard 9870: }/* end loop ntqv */
1.225 brouard 9871:
1.223 brouard 9872: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9873: cutv(stra, strb, line, ' ');
9874: if(strb[0]=='.') { /* Missing value */
9875: lval=-1;
9876: }else{
9877: errno=0;
9878: lval=strtol(strb,&endptr,10);
9879: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9880: if( strb[0]=='\0' || (*endptr != '\0')){
9881: 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);
9882: 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);
9883: return 1;
9884: }
9885: }
9886: if(lval <-1 || lval >1){
9887: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 9888: 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 9889: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9890: For example, for multinomial values like 1, 2 and 3,\n \
9891: build V1=0 V2=0 for the reference value (1),\n \
9892: V1=1 V2=0 for (2) \n \
1.223 brouard 9893: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9894: output of IMaCh is often meaningless.\n \
1.319 brouard 9895: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 9896: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 9897: 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 9898: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9899: For example, for multinomial values like 1, 2 and 3,\n \
9900: build V1=0 V2=0 for the reference value (1),\n \
9901: V1=1 V2=0 for (2) \n \
1.223 brouard 9902: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9903: output of IMaCh is often meaningless.\n \
1.319 brouard 9904: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 9905: return 1;
9906: }
9907: cotvar[j][iv][i]=(double)(lval);
9908: strcpy(line,stra);
1.223 brouard 9909: }/* end loop ntv */
1.225 brouard 9910:
1.223 brouard 9911: /* Statuses at wave */
1.137 brouard 9912: cutv(stra, strb, line, ' ');
1.223 brouard 9913: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9914: lval=-1;
1.136 brouard 9915: }else{
1.238 brouard 9916: errno=0;
9917: lval=strtol(strb,&endptr,10);
9918: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9919: if( strb[0]=='\0' || (*endptr != '\0')){
9920: 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);
9921: 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);
9922: return 1;
9923: }
1.136 brouard 9924: }
1.225 brouard 9925:
1.136 brouard 9926: s[j][i]=lval;
1.225 brouard 9927:
1.223 brouard 9928: /* Date of Interview */
1.136 brouard 9929: strcpy(line,stra);
9930: cutv(stra, strb,line,' ');
1.169 brouard 9931: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9932: }
1.169 brouard 9933: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9934: month=99;
9935: year=9999;
1.136 brouard 9936: }else{
1.225 brouard 9937: 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);
9938: 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);
9939: return 1;
1.136 brouard 9940: }
9941: anint[j][i]= (double) year;
1.302 brouard 9942: mint[j][i]= (double)month;
9943: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
9944: /* 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]); */
9945: /* 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]); */
9946: /* } */
1.136 brouard 9947: strcpy(line,stra);
1.223 brouard 9948: } /* End loop on waves */
1.225 brouard 9949:
1.223 brouard 9950: /* Date of death */
1.136 brouard 9951: cutv(stra, strb,line,' ');
1.169 brouard 9952: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9953: }
1.169 brouard 9954: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9955: month=99;
9956: year=9999;
9957: }else{
1.141 brouard 9958: 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 9959: 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);
9960: return 1;
1.136 brouard 9961: }
9962: andc[i]=(double) year;
9963: moisdc[i]=(double) month;
9964: strcpy(line,stra);
9965:
1.223 brouard 9966: /* Date of birth */
1.136 brouard 9967: cutv(stra, strb,line,' ');
1.169 brouard 9968: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9969: }
1.169 brouard 9970: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9971: month=99;
9972: year=9999;
9973: }else{
1.141 brouard 9974: 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);
9975: 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 9976: return 1;
1.136 brouard 9977: }
9978: if (year==9999) {
1.141 brouard 9979: 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);
9980: 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 9981: return 1;
9982:
1.136 brouard 9983: }
9984: annais[i]=(double)(year);
1.302 brouard 9985: moisnais[i]=(double)(month);
9986: for (j=1;j<=maxwav;j++){
9987: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
9988: 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]);
9989: 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]);
9990: }
9991: }
9992:
1.136 brouard 9993: strcpy(line,stra);
1.225 brouard 9994:
1.223 brouard 9995: /* Sample weight */
1.136 brouard 9996: cutv(stra, strb,line,' ');
9997: errno=0;
9998: dval=strtod(strb,&endptr);
9999: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 10000: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
10001: 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 10002: fflush(ficlog);
10003: return 1;
10004: }
10005: weight[i]=dval;
10006: strcpy(line,stra);
1.225 brouard 10007:
1.223 brouard 10008: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
10009: cutv(stra, strb, line, ' ');
10010: if(strb[0]=='.') { /* Missing value */
1.225 brouard 10011: lval=-1;
1.311 brouard 10012: coqvar[iv][i]=NAN;
10013: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 10014: }else{
1.225 brouard 10015: errno=0;
10016: /* what_kind_of_number(strb); */
10017: dval=strtod(strb,&endptr);
10018: /* if(strb != endptr && *endptr == '\0') */
10019: /* dval=dlval; */
10020: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10021: if( strb[0]=='\0' || (*endptr != '\0')){
10022: 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);
10023: 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);
10024: return 1;
10025: }
10026: coqvar[iv][i]=dval;
1.226 brouard 10027: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 10028: }
10029: strcpy(line,stra);
10030: }/* end loop nqv */
1.136 brouard 10031:
1.223 brouard 10032: /* Covariate values */
1.136 brouard 10033: for (j=ncovcol;j>=1;j--){
10034: cutv(stra, strb,line,' ');
1.223 brouard 10035: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 10036: lval=-1;
1.136 brouard 10037: }else{
1.225 brouard 10038: errno=0;
10039: lval=strtol(strb,&endptr,10);
10040: if( strb[0]=='\0' || (*endptr != '\0')){
10041: 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);
10042: 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);
10043: return 1;
10044: }
1.136 brouard 10045: }
10046: if(lval <-1 || lval >1){
1.225 brouard 10047: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10048: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10049: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10050: For example, for multinomial values like 1, 2 and 3,\n \
10051: build V1=0 V2=0 for the reference value (1),\n \
10052: V1=1 V2=0 for (2) \n \
1.136 brouard 10053: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10054: output of IMaCh is often meaningless.\n \
1.136 brouard 10055: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 10056: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 10057: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
10058: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 10059: For example, for multinomial values like 1, 2 and 3,\n \
10060: build V1=0 V2=0 for the reference value (1),\n \
10061: V1=1 V2=0 for (2) \n \
1.136 brouard 10062: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 10063: output of IMaCh is often meaningless.\n \
1.136 brouard 10064: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 10065: return 1;
1.136 brouard 10066: }
10067: covar[j][i]=(double)(lval);
10068: strcpy(line,stra);
10069: }
10070: lstra=strlen(stra);
1.225 brouard 10071:
1.136 brouard 10072: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
10073: stratrunc = &(stra[lstra-9]);
10074: num[i]=atol(stratrunc);
10075: }
10076: else
10077: num[i]=atol(stra);
10078: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
10079: 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;}*/
10080:
10081: i=i+1;
10082: } /* End loop reading data */
1.225 brouard 10083:
1.136 brouard 10084: *imax=i-1; /* Number of individuals */
10085: fclose(fic);
1.225 brouard 10086:
1.136 brouard 10087: return (0);
1.164 brouard 10088: /* endread: */
1.225 brouard 10089: printf("Exiting readdata: ");
10090: fclose(fic);
10091: return (1);
1.223 brouard 10092: }
1.126 brouard 10093:
1.234 brouard 10094: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 10095: char *p1 = *stri, *p2 = *stri;
1.235 brouard 10096: while (*p2 == ' ')
1.234 brouard 10097: p2++;
10098: /* while ((*p1++ = *p2++) !=0) */
10099: /* ; */
10100: /* do */
10101: /* while (*p2 == ' ') */
10102: /* p2++; */
10103: /* while (*p1++ == *p2++); */
10104: *stri=p2;
1.145 brouard 10105: }
10106:
1.330 brouard 10107: int decoderesult( char resultline[], int nres)
1.230 brouard 10108: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
10109: {
1.235 brouard 10110: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 10111: char resultsav[MAXLINE];
1.330 brouard 10112: /* int resultmodel[MAXLINE]; */
1.234 brouard 10113: int modelresult[MAXLINE];
1.230 brouard 10114: char stra[80], strb[80], strc[80], strd[80],stre[80];
10115:
1.234 brouard 10116: removefirstspace(&resultline);
1.230 brouard 10117:
10118: if (strstr(resultline,"v") !=0){
10119: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
10120: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
10121: return 1;
10122: }
10123: trimbb(resultsav, resultline);
10124: if (strlen(resultsav) >1){
10125: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
10126: }
1.253 brouard 10127: if(j == 0){ /* Resultline but no = */
10128: TKresult[nres]=0; /* Combination for the nresult and the model */
10129: return (0);
10130: }
1.234 brouard 10131: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.318 brouard 10132: printf("ERROR: the number of variables in this result line, %d, differs from the number of variables used in the model line, %d.\n",j, cptcovs);
1.310 brouard 10133: fprintf(ficlog,"ERROR: the number of variables in the resultline, %d, differs from the number of variables used in the model line, %d.\n",j, cptcovs);
1.234 brouard 10134: }
10135: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
10136: if(nbocc(resultsav,'=') >1){
1.318 brouard 10137: 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" */
10138: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.234 brouard 10139: }else
10140: cutl(strc,strd,resultsav,'=');
1.318 brouard 10141: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 10142:
1.230 brouard 10143: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 10144: 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 10145: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
10146: /* cptcovsel++; */
10147: if (nbocc(stra,'=') >0)
10148: strcpy(resultsav,stra); /* and analyzes it */
10149: }
1.235 brouard 10150: /* Checking for missing or useless values in comparison of current model needs */
1.318 brouard 10151: for(k1=1; k1<= cptcovt ;k1++){ /* Loop on model. model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10152: if(Typevar[k1]==0){ /* Single covariate in model *//*0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 10153: match=0;
1.318 brouard 10154: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
10155: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 10156: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 10157: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 10158: break;
10159: }
10160: }
10161: if(match == 0){
1.310 brouard 10162: printf("Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model);
10163: fprintf(ficlog,"Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model);
10164: return 1;
1.234 brouard 10165: }
10166: }
10167: }
1.235 brouard 10168: /* Checking for missing or useless values in comparison of current model needs */
1.318 brouard 10169: 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 10170: match=0;
1.318 brouard 10171: for(k1=1; k1<= cptcovt ;k1++){ /* loop on model: model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.235 brouard 10172: if(Typevar[k1]==0){ /* Single */
1.237 brouard 10173: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.330 brouard 10174: 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 10175: ++match;
10176: }
10177: }
10178: }
10179: if(match == 0){
10180: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
1.310 brouard 10181: fprintf(ficlog,"Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
10182: return 1;
1.234 brouard 10183: }else if(match > 1){
10184: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
1.310 brouard 10185: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
10186: return 1;
1.234 brouard 10187: }
10188: }
1.235 brouard 10189:
1.234 brouard 10190: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 10191: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 10192: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
10193: /* 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*/
10194: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 10195: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
10196: /* 1 0 0 0 */
10197: /* 2 1 0 0 */
10198: /* 3 0 1 0 */
1.330 brouard 10199: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 10200: /* 5 0 0 1 */
1.330 brouard 10201: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 10202: /* 7 0 1 1 */
10203: /* 8 1 1 1 */
1.237 brouard 10204: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
10205: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
10206: /* V5*age V5 known which value for nres? */
10207: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.330 brouard 10208: 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 10209: /* k counting number of combination of single dummies in the equation model */
! 10210: /* k4 counting single dummies in the equation model */
! 10211: /* k4q counting single quantitatives in the equation model */
! 10212: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Dummy and Single */
! 10213: /* k4+1= position in the resultline V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) */
1.330 brouard 10214: /* modelresult[k3]=k1: k3th position in the result line correspond to the k1 position in the model line */
10215: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
10216: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
10217: /* k3 is the position in the nres result line of the k1th variable of the model equation */
1.331 ! brouard 10218: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
! 10219: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
1.330 brouard 10220: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
10221: /* Tvresult[nres][result_position]= id of the dummy variable at the result_position in the nres resultline */
10222: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
10223: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
10224: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
10225: 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)*/
10226: k+=Tvalsel[k3]*pow(2,k4); /* nres=1 k1=2 Tvalsel[1]=1 (V4=1); k1=3 k3=2 Tvalsel[2]=0 (V3=0) */
1.331 ! brouard 10227: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.330 brouard 10228: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
1.237 brouard 10229: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
10230: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 10231: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
10232: k4++;;
1.331 ! brouard 10233: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 10234: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
10235: /* Tqvresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
10236: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
10237: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
1.318 brouard 10238: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.237 brouard 10239: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
10240: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
10241: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 10242: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 10243: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
10244: k4q++;;
1.331 ! brouard 10245: }else if( Dummy[k1]==2 ){ /* For dummy with age product */
! 10246: /* Tvar[k1]; */ /* Age variable */
! 10247: k3= resultmodel[nres][Tvar[k1]]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
! 10248: 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)*/
! 10249: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
! 10250: printf("Decoderesult Dummy with age k=%d, k1=%d Tvar[%d]=V%d k2=Tvarsel[%d]=%d Tvalsel[%d]=%d\n",k, k1, k1, Tvar[k1], k3,(int)Tvarsel[k3], k3, (int)Tvalsel[k3]);
! 10251: }else if( Dummy[k1]==3 ){ /* For quant with age product */
! 10252: k3q= resultmodel[nres][Tvar[k1]]; /* resultmodel[1(V5)] = 25.1=k3q */
! 10253: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
! 10254: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
! 10255: printf("Decoderesult Quantitative with age nres=%d, k1=%d, Tvar[%d]=V%d V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k1, k1, Tvar[k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
! 10256: }else if(Typevar[k1]==2 ){ /* For product quant or dummy (not with age) */
! 10257: printf("Decoderesult Quantitative or Dummy (not with age) nres=%d k1=%d Tvar[%d]=%d \n",nres, k1, k1, Tvar[k1]);
1.330 brouard 10258: }else{
1.331 ! brouard 10259: printf("Error Decodemodel probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
! 10260: fprintf(ficlog,"Error Decodemodel probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 10261: }
10262: }
1.234 brouard 10263:
1.235 brouard 10264: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 10265: return (0);
10266: }
1.235 brouard 10267:
1.230 brouard 10268: int decodemodel( char model[], int lastobs)
10269: /**< This routine decodes the model and returns:
1.224 brouard 10270: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
10271: * - nagesqr = 1 if age*age in the model, otherwise 0.
10272: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
10273: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
10274: * - cptcovage number of covariates with age*products =2
10275: * - cptcovs number of simple covariates
10276: * - 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
10277: * which is a new column after the 9 (ncovcol) variables.
1.319 brouard 10278: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 10279: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
10280: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
10281: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
10282: */
1.319 brouard 10283: /* 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 10284: {
1.238 brouard 10285: int i, j, k, ks, v;
1.227 brouard 10286: int j1, k1, k2, k3, k4;
1.136 brouard 10287: char modelsav[80];
1.145 brouard 10288: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 10289: char *strpt;
1.136 brouard 10290:
1.145 brouard 10291: /*removespace(model);*/
1.136 brouard 10292: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 10293: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 10294: if (strstr(model,"AGE") !=0){
1.192 brouard 10295: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
10296: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 10297: return 1;
10298: }
1.141 brouard 10299: if (strstr(model,"v") !=0){
10300: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
10301: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
10302: return 1;
10303: }
1.187 brouard 10304: strcpy(modelsav,model);
10305: if ((strpt=strstr(model,"age*age")) !=0){
10306: printf(" strpt=%s, model=%s\n",strpt, model);
10307: if(strpt != model){
1.234 brouard 10308: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10309: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10310: corresponding column of parameters.\n",model);
1.234 brouard 10311: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10312: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10313: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 10314: return 1;
1.225 brouard 10315: }
1.187 brouard 10316: nagesqr=1;
10317: if (strstr(model,"+age*age") !=0)
1.234 brouard 10318: substrchaine(modelsav, model, "+age*age");
1.187 brouard 10319: else if (strstr(model,"age*age+") !=0)
1.234 brouard 10320: substrchaine(modelsav, model, "age*age+");
1.187 brouard 10321: else
1.234 brouard 10322: substrchaine(modelsav, model, "age*age");
1.187 brouard 10323: }else
10324: nagesqr=0;
10325: if (strlen(modelsav) >1){
10326: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
10327: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 10328: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 10329: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 10330: * cst, age and age*age
10331: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
10332: /* including age products which are counted in cptcovage.
10333: * but the covariates which are products must be treated
10334: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 10335: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
10336: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 10337:
10338:
1.187 brouard 10339: /* Design
10340: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
10341: * < ncovcol=8 >
10342: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
10343: * k= 1 2 3 4 5 6 7 8
10344: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
10345: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 10346: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
10347: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 10348: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
10349: * Tage[++cptcovage]=k
10350: * if products, new covar are created after ncovcol with k1
10351: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
10352: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
10353: * 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
10354: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
10355: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
10356: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
10357: * < ncovcol=8 >
10358: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
10359: * k= 1 2 3 4 5 6 7 8 9 10 11 12
10360: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
1.319 brouard 10361: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
1.187 brouard 10362: * p Tprod[1]@2={ 6, 5}
10363: *p Tvard[1][1]@4= {7, 8, 5, 6}
10364: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
10365: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 10366: *How to reorganize? Tvars(orted)
1.187 brouard 10367: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
10368: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
10369: * {2, 1, 4, 8, 5, 6, 3, 7}
10370: * Struct []
10371: */
1.225 brouard 10372:
1.187 brouard 10373: /* This loop fills the array Tvar from the string 'model'.*/
10374: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
10375: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
10376: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
10377: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
10378: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
10379: /* k=1 Tvar[1]=2 (from V2) */
10380: /* k=5 Tvar[5] */
10381: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 10382: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 10383: /* } */
1.198 brouard 10384: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 10385: /*
10386: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 10387: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
10388: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
10389: }
1.187 brouard 10390: cptcovage=0;
1.319 brouard 10391: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
10392: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
10393: 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" */
10394: if (nbocc(modelsav,'+')==0)
10395: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 10396: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
10397: /*scanf("%d",i);*/
1.319 brouard 10398: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age */
10399: 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 10400: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
10401: /* covar is not filled and then is empty */
10402: cptcovprod--;
10403: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
1.319 brouard 10404: 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 10405: Typevar[k]=1; /* 1 for age product */
1.319 brouard 10406: cptcovage++; /* Counts the number of covariates which include age as a product */
10407: 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 10408: /*printf("stre=%s ", stre);*/
10409: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
10410: cptcovprod--;
10411: cutl(stre,strb,strc,'V');
10412: Tvar[k]=atoi(stre);
10413: Typevar[k]=1; /* 1 for age product */
10414: cptcovage++;
10415: Tage[cptcovage]=k;
10416: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
10417: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
10418: cptcovn++;
10419: cptcovprodnoage++;k1++;
10420: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
10421: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
10422: because this model-covariate is a construction we invent a new column
10423: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
1.319 brouard 10424: If already ncovcol=4 and model=V2 + V1 +V1*V4 +age*V3 +V3*V2
10425: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
10426: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=4 etc */
1.234 brouard 10427: Typevar[k]=2; /* 2 for double fixed dummy covariates */
10428: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
10429: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
1.319 brouard 10430: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
1.234 brouard 10431: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
1.330 brouard 10432: Tvardk[k][1] =atoi(strc); /* m 1 for V1*/
1.234 brouard 10433: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
1.330 brouard 10434: Tvardk[k][2] =atoi(stre); /* n 4 for V4*/
1.234 brouard 10435: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
10436: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
10437: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 10438: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 10439: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
10440: for (i=1; i<=lastobs;i++){
10441: /* Computes the new covariate which is a product of
10442: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
10443: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
10444: }
10445: } /* End age is not in the model */
10446: } /* End if model includes a product */
1.319 brouard 10447: else { /* not a product */
1.234 brouard 10448: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
10449: /* scanf("%d",i);*/
10450: cutl(strd,strc,strb,'V');
10451: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
10452: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
10453: Tvar[k]=atoi(strd);
10454: Typevar[k]=0; /* 0 for simple covariates */
10455: }
10456: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 10457: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 10458: scanf("%d",i);*/
1.187 brouard 10459: } /* end of loop + on total covariates */
10460: } /* end if strlen(modelsave == 0) age*age might exist */
10461: } /* end if strlen(model == 0) */
1.136 brouard 10462:
10463: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
10464: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 10465:
1.136 brouard 10466: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 10467: printf("cptcovprod=%d ", cptcovprod);
10468: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
10469: scanf("%d ",i);*/
10470:
10471:
1.230 brouard 10472: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
10473: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 10474: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
10475: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
10476: k = 1 2 3 4 5 6 7 8 9
10477: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 10478: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 10479: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
10480: Dummy[k] 1 0 0 0 3 1 1 2 3
10481: Tmodelind[combination of covar]=k;
1.225 brouard 10482: */
10483: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 10484: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 10485: /* 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 10486: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 10487: printf("Model=1+age+%s\n\
1.227 brouard 10488: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10489: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10490: 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 10491: fprintf(ficlog,"Model=1+age+%s\n\
1.227 brouard 10492: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10493: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10494: 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 10495: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 10496: 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 */
10497: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 10498: Fixed[k]= 0;
10499: Dummy[k]= 0;
1.225 brouard 10500: ncoveff++;
1.232 brouard 10501: ncovf++;
1.234 brouard 10502: nsd++;
10503: modell[k].maintype= FTYPE;
10504: TvarsD[nsd]=Tvar[k];
10505: TvarsDind[nsd]=k;
1.330 brouard 10506: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 10507: TvarF[ncovf]=Tvar[k];
10508: TvarFind[ncovf]=k;
10509: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10510: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10511: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
10512: Fixed[k]= 0;
10513: Dummy[k]= 0;
10514: ncoveff++;
10515: ncovf++;
10516: modell[k].maintype= FTYPE;
10517: TvarF[ncovf]=Tvar[k];
1.330 brouard 10518: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
1.234 brouard 10519: TvarFind[ncovf]=k;
1.230 brouard 10520: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 10521: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 10522: }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 10523: Fixed[k]= 0;
10524: Dummy[k]= 1;
1.230 brouard 10525: nqfveff++;
1.234 brouard 10526: modell[k].maintype= FTYPE;
10527: modell[k].subtype= FQ;
10528: nsq++;
10529: TvarsQ[nsq]=Tvar[k];
10530: TvarsQind[nsq]=k;
1.232 brouard 10531: ncovf++;
1.234 brouard 10532: TvarF[ncovf]=Tvar[k];
10533: TvarFind[ncovf]=k;
1.231 brouard 10534: 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 10535: 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 10536: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 10537: Fixed[k]= 1;
10538: Dummy[k]= 0;
1.225 brouard 10539: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 10540: modell[k].maintype= VTYPE;
10541: modell[k].subtype= VD;
10542: nsd++;
10543: TvarsD[nsd]=Tvar[k];
10544: TvarsDind[nsd]=k;
1.330 brouard 10545: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 10546: ncovv++; /* Only simple time varying variables */
10547: TvarV[ncovv]=Tvar[k];
1.242 brouard 10548: 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 10549: 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 */
10550: 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 10551: 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);
10552: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 10553: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 10554: Fixed[k]= 1;
10555: Dummy[k]= 1;
10556: nqtveff++;
10557: modell[k].maintype= VTYPE;
10558: modell[k].subtype= VQ;
10559: ncovv++; /* Only simple time varying variables */
10560: nsq++;
1.319 brouard 10561: TvarsQ[nsq]=Tvar[k]; /* k=1 Tvar=5 nsq=1 TvarsQ[1]=5 */
1.234 brouard 10562: TvarsQind[nsq]=k;
10563: TvarV[ncovv]=Tvar[k];
1.242 brouard 10564: 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 10565: 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 */
10566: 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 10567: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
10568: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
10569: 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 10570: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 10571: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 10572: ncova++;
10573: TvarA[ncova]=Tvar[k];
10574: TvarAind[ncova]=k;
1.231 brouard 10575: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 10576: Fixed[k]= 2;
10577: Dummy[k]= 2;
10578: modell[k].maintype= ATYPE;
10579: modell[k].subtype= APFD;
10580: /* ncoveff++; */
1.227 brouard 10581: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 10582: Fixed[k]= 2;
10583: Dummy[k]= 3;
10584: modell[k].maintype= ATYPE;
10585: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
10586: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 10587: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 10588: Fixed[k]= 3;
10589: Dummy[k]= 2;
10590: modell[k].maintype= ATYPE;
10591: modell[k].subtype= APVD; /* Product age * varying dummy */
10592: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 10593: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10594: Fixed[k]= 3;
10595: Dummy[k]= 3;
10596: modell[k].maintype= ATYPE;
10597: modell[k].subtype= APVQ; /* Product age * varying quantitative */
10598: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 10599: }
10600: }else if (Typevar[k] == 2) { /* product without age */
10601: k1=Tposprod[k];
10602: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 10603: if(Tvard[k1][2] <=ncovcol){
10604: Fixed[k]= 1;
10605: Dummy[k]= 0;
10606: modell[k].maintype= FTYPE;
10607: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
10608: ncovf++; /* Fixed variables without age */
10609: TvarF[ncovf]=Tvar[k];
10610: TvarFind[ncovf]=k;
10611: }else if(Tvard[k1][2] <=ncovcol+nqv){
10612: Fixed[k]= 0; /* or 2 ?*/
10613: Dummy[k]= 1;
10614: modell[k].maintype= FTYPE;
10615: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
10616: ncovf++; /* Varying variables without age */
10617: TvarF[ncovf]=Tvar[k];
10618: TvarFind[ncovf]=k;
10619: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10620: Fixed[k]= 1;
10621: Dummy[k]= 0;
10622: modell[k].maintype= VTYPE;
10623: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
10624: ncovv++; /* Varying variables without age */
10625: TvarV[ncovv]=Tvar[k];
10626: TvarVind[ncovv]=k;
10627: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10628: Fixed[k]= 1;
10629: Dummy[k]= 1;
10630: modell[k].maintype= VTYPE;
10631: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
10632: ncovv++; /* Varying variables without age */
10633: TvarV[ncovv]=Tvar[k];
10634: TvarVind[ncovv]=k;
10635: }
1.227 brouard 10636: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 10637: if(Tvard[k1][2] <=ncovcol){
10638: Fixed[k]= 0; /* or 2 ?*/
10639: Dummy[k]= 1;
10640: modell[k].maintype= FTYPE;
10641: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
10642: ncovf++; /* Fixed variables without age */
10643: TvarF[ncovf]=Tvar[k];
10644: TvarFind[ncovf]=k;
10645: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10646: Fixed[k]= 1;
10647: Dummy[k]= 1;
10648: modell[k].maintype= VTYPE;
10649: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
10650: ncovv++; /* Varying variables without age */
10651: TvarV[ncovv]=Tvar[k];
10652: TvarVind[ncovv]=k;
10653: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10654: Fixed[k]= 1;
10655: Dummy[k]= 1;
10656: modell[k].maintype= VTYPE;
10657: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
10658: ncovv++; /* Varying variables without age */
10659: TvarV[ncovv]=Tvar[k];
10660: TvarVind[ncovv]=k;
10661: ncovv++; /* Varying variables without age */
10662: TvarV[ncovv]=Tvar[k];
10663: TvarVind[ncovv]=k;
10664: }
1.227 brouard 10665: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 10666: if(Tvard[k1][2] <=ncovcol){
10667: Fixed[k]= 1;
10668: Dummy[k]= 1;
10669: modell[k].maintype= VTYPE;
10670: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
10671: ncovv++; /* Varying variables without age */
10672: TvarV[ncovv]=Tvar[k];
10673: TvarVind[ncovv]=k;
10674: }else if(Tvard[k1][2] <=ncovcol+nqv){
10675: Fixed[k]= 1;
10676: Dummy[k]= 1;
10677: modell[k].maintype= VTYPE;
10678: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
10679: ncovv++; /* Varying variables without age */
10680: TvarV[ncovv]=Tvar[k];
10681: TvarVind[ncovv]=k;
10682: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10683: Fixed[k]= 1;
10684: Dummy[k]= 0;
10685: modell[k].maintype= VTYPE;
10686: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
10687: ncovv++; /* Varying variables without age */
10688: TvarV[ncovv]=Tvar[k];
10689: TvarVind[ncovv]=k;
10690: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10691: Fixed[k]= 1;
10692: Dummy[k]= 1;
10693: modell[k].maintype= VTYPE;
10694: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
10695: ncovv++; /* Varying variables without age */
10696: TvarV[ncovv]=Tvar[k];
10697: TvarVind[ncovv]=k;
10698: }
1.227 brouard 10699: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10700: if(Tvard[k1][2] <=ncovcol){
10701: Fixed[k]= 1;
10702: Dummy[k]= 1;
10703: modell[k].maintype= VTYPE;
10704: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
10705: ncovv++; /* Varying variables without age */
10706: TvarV[ncovv]=Tvar[k];
10707: TvarVind[ncovv]=k;
10708: }else if(Tvard[k1][2] <=ncovcol+nqv){
10709: Fixed[k]= 1;
10710: Dummy[k]= 1;
10711: modell[k].maintype= VTYPE;
10712: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
10713: ncovv++; /* Varying variables without age */
10714: TvarV[ncovv]=Tvar[k];
10715: TvarVind[ncovv]=k;
10716: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10717: Fixed[k]= 1;
10718: Dummy[k]= 1;
10719: modell[k].maintype= VTYPE;
10720: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
10721: ncovv++; /* Varying variables without age */
10722: TvarV[ncovv]=Tvar[k];
10723: TvarVind[ncovv]=k;
10724: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10725: Fixed[k]= 1;
10726: Dummy[k]= 1;
10727: modell[k].maintype= VTYPE;
10728: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
10729: ncovv++; /* Varying variables without age */
10730: TvarV[ncovv]=Tvar[k];
10731: TvarVind[ncovv]=k;
10732: }
1.227 brouard 10733: }else{
1.240 brouard 10734: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10735: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10736: } /*end k1*/
1.225 brouard 10737: }else{
1.226 brouard 10738: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10739: 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 10740: }
1.227 brouard 10741: 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 10742: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10743: 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]);
10744: }
10745: /* Searching for doublons in the model */
10746: for(k1=1; k1<= cptcovt;k1++){
10747: for(k2=1; k2 <k1;k2++){
1.285 brouard 10748: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10749: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10750: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10751: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10752: 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]);
10753: 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 10754: return(1);
10755: }
10756: }else if (Typevar[k1] ==2){
10757: k3=Tposprod[k1];
10758: k4=Tposprod[k2];
10759: 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])) ){
10760: 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]]);
10761: 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);
10762: return(1);
10763: }
10764: }
1.227 brouard 10765: }
10766: }
1.225 brouard 10767: }
10768: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10769: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10770: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10771: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10772: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10773: /*endread:*/
1.225 brouard 10774: printf("Exiting decodemodel: ");
10775: return (1);
1.136 brouard 10776: }
10777:
1.169 brouard 10778: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10779: {/* Check ages at death */
1.136 brouard 10780: int i, m;
1.218 brouard 10781: int firstone=0;
10782:
1.136 brouard 10783: for (i=1; i<=imx; i++) {
10784: for(m=2; (m<= maxwav); m++) {
10785: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10786: anint[m][i]=9999;
1.216 brouard 10787: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10788: s[m][i]=-1;
1.136 brouard 10789: }
10790: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10791: *nberr = *nberr + 1;
1.218 brouard 10792: if(firstone == 0){
10793: firstone=1;
1.260 brouard 10794: 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 10795: }
1.262 brouard 10796: 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 10797: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10798: }
10799: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10800: (*nberr)++;
1.259 brouard 10801: 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 10802: 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 10803: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10804: }
10805: }
10806: }
10807:
10808: for (i=1; i<=imx; i++) {
10809: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10810: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10811: 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 10812: if (s[m][i] >= nlstate+1) {
1.169 brouard 10813: if(agedc[i]>0){
10814: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10815: agev[m][i]=agedc[i];
1.214 brouard 10816: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10817: }else {
1.136 brouard 10818: if ((int)andc[i]!=9999){
10819: nbwarn++;
10820: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10821: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10822: agev[m][i]=-1;
10823: }
10824: }
1.169 brouard 10825: } /* agedc > 0 */
1.214 brouard 10826: } /* end if */
1.136 brouard 10827: else if(s[m][i] !=9){ /* Standard case, age in fractional
10828: years but with the precision of a month */
10829: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10830: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10831: agev[m][i]=1;
10832: else if(agev[m][i] < *agemin){
10833: *agemin=agev[m][i];
10834: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10835: }
10836: else if(agev[m][i] >*agemax){
10837: *agemax=agev[m][i];
1.156 brouard 10838: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10839: }
10840: /*agev[m][i]=anint[m][i]-annais[i];*/
10841: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10842: } /* en if 9*/
1.136 brouard 10843: else { /* =9 */
1.214 brouard 10844: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10845: agev[m][i]=1;
10846: s[m][i]=-1;
10847: }
10848: }
1.214 brouard 10849: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10850: agev[m][i]=1;
1.214 brouard 10851: else{
10852: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10853: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10854: agev[m][i]=0;
10855: }
10856: } /* End for lastpass */
10857: }
1.136 brouard 10858:
10859: for (i=1; i<=imx; i++) {
10860: for(m=firstpass; (m<=lastpass); m++){
10861: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10862: (*nberr)++;
1.136 brouard 10863: 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);
10864: 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);
10865: return 1;
10866: }
10867: }
10868: }
10869:
10870: /*for (i=1; i<=imx; i++){
10871: for (m=firstpass; (m<lastpass); m++){
10872: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10873: }
10874:
10875: }*/
10876:
10877:
1.139 brouard 10878: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10879: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10880:
10881: return (0);
1.164 brouard 10882: /* endread:*/
1.136 brouard 10883: printf("Exiting calandcheckages: ");
10884: return (1);
10885: }
10886:
1.172 brouard 10887: #if defined(_MSC_VER)
10888: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10889: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10890: //#include "stdafx.h"
10891: //#include <stdio.h>
10892: //#include <tchar.h>
10893: //#include <windows.h>
10894: //#include <iostream>
10895: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10896:
10897: LPFN_ISWOW64PROCESS fnIsWow64Process;
10898:
10899: BOOL IsWow64()
10900: {
10901: BOOL bIsWow64 = FALSE;
10902:
10903: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10904: // (HANDLE, PBOOL);
10905:
10906: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10907:
10908: HMODULE module = GetModuleHandle(_T("kernel32"));
10909: const char funcName[] = "IsWow64Process";
10910: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10911: GetProcAddress(module, funcName);
10912:
10913: if (NULL != fnIsWow64Process)
10914: {
10915: if (!fnIsWow64Process(GetCurrentProcess(),
10916: &bIsWow64))
10917: //throw std::exception("Unknown error");
10918: printf("Unknown error\n");
10919: }
10920: return bIsWow64 != FALSE;
10921: }
10922: #endif
1.177 brouard 10923:
1.191 brouard 10924: void syscompilerinfo(int logged)
1.292 brouard 10925: {
10926: #include <stdint.h>
10927:
10928: /* #include "syscompilerinfo.h"*/
1.185 brouard 10929: /* command line Intel compiler 32bit windows, XP compatible:*/
10930: /* /GS /W3 /Gy
10931: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10932: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10933: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10934: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10935: */
10936: /* 64 bits */
1.185 brouard 10937: /*
10938: /GS /W3 /Gy
10939: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10940: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10941: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10942: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10943: /* Optimization are useless and O3 is slower than O2 */
10944: /*
10945: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10946: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10947: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10948: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10949: */
1.186 brouard 10950: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10951: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10952: /PDB:"visual studio
10953: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10954: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10955: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10956: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10957: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10958: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10959: uiAccess='false'"
10960: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10961: /NOLOGO /TLBID:1
10962: */
1.292 brouard 10963:
10964:
1.177 brouard 10965: #if defined __INTEL_COMPILER
1.178 brouard 10966: #if defined(__GNUC__)
10967: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10968: #endif
1.177 brouard 10969: #elif defined(__GNUC__)
1.179 brouard 10970: #ifndef __APPLE__
1.174 brouard 10971: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10972: #endif
1.177 brouard 10973: struct utsname sysInfo;
1.178 brouard 10974: int cross = CROSS;
10975: if (cross){
10976: printf("Cross-");
1.191 brouard 10977: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10978: }
1.174 brouard 10979: #endif
10980:
1.191 brouard 10981: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10982: #if defined(__clang__)
1.191 brouard 10983: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10984: #endif
10985: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10986: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10987: #endif
10988: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10989: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10990: #endif
10991: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10992: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10993: #endif
10994: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10995: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10996: #endif
10997: #if defined(_MSC_VER)
1.191 brouard 10998: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10999: #endif
11000: #if defined(__PGI)
1.191 brouard 11001: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 11002: #endif
11003: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 11004: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 11005: #endif
1.191 brouard 11006: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 11007:
1.167 brouard 11008: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
11009: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
11010: // Windows (x64 and x86)
1.191 brouard 11011: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 11012: #elif __unix__ // all unices, not all compilers
11013: // Unix
1.191 brouard 11014: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 11015: #elif __linux__
11016: // linux
1.191 brouard 11017: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 11018: #elif __APPLE__
1.174 brouard 11019: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 11020: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 11021: #endif
11022:
11023: /* __MINGW32__ */
11024: /* __CYGWIN__ */
11025: /* __MINGW64__ */
11026: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
11027: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
11028: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
11029: /* _WIN64 // Defined for applications for Win64. */
11030: /* _M_X64 // Defined for compilations that target x64 processors. */
11031: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 11032:
1.167 brouard 11033: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 11034: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 11035: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 11036: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 11037: #else
1.191 brouard 11038: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 11039: #endif
11040:
1.169 brouard 11041: #if defined(__GNUC__)
11042: # if defined(__GNUC_PATCHLEVEL__)
11043: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11044: + __GNUC_MINOR__ * 100 \
11045: + __GNUC_PATCHLEVEL__)
11046: # else
11047: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
11048: + __GNUC_MINOR__ * 100)
11049: # endif
1.174 brouard 11050: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 11051: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 11052:
11053: if (uname(&sysInfo) != -1) {
11054: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 11055: 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 11056: }
11057: else
11058: perror("uname() error");
1.179 brouard 11059: //#ifndef __INTEL_COMPILER
11060: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 11061: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 11062: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 11063: #endif
1.169 brouard 11064: #endif
1.172 brouard 11065:
1.286 brouard 11066: // void main ()
1.172 brouard 11067: // {
1.169 brouard 11068: #if defined(_MSC_VER)
1.174 brouard 11069: if (IsWow64()){
1.191 brouard 11070: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
11071: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 11072: }
11073: else{
1.191 brouard 11074: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
11075: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 11076: }
1.172 brouard 11077: // printf("\nPress Enter to continue...");
11078: // getchar();
11079: // }
11080:
1.169 brouard 11081: #endif
11082:
1.167 brouard 11083:
1.219 brouard 11084: }
1.136 brouard 11085:
1.219 brouard 11086: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 11087: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.235 brouard 11088: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 11089: /* double ftolpl = 1.e-10; */
1.180 brouard 11090: double age, agebase, agelim;
1.203 brouard 11091: double tot;
1.180 brouard 11092:
1.202 brouard 11093: strcpy(filerespl,"PL_");
11094: strcat(filerespl,fileresu);
11095: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 11096: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
11097: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 11098: }
1.288 brouard 11099: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
11100: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 11101: pstamp(ficrespl);
1.288 brouard 11102: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 11103: fprintf(ficrespl,"#Age ");
11104: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
11105: fprintf(ficrespl,"\n");
1.180 brouard 11106:
1.219 brouard 11107: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 11108:
1.219 brouard 11109: agebase=ageminpar;
11110: agelim=agemaxpar;
1.180 brouard 11111:
1.227 brouard 11112: /* i1=pow(2,ncoveff); */
1.234 brouard 11113: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 11114: if (cptcovn < 1){i1=1;}
1.180 brouard 11115:
1.238 brouard 11116: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
11117: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 11118: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 11119: continue;
1.235 brouard 11120:
1.238 brouard 11121: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11122: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
11123: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
11124: /* k=k+1; */
11125: /* to clean */
11126: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
11127: fprintf(ficrespl,"#******");
11128: printf("#******");
11129: fprintf(ficlog,"#******");
11130: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
1.330 brouard 11131: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /* Here problem for varying dummy*/
11132: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
11133: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.238 brouard 11134: }
11135: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
11136: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11137: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11138: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11139: }
11140: fprintf(ficrespl,"******\n");
11141: printf("******\n");
11142: fprintf(ficlog,"******\n");
11143: if(invalidvarcomb[k]){
11144: printf("\nCombination (%d) ignored because no case \n",k);
11145: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
11146: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
11147: continue;
11148: }
1.219 brouard 11149:
1.238 brouard 11150: fprintf(ficrespl,"#Age ");
11151: for(j=1;j<=cptcoveff;j++) {
1.330 brouard 11152: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.238 brouard 11153: }
11154: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
11155: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 11156:
1.238 brouard 11157: for (age=agebase; age<=agelim; age++){
11158: /* for (age=agebase; age<=agebase; age++){ */
11159: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
11160: fprintf(ficrespl,"%.0f ",age );
11161: for(j=1;j<=cptcoveff;j++)
1.330 brouard 11162: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.238 brouard 11163: tot=0.;
11164: for(i=1; i<=nlstate;i++){
11165: tot += prlim[i][i];
11166: fprintf(ficrespl," %.5f", prlim[i][i]);
11167: }
11168: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
11169: } /* Age */
11170: /* was end of cptcod */
11171: } /* cptcov */
11172: } /* nres */
1.219 brouard 11173: return 0;
1.180 brouard 11174: }
11175:
1.218 brouard 11176: 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 11177: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 11178:
11179: /* Computes the back prevalence limit for any combination of covariate values
11180: * at any age between ageminpar and agemaxpar
11181: */
1.235 brouard 11182: int i, j, k, i1, nres=0 ;
1.217 brouard 11183: /* double ftolpl = 1.e-10; */
11184: double age, agebase, agelim;
11185: double tot;
1.218 brouard 11186: /* double ***mobaverage; */
11187: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 11188:
11189: strcpy(fileresplb,"PLB_");
11190: strcat(fileresplb,fileresu);
11191: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 11192: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
11193: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 11194: }
1.288 brouard 11195: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
11196: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 11197: pstamp(ficresplb);
1.288 brouard 11198: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 11199: fprintf(ficresplb,"#Age ");
11200: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
11201: fprintf(ficresplb,"\n");
11202:
1.218 brouard 11203:
11204: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
11205:
11206: agebase=ageminpar;
11207: agelim=agemaxpar;
11208:
11209:
1.227 brouard 11210: i1=pow(2,cptcoveff);
1.218 brouard 11211: if (cptcovn < 1){i1=1;}
1.227 brouard 11212:
1.238 brouard 11213: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11214: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 11215: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 11216: continue;
11217: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
11218: fprintf(ficresplb,"#******");
11219: printf("#******");
11220: fprintf(ficlog,"#******");
11221: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
1.330 brouard 11222: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
11223: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
11224: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.238 brouard 11225: }
11226: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11227: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11228: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11229: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11230: }
11231: fprintf(ficresplb,"******\n");
11232: printf("******\n");
11233: fprintf(ficlog,"******\n");
11234: if(invalidvarcomb[k]){
11235: printf("\nCombination (%d) ignored because no cases \n",k);
11236: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
11237: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
11238: continue;
11239: }
1.218 brouard 11240:
1.238 brouard 11241: fprintf(ficresplb,"#Age ");
11242: for(j=1;j<=cptcoveff;j++) {
1.330 brouard 11243: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.238 brouard 11244: }
11245: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
11246: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 11247:
11248:
1.238 brouard 11249: for (age=agebase; age<=agelim; age++){
11250: /* for (age=agebase; age<=agebase; age++){ */
11251: if(mobilavproj > 0){
11252: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
11253: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11254: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 11255: }else if (mobilavproj == 0){
11256: 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);
11257: 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);
11258: exit(1);
11259: }else{
11260: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11261: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 11262: /* printf("TOTOT\n"); */
11263: /* exit(1); */
1.238 brouard 11264: }
11265: fprintf(ficresplb,"%.0f ",age );
11266: for(j=1;j<=cptcoveff;j++)
1.330 brouard 11267: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.238 brouard 11268: tot=0.;
11269: for(i=1; i<=nlstate;i++){
11270: tot += bprlim[i][i];
11271: fprintf(ficresplb," %.5f", bprlim[i][i]);
11272: }
11273: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
11274: } /* Age */
11275: /* was end of cptcod */
1.255 brouard 11276: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 11277: } /* end of any combination */
11278: } /* end of nres */
1.218 brouard 11279: /* hBijx(p, bage, fage); */
11280: /* fclose(ficrespijb); */
11281:
11282: return 0;
1.217 brouard 11283: }
1.218 brouard 11284:
1.180 brouard 11285: int hPijx(double *p, int bage, int fage){
11286: /*------------- h Pij x at various ages ------------*/
11287:
11288: int stepsize;
11289: int agelim;
11290: int hstepm;
11291: int nhstepm;
1.235 brouard 11292: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 11293:
11294: double agedeb;
11295: double ***p3mat;
11296:
1.201 brouard 11297: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 11298: if((ficrespij=fopen(filerespij,"w"))==NULL) {
11299: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
11300: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
11301: }
11302: printf("Computing pij: result on file '%s' \n", filerespij);
11303: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
11304:
11305: stepsize=(int) (stepm+YEARM-1)/YEARM;
11306: /*if (stepm<=24) stepsize=2;*/
11307:
11308: agelim=AGESUP;
11309: hstepm=stepsize*YEARM; /* Every year of age */
11310: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 11311:
1.180 brouard 11312: /* hstepm=1; aff par mois*/
11313: pstamp(ficrespij);
11314: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 11315: i1= pow(2,cptcoveff);
1.218 brouard 11316: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11317: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11318: /* k=k+1; */
1.235 brouard 11319: for(nres=1; nres <= nresult; nres++) /* For each resultline */
11320: for(k=1; k<=i1;k++){
1.253 brouard 11321: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 11322: continue;
1.183 brouard 11323: fprintf(ficrespij,"\n#****** ");
1.227 brouard 11324: for(j=1;j<=cptcoveff;j++)
1.330 brouard 11325: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.235 brouard 11326: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
11327: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11328: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11329: }
1.183 brouard 11330: fprintf(ficrespij,"******\n");
11331:
11332: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
11333: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
11334: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
11335:
11336: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 11337:
1.183 brouard 11338: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11339: oldm=oldms;savm=savms;
1.235 brouard 11340: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 11341: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
11342: for(i=1; i<=nlstate;i++)
11343: for(j=1; j<=nlstate+ndeath;j++)
11344: fprintf(ficrespij," %1d-%1d",i,j);
11345: fprintf(ficrespij,"\n");
11346: for (h=0; h<=nhstepm; h++){
11347: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11348: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 11349: for(i=1; i<=nlstate;i++)
11350: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 11351: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 11352: fprintf(ficrespij,"\n");
11353: }
1.183 brouard 11354: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11355: fprintf(ficrespij,"\n");
11356: }
1.180 brouard 11357: /*}*/
11358: }
1.218 brouard 11359: return 0;
1.180 brouard 11360: }
1.218 brouard 11361:
11362: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 11363: /*------------- h Bij x at various ages ------------*/
11364:
11365: int stepsize;
1.218 brouard 11366: /* int agelim; */
11367: int ageminl;
1.217 brouard 11368: int hstepm;
11369: int nhstepm;
1.238 brouard 11370: int h, i, i1, j, k, nres;
1.218 brouard 11371:
1.217 brouard 11372: double agedeb;
11373: double ***p3mat;
1.218 brouard 11374:
11375: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
11376: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
11377: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11378: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11379: }
11380: printf("Computing pij back: result on file '%s' \n", filerespijb);
11381: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
11382:
11383: stepsize=(int) (stepm+YEARM-1)/YEARM;
11384: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 11385:
1.218 brouard 11386: /* agelim=AGESUP; */
1.289 brouard 11387: ageminl=AGEINF; /* was 30 */
1.218 brouard 11388: hstepm=stepsize*YEARM; /* Every year of age */
11389: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
11390:
11391: /* hstepm=1; aff par mois*/
11392: pstamp(ficrespijb);
1.255 brouard 11393: 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 11394: i1= pow(2,cptcoveff);
1.218 brouard 11395: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11396: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11397: /* k=k+1; */
1.238 brouard 11398: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11399: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 11400: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 11401: continue;
11402: fprintf(ficrespijb,"\n#****** ");
11403: for(j=1;j<=cptcoveff;j++)
1.330 brouard 11404: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.238 brouard 11405: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11406: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11407: }
11408: fprintf(ficrespijb,"******\n");
1.264 brouard 11409: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 11410: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
11411: continue;
11412: }
11413:
11414: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
11415: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
11416: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
1.297 brouard 11417: 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 */
11418: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
1.238 brouard 11419:
11420: /* nhstepm=nhstepm*YEARM; aff par mois*/
11421:
1.266 brouard 11422: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
11423: /* and memory limitations if stepm is small */
11424:
1.238 brouard 11425: /* oldm=oldms;savm=savms; */
11426: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.325 brouard 11427: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
1.238 brouard 11428: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 11429: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 11430: for(i=1; i<=nlstate;i++)
11431: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 11432: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 11433: fprintf(ficrespijb,"\n");
1.238 brouard 11434: for (h=0; h<=nhstepm; h++){
11435: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11436: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
11437: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
11438: for(i=1; i<=nlstate;i++)
11439: for(j=1; j<=nlstate+ndeath;j++)
1.325 brouard 11440: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.238 brouard 11441: fprintf(ficrespijb,"\n");
11442: }
11443: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11444: fprintf(ficrespijb,"\n");
11445: } /* end age deb */
11446: } /* end combination */
11447: } /* end nres */
1.218 brouard 11448: return 0;
11449: } /* hBijx */
1.217 brouard 11450:
1.180 brouard 11451:
1.136 brouard 11452: /***********************************************/
11453: /**************** Main Program *****************/
11454: /***********************************************/
11455:
11456: int main(int argc, char *argv[])
11457: {
11458: #ifdef GSL
11459: const gsl_multimin_fminimizer_type *T;
11460: size_t iteri = 0, it;
11461: int rval = GSL_CONTINUE;
11462: int status = GSL_SUCCESS;
11463: double ssval;
11464: #endif
11465: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 11466: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
11467: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 11468: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 11469: int jj, ll, li, lj, lk;
1.136 brouard 11470: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 11471: int num_filled;
1.136 brouard 11472: int itimes;
11473: int NDIM=2;
11474: int vpopbased=0;
1.235 brouard 11475: int nres=0;
1.258 brouard 11476: int endishere=0;
1.277 brouard 11477: int noffset=0;
1.274 brouard 11478: int ncurrv=0; /* Temporary variable */
11479:
1.164 brouard 11480: char ca[32], cb[32];
1.136 brouard 11481: /* FILE *fichtm; *//* Html File */
11482: /* FILE *ficgp;*/ /*Gnuplot File */
11483: struct stat info;
1.191 brouard 11484: double agedeb=0.;
1.194 brouard 11485:
11486: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 11487: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 11488:
1.165 brouard 11489: double fret;
1.191 brouard 11490: double dum=0.; /* Dummy variable */
1.136 brouard 11491: double ***p3mat;
1.218 brouard 11492: /* double ***mobaverage; */
1.319 brouard 11493: double wald;
1.164 brouard 11494:
11495: char line[MAXLINE];
1.197 brouard 11496: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
11497:
1.234 brouard 11498: char modeltemp[MAXLINE];
1.230 brouard 11499: char resultline[MAXLINE];
11500:
1.136 brouard 11501: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 11502: char *tok, *val; /* pathtot */
1.290 brouard 11503: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs declared globally ;*/
1.195 brouard 11504: int c, h , cpt, c2;
1.191 brouard 11505: int jl=0;
11506: int i1, j1, jk, stepsize=0;
1.194 brouard 11507: int count=0;
11508:
1.164 brouard 11509: int *tab;
1.136 brouard 11510: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 11511: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
11512: /* double anprojf, mprojf, jprojf; */
11513: /* double jintmean,mintmean,aintmean; */
11514: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11515: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11516: double yrfproj= 10.0; /* Number of years of forward projections */
11517: double yrbproj= 10.0; /* Number of years of backward projections */
11518: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 11519: int mobilav=0,popforecast=0;
1.191 brouard 11520: int hstepm=0, nhstepm=0;
1.136 brouard 11521: int agemortsup;
11522: float sumlpop=0.;
11523: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
11524: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
11525:
1.191 brouard 11526: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 11527: double ftolpl=FTOL;
11528: double **prlim;
1.217 brouard 11529: double **bprlim;
1.317 brouard 11530: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
11531: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 11532: double ***paramstart; /* Matrix of starting parameter values */
11533: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 11534: double **matcov; /* Matrix of covariance */
1.203 brouard 11535: double **hess; /* Hessian matrix */
1.136 brouard 11536: double ***delti3; /* Scale */
11537: double *delti; /* Scale */
11538: double ***eij, ***vareij;
11539: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 11540:
1.136 brouard 11541: double *epj, vepp;
1.164 brouard 11542:
1.273 brouard 11543: double dateprev1, dateprev2;
1.296 brouard 11544: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
11545: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
11546:
1.217 brouard 11547:
1.136 brouard 11548: double **ximort;
1.145 brouard 11549: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 11550: int *dcwave;
11551:
1.164 brouard 11552: char z[1]="c";
1.136 brouard 11553:
11554: /*char *strt;*/
11555: char strtend[80];
1.126 brouard 11556:
1.164 brouard 11557:
1.126 brouard 11558: /* setlocale (LC_ALL, ""); */
11559: /* bindtextdomain (PACKAGE, LOCALEDIR); */
11560: /* textdomain (PACKAGE); */
11561: /* setlocale (LC_CTYPE, ""); */
11562: /* setlocale (LC_MESSAGES, ""); */
11563:
11564: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 11565: rstart_time = time(NULL);
11566: /* (void) gettimeofday(&start_time,&tzp);*/
11567: start_time = *localtime(&rstart_time);
1.126 brouard 11568: curr_time=start_time;
1.157 brouard 11569: /*tml = *localtime(&start_time.tm_sec);*/
11570: /* strcpy(strstart,asctime(&tml)); */
11571: strcpy(strstart,asctime(&start_time));
1.126 brouard 11572:
11573: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 11574: /* tp.tm_sec = tp.tm_sec +86400; */
11575: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 11576: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
11577: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
11578: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 11579: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 11580: /* strt=asctime(&tmg); */
11581: /* printf("Time(after) =%s",strstart); */
11582: /* (void) time (&time_value);
11583: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
11584: * tm = *localtime(&time_value);
11585: * strstart=asctime(&tm);
11586: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
11587: */
11588:
11589: nberr=0; /* Number of errors and warnings */
11590: nbwarn=0;
1.184 brouard 11591: #ifdef WIN32
11592: _getcwd(pathcd, size);
11593: #else
1.126 brouard 11594: getcwd(pathcd, size);
1.184 brouard 11595: #endif
1.191 brouard 11596: syscompilerinfo(0);
1.196 brouard 11597: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 11598: if(argc <=1){
11599: printf("\nEnter the parameter file name: ");
1.205 brouard 11600: if(!fgets(pathr,FILENAMELENGTH,stdin)){
11601: printf("ERROR Empty parameter file name\n");
11602: goto end;
11603: }
1.126 brouard 11604: i=strlen(pathr);
11605: if(pathr[i-1]=='\n')
11606: pathr[i-1]='\0';
1.156 brouard 11607: i=strlen(pathr);
1.205 brouard 11608: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 11609: pathr[i-1]='\0';
1.205 brouard 11610: }
11611: i=strlen(pathr);
11612: if( i==0 ){
11613: printf("ERROR Empty parameter file name\n");
11614: goto end;
11615: }
11616: for (tok = pathr; tok != NULL; ){
1.126 brouard 11617: printf("Pathr |%s|\n",pathr);
11618: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
11619: printf("val= |%s| pathr=%s\n",val,pathr);
11620: strcpy (pathtot, val);
11621: if(pathr[0] == '\0') break; /* Dirty */
11622: }
11623: }
1.281 brouard 11624: else if (argc<=2){
11625: strcpy(pathtot,argv[1]);
11626: }
1.126 brouard 11627: else{
11628: strcpy(pathtot,argv[1]);
1.281 brouard 11629: strcpy(z,argv[2]);
11630: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 11631: }
11632: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
11633: /*cygwin_split_path(pathtot,path,optionfile);
11634: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
11635: /* cutv(path,optionfile,pathtot,'\\');*/
11636:
11637: /* Split argv[0], imach program to get pathimach */
11638: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
11639: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11640: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11641: /* strcpy(pathimach,argv[0]); */
11642: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
11643: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
11644: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 11645: #ifdef WIN32
11646: _chdir(path); /* Can be a relative path */
11647: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
11648: #else
1.126 brouard 11649: chdir(path); /* Can be a relative path */
1.184 brouard 11650: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
11651: #endif
11652: printf("Current directory %s!\n",pathcd);
1.126 brouard 11653: strcpy(command,"mkdir ");
11654: strcat(command,optionfilefiname);
11655: if((outcmd=system(command)) != 0){
1.169 brouard 11656: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 11657: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
11658: /* fclose(ficlog); */
11659: /* exit(1); */
11660: }
11661: /* if((imk=mkdir(optionfilefiname))<0){ */
11662: /* perror("mkdir"); */
11663: /* } */
11664:
11665: /*-------- arguments in the command line --------*/
11666:
1.186 brouard 11667: /* Main Log file */
1.126 brouard 11668: strcat(filelog, optionfilefiname);
11669: strcat(filelog,".log"); /* */
11670: if((ficlog=fopen(filelog,"w"))==NULL) {
11671: printf("Problem with logfile %s\n",filelog);
11672: goto end;
11673: }
11674: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 11675: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 11676: fprintf(ficlog,"\nEnter the parameter file name: \n");
11677: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
11678: path=%s \n\
11679: optionfile=%s\n\
11680: optionfilext=%s\n\
1.156 brouard 11681: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 11682:
1.197 brouard 11683: syscompilerinfo(1);
1.167 brouard 11684:
1.126 brouard 11685: printf("Local time (at start):%s",strstart);
11686: fprintf(ficlog,"Local time (at start): %s",strstart);
11687: fflush(ficlog);
11688: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 11689: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 11690:
11691: /* */
11692: strcpy(fileres,"r");
11693: strcat(fileres, optionfilefiname);
1.201 brouard 11694: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 11695: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 11696: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 11697:
1.186 brouard 11698: /* Main ---------arguments file --------*/
1.126 brouard 11699:
11700: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 11701: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
11702: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 11703: fflush(ficlog);
1.149 brouard 11704: /* goto end; */
11705: exit(70);
1.126 brouard 11706: }
11707:
11708: strcpy(filereso,"o");
1.201 brouard 11709: strcat(filereso,fileresu);
1.126 brouard 11710: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
11711: printf("Problem with Output resultfile: %s\n", filereso);
11712: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
11713: fflush(ficlog);
11714: goto end;
11715: }
1.278 brouard 11716: /*-------- Rewriting parameter file ----------*/
11717: strcpy(rfileres,"r"); /* "Rparameterfile */
11718: strcat(rfileres,optionfilefiname); /* Parameter file first name */
11719: strcat(rfileres,"."); /* */
11720: strcat(rfileres,optionfilext); /* Other files have txt extension */
11721: if((ficres =fopen(rfileres,"w"))==NULL) {
11722: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
11723: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
11724: fflush(ficlog);
11725: goto end;
11726: }
11727: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 11728:
1.278 brouard 11729:
1.126 brouard 11730: /* Reads comments: lines beginning with '#' */
11731: numlinepar=0;
1.277 brouard 11732: /* Is it a BOM UTF-8 Windows file? */
11733: /* First parameter line */
1.197 brouard 11734: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 11735: noffset=0;
11736: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
11737: {
11738: noffset=noffset+3;
11739: printf("# File is an UTF8 Bom.\n"); // 0xBF
11740: }
1.302 brouard 11741: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
11742: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 11743: {
11744: noffset=noffset+2;
11745: printf("# File is an UTF16BE BOM file\n");
11746: }
11747: else if( line[0] == 0 && line[1] == 0)
11748: {
11749: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
11750: noffset=noffset+4;
11751: printf("# File is an UTF16BE BOM file\n");
11752: }
11753: } else{
11754: ;/*printf(" Not a BOM file\n");*/
11755: }
11756:
1.197 brouard 11757: /* If line starts with a # it is a comment */
1.277 brouard 11758: if (line[noffset] == '#') {
1.197 brouard 11759: numlinepar++;
11760: fputs(line,stdout);
11761: fputs(line,ficparo);
1.278 brouard 11762: fputs(line,ficres);
1.197 brouard 11763: fputs(line,ficlog);
11764: continue;
11765: }else
11766: break;
11767: }
11768: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11769: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11770: if (num_filled != 5) {
11771: printf("Should be 5 parameters\n");
1.283 brouard 11772: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11773: }
1.126 brouard 11774: numlinepar++;
1.197 brouard 11775: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11776: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11777: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11778: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11779: }
11780: /* Second parameter line */
11781: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11782: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11783: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11784: if (line[0] == '#') {
11785: numlinepar++;
1.283 brouard 11786: printf("%s",line);
11787: fprintf(ficres,"%s",line);
11788: fprintf(ficparo,"%s",line);
11789: fprintf(ficlog,"%s",line);
1.197 brouard 11790: continue;
11791: }else
11792: break;
11793: }
1.223 brouard 11794: 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", \
11795: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11796: if (num_filled != 11) {
11797: 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 11798: printf("but line=%s\n",line);
1.283 brouard 11799: 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");
11800: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11801: }
1.286 brouard 11802: if( lastpass > maxwav){
11803: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11804: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11805: fflush(ficlog);
11806: goto end;
11807: }
11808: 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 11809: 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 11810: 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 11811: 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 11812: }
1.203 brouard 11813: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11814: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11815: /* Third parameter line */
11816: while(fgets(line, MAXLINE, ficpar)) {
11817: /* If line starts with a # it is a comment */
11818: if (line[0] == '#') {
11819: numlinepar++;
1.283 brouard 11820: printf("%s",line);
11821: fprintf(ficres,"%s",line);
11822: fprintf(ficparo,"%s",line);
11823: fprintf(ficlog,"%s",line);
1.197 brouard 11824: continue;
11825: }else
11826: break;
11827: }
1.201 brouard 11828: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11829: if (num_filled != 1){
1.302 brouard 11830: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
11831: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 11832: model[0]='\0';
11833: goto end;
11834: }
11835: else{
11836: if (model[0]=='+'){
11837: for(i=1; i<=strlen(model);i++)
11838: modeltemp[i-1]=model[i];
1.201 brouard 11839: strcpy(model,modeltemp);
1.197 brouard 11840: }
11841: }
1.199 brouard 11842: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11843: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11844: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11845: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11846: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11847: }
11848: /* 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); */
11849: /* numlinepar=numlinepar+3; /\* In general *\/ */
11850: /* 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 11851: /* 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); */
11852: /* 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 11853: fflush(ficlog);
1.190 brouard 11854: /* if(model[0]=='#'|| model[0]== '\0'){ */
11855: if(model[0]=='#'){
1.279 brouard 11856: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11857: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11858: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11859: if(mle != -1){
1.279 brouard 11860: 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 11861: exit(1);
11862: }
11863: }
1.126 brouard 11864: while((c=getc(ficpar))=='#' && c!= EOF){
11865: ungetc(c,ficpar);
11866: fgets(line, MAXLINE, ficpar);
11867: numlinepar++;
1.195 brouard 11868: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11869: z[0]=line[1];
11870: }
11871: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11872: fputs(line, stdout);
11873: //puts(line);
1.126 brouard 11874: fputs(line,ficparo);
11875: fputs(line,ficlog);
11876: }
11877: ungetc(c,ficpar);
11878:
11879:
1.290 brouard 11880: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
11881: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
11882: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
11883: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11884: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11885: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11886: v1+v2*age+v2*v3 makes cptcovn = 3
11887: */
11888: if (strlen(model)>1)
1.187 brouard 11889: 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 11890: else
1.187 brouard 11891: ncovmodel=2; /* Constant and age */
1.133 brouard 11892: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11893: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11894: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11895: 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);
11896: 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);
11897: fflush(stdout);
11898: fclose (ficlog);
11899: goto end;
11900: }
1.126 brouard 11901: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11902: delti=delti3[1][1];
11903: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11904: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11905: /* We could also provide initial parameters values giving by simple logistic regression
11906: * only one way, that is without matrix product. We will have nlstate maximizations */
11907: /* for(i=1;i<nlstate;i++){ */
11908: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11909: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11910: /* } */
1.126 brouard 11911: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11912: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11913: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11914: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11915: fclose (ficparo);
11916: fclose (ficlog);
11917: goto end;
11918: exit(0);
1.220 brouard 11919: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11920: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11921: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11922: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11923: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11924: matcov=matrix(1,npar,1,npar);
1.203 brouard 11925: hess=matrix(1,npar,1,npar);
1.220 brouard 11926: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11927: /* Read guessed parameters */
1.126 brouard 11928: /* Reads comments: lines beginning with '#' */
11929: while((c=getc(ficpar))=='#' && c!= EOF){
11930: ungetc(c,ficpar);
11931: fgets(line, MAXLINE, ficpar);
11932: numlinepar++;
1.141 brouard 11933: fputs(line,stdout);
1.126 brouard 11934: fputs(line,ficparo);
11935: fputs(line,ficlog);
11936: }
11937: ungetc(c,ficpar);
11938:
11939: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11940: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11941: for(i=1; i <=nlstate; i++){
1.234 brouard 11942: j=0;
1.126 brouard 11943: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11944: if(jj==i) continue;
11945: j++;
1.292 brouard 11946: while((c=getc(ficpar))=='#' && c!= EOF){
11947: ungetc(c,ficpar);
11948: fgets(line, MAXLINE, ficpar);
11949: numlinepar++;
11950: fputs(line,stdout);
11951: fputs(line,ficparo);
11952: fputs(line,ficlog);
11953: }
11954: ungetc(c,ficpar);
1.234 brouard 11955: fscanf(ficpar,"%1d%1d",&i1,&j1);
11956: if ((i1 != i) || (j1 != jj)){
11957: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11958: It might be a problem of design; if ncovcol and the model are correct\n \
11959: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11960: exit(1);
11961: }
11962: fprintf(ficparo,"%1d%1d",i1,j1);
11963: if(mle==1)
11964: printf("%1d%1d",i,jj);
11965: fprintf(ficlog,"%1d%1d",i,jj);
11966: for(k=1; k<=ncovmodel;k++){
11967: fscanf(ficpar," %lf",¶m[i][j][k]);
11968: if(mle==1){
11969: printf(" %lf",param[i][j][k]);
11970: fprintf(ficlog," %lf",param[i][j][k]);
11971: }
11972: else
11973: fprintf(ficlog," %lf",param[i][j][k]);
11974: fprintf(ficparo," %lf",param[i][j][k]);
11975: }
11976: fscanf(ficpar,"\n");
11977: numlinepar++;
11978: if(mle==1)
11979: printf("\n");
11980: fprintf(ficlog,"\n");
11981: fprintf(ficparo,"\n");
1.126 brouard 11982: }
11983: }
11984: fflush(ficlog);
1.234 brouard 11985:
1.251 brouard 11986: /* Reads parameters values */
1.126 brouard 11987: p=param[1][1];
1.251 brouard 11988: pstart=paramstart[1][1];
1.126 brouard 11989:
11990: /* Reads comments: lines beginning with '#' */
11991: while((c=getc(ficpar))=='#' && c!= EOF){
11992: ungetc(c,ficpar);
11993: fgets(line, MAXLINE, ficpar);
11994: numlinepar++;
1.141 brouard 11995: fputs(line,stdout);
1.126 brouard 11996: fputs(line,ficparo);
11997: fputs(line,ficlog);
11998: }
11999: ungetc(c,ficpar);
12000:
12001: for(i=1; i <=nlstate; i++){
12002: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 12003: fscanf(ficpar,"%1d%1d",&i1,&j1);
12004: if ( (i1-i) * (j1-j) != 0){
12005: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
12006: exit(1);
12007: }
12008: printf("%1d%1d",i,j);
12009: fprintf(ficparo,"%1d%1d",i1,j1);
12010: fprintf(ficlog,"%1d%1d",i1,j1);
12011: for(k=1; k<=ncovmodel;k++){
12012: fscanf(ficpar,"%le",&delti3[i][j][k]);
12013: printf(" %le",delti3[i][j][k]);
12014: fprintf(ficparo," %le",delti3[i][j][k]);
12015: fprintf(ficlog," %le",delti3[i][j][k]);
12016: }
12017: fscanf(ficpar,"\n");
12018: numlinepar++;
12019: printf("\n");
12020: fprintf(ficparo,"\n");
12021: fprintf(ficlog,"\n");
1.126 brouard 12022: }
12023: }
12024: fflush(ficlog);
1.234 brouard 12025:
1.145 brouard 12026: /* Reads covariance matrix */
1.126 brouard 12027: delti=delti3[1][1];
1.220 brouard 12028:
12029:
1.126 brouard 12030: /* 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 12031:
1.126 brouard 12032: /* Reads comments: lines beginning with '#' */
12033: while((c=getc(ficpar))=='#' && c!= EOF){
12034: ungetc(c,ficpar);
12035: fgets(line, MAXLINE, ficpar);
12036: numlinepar++;
1.141 brouard 12037: fputs(line,stdout);
1.126 brouard 12038: fputs(line,ficparo);
12039: fputs(line,ficlog);
12040: }
12041: ungetc(c,ficpar);
1.220 brouard 12042:
1.126 brouard 12043: matcov=matrix(1,npar,1,npar);
1.203 brouard 12044: hess=matrix(1,npar,1,npar);
1.131 brouard 12045: for(i=1; i <=npar; i++)
12046: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 12047:
1.194 brouard 12048: /* Scans npar lines */
1.126 brouard 12049: for(i=1; i <=npar; i++){
1.226 brouard 12050: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 12051: if(count != 3){
1.226 brouard 12052: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12053: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12054: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12055: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 12056: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
12057: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 12058: exit(1);
1.220 brouard 12059: }else{
1.226 brouard 12060: if(mle==1)
12061: printf("%1d%1d%d",i1,j1,jk);
12062: }
12063: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
12064: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 12065: for(j=1; j <=i; j++){
1.226 brouard 12066: fscanf(ficpar," %le",&matcov[i][j]);
12067: if(mle==1){
12068: printf(" %.5le",matcov[i][j]);
12069: }
12070: fprintf(ficlog," %.5le",matcov[i][j]);
12071: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 12072: }
12073: fscanf(ficpar,"\n");
12074: numlinepar++;
12075: if(mle==1)
1.220 brouard 12076: printf("\n");
1.126 brouard 12077: fprintf(ficlog,"\n");
12078: fprintf(ficparo,"\n");
12079: }
1.194 brouard 12080: /* End of read covariance matrix npar lines */
1.126 brouard 12081: for(i=1; i <=npar; i++)
12082: for(j=i+1;j<=npar;j++)
1.226 brouard 12083: matcov[i][j]=matcov[j][i];
1.126 brouard 12084:
12085: if(mle==1)
12086: printf("\n");
12087: fprintf(ficlog,"\n");
12088:
12089: fflush(ficlog);
12090:
12091: } /* End of mle != -3 */
1.218 brouard 12092:
1.186 brouard 12093: /* Main data
12094: */
1.290 brouard 12095: nobs=lastobs-firstobs+1; /* was = lastobs;*/
12096: /* num=lvector(1,n); */
12097: /* moisnais=vector(1,n); */
12098: /* annais=vector(1,n); */
12099: /* moisdc=vector(1,n); */
12100: /* andc=vector(1,n); */
12101: /* weight=vector(1,n); */
12102: /* agedc=vector(1,n); */
12103: /* cod=ivector(1,n); */
12104: /* for(i=1;i<=n;i++){ */
12105: num=lvector(firstobs,lastobs);
12106: moisnais=vector(firstobs,lastobs);
12107: annais=vector(firstobs,lastobs);
12108: moisdc=vector(firstobs,lastobs);
12109: andc=vector(firstobs,lastobs);
12110: weight=vector(firstobs,lastobs);
12111: agedc=vector(firstobs,lastobs);
12112: cod=ivector(firstobs,lastobs);
12113: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 12114: num[i]=0;
12115: moisnais[i]=0;
12116: annais[i]=0;
12117: moisdc[i]=0;
12118: andc[i]=0;
12119: agedc[i]=0;
12120: cod[i]=0;
12121: weight[i]=1.0; /* Equal weights, 1 by default */
12122: }
1.290 brouard 12123: mint=matrix(1,maxwav,firstobs,lastobs);
12124: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 12125: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
12126: printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel));
1.126 brouard 12127: tab=ivector(1,NCOVMAX);
1.144 brouard 12128: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 12129: 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 12130:
1.136 brouard 12131: /* Reads data from file datafile */
12132: if (readdata(datafile, firstobs, lastobs, &imx)==1)
12133: goto end;
12134:
12135: /* Calculation of the number of parameters from char model */
1.234 brouard 12136: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 12137: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
12138: k=3 V4 Tvar[k=3]= 4 (from V4)
12139: k=2 V1 Tvar[k=2]= 1 (from V1)
12140: k=1 Tvar[1]=2 (from V2)
1.234 brouard 12141: */
12142:
12143: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
12144: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 12145: TnsdVar=ivector(1,NCOVMAX); /* */
1.234 brouard 12146: TvarsD=ivector(1,NCOVMAX); /* */
12147: TvarsQind=ivector(1,NCOVMAX); /* */
12148: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 12149: TvarF=ivector(1,NCOVMAX); /* */
12150: TvarFind=ivector(1,NCOVMAX); /* */
12151: TvarV=ivector(1,NCOVMAX); /* */
12152: TvarVind=ivector(1,NCOVMAX); /* */
12153: TvarA=ivector(1,NCOVMAX); /* */
12154: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 12155: TvarFD=ivector(1,NCOVMAX); /* */
12156: TvarFDind=ivector(1,NCOVMAX); /* */
12157: TvarFQ=ivector(1,NCOVMAX); /* */
12158: TvarFQind=ivector(1,NCOVMAX); /* */
12159: TvarVD=ivector(1,NCOVMAX); /* */
12160: TvarVDind=ivector(1,NCOVMAX); /* */
12161: TvarVQ=ivector(1,NCOVMAX); /* */
12162: TvarVQind=ivector(1,NCOVMAX); /* */
12163:
1.230 brouard 12164: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 12165: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 12166: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
12167: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
12168: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 12169: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
12170: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
12171: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
12172: */
12173: /* For model-covariate k tells which data-covariate to use but
12174: because this model-covariate is a construction we invent a new column
12175: ncovcol + k1
12176: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
12177: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 12178: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
12179: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 12180: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
12181: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 12182: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 12183: */
1.145 brouard 12184: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
12185: 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 12186: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
12187: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.330 brouard 12188: Tvardk=imatrix(1,NCOVMAX,1,2);
1.145 brouard 12189: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 12190: 4 covariates (3 plus signs)
12191: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 12192: */
12193: for(i=1;i<NCOVMAX;i++)
12194: Tage[i]=0;
1.230 brouard 12195: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 12196: * individual dummy, fixed or varying:
12197: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
12198: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 12199: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
12200: * V1 df, V2 qf, V3 & V4 dv, V5 qv
12201: * Tmodelind[1]@9={9,0,3,2,}*/
12202: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
12203: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 12204: * individual quantitative, fixed or varying:
12205: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
12206: * 3, 1, 0, 0, 0, 0, 0, 0},
12207: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 12208: /* Main decodemodel */
12209:
1.187 brouard 12210:
1.223 brouard 12211: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 12212: goto end;
12213:
1.137 brouard 12214: if((double)(lastobs-imx)/(double)imx > 1.10){
12215: nbwarn++;
12216: 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);
12217: 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);
12218: }
1.136 brouard 12219: /* if(mle==1){*/
1.137 brouard 12220: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
12221: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 12222: }
12223:
12224: /*-calculation of age at interview from date of interview and age at death -*/
12225: agev=matrix(1,maxwav,1,imx);
12226:
12227: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
12228: goto end;
12229:
1.126 brouard 12230:
1.136 brouard 12231: agegomp=(int)agemin;
1.290 brouard 12232: free_vector(moisnais,firstobs,lastobs);
12233: free_vector(annais,firstobs,lastobs);
1.126 brouard 12234: /* free_matrix(mint,1,maxwav,1,n);
12235: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 12236: /* free_vector(moisdc,1,n); */
12237: /* free_vector(andc,1,n); */
1.145 brouard 12238: /* */
12239:
1.126 brouard 12240: wav=ivector(1,imx);
1.214 brouard 12241: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
12242: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
12243: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
12244: 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.*/
12245: bh=imatrix(1,lastpass-firstpass+2,1,imx);
12246: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 12247:
12248: /* Concatenates waves */
1.214 brouard 12249: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
12250: Death is a valid wave (if date is known).
12251: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
12252: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
12253: and mw[mi+1][i]. dh depends on stepm.
12254: */
12255:
1.126 brouard 12256: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 12257: /* Concatenates waves */
1.145 brouard 12258:
1.290 brouard 12259: free_vector(moisdc,firstobs,lastobs);
12260: free_vector(andc,firstobs,lastobs);
1.215 brouard 12261:
1.126 brouard 12262: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
12263: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
12264: ncodemax[1]=1;
1.145 brouard 12265: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 12266: cptcoveff=0;
1.220 brouard 12267: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
12268: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 12269: }
12270:
12271: ncovcombmax=pow(2,cptcoveff);
12272: invalidvarcomb=ivector(1, ncovcombmax);
12273: for(i=1;i<ncovcombmax;i++)
12274: invalidvarcomb[i]=0;
12275:
1.211 brouard 12276: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 12277: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 12278: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 12279:
1.200 brouard 12280: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 12281: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 12282: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 12283: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
12284: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
12285: * (currently 0 or 1) in the data.
12286: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
12287: * corresponding modality (h,j).
12288: */
12289:
1.145 brouard 12290: h=0;
12291: /*if (cptcovn > 0) */
1.126 brouard 12292: m=pow(2,cptcoveff);
12293:
1.144 brouard 12294: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 12295: * For k=4 covariates, h goes from 1 to m=2**k
12296: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
12297: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 12298: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
12299: *______________________________ *______________________
12300: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
12301: * 2 2 1 1 1 * 1 0 0 0 1
12302: * 3 i=2 1 2 1 1 * 2 0 0 1 0
12303: * 4 2 2 1 1 * 3 0 0 1 1
12304: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
12305: * 6 2 1 2 1 * 5 0 1 0 1
12306: * 7 i=4 1 2 2 1 * 6 0 1 1 0
12307: * 8 2 2 2 1 * 7 0 1 1 1
12308: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
12309: * 10 2 1 1 2 * 9 1 0 0 1
12310: * 11 i=6 1 2 1 2 * 10 1 0 1 0
12311: * 12 2 2 1 2 * 11 1 0 1 1
12312: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
12313: * 14 2 1 2 2 * 13 1 1 0 1
12314: * 15 i=8 1 2 2 2 * 14 1 1 1 0
12315: * 16 2 2 2 2 * 15 1 1 1 1
12316: */
1.212 brouard 12317: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 12318: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
12319: * and the value of each covariate?
12320: * V1=1, V2=1, V3=2, V4=1 ?
12321: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
12322: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
12323: * In order to get the real value in the data, we use nbcode
12324: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
12325: * We are keeping this crazy system in order to be able (in the future?)
12326: * to have more than 2 values (0 or 1) for a covariate.
12327: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
12328: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
12329: * bbbbbbbb
12330: * 76543210
12331: * h-1 00000101 (6-1=5)
1.219 brouard 12332: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 12333: * &
12334: * 1 00000001 (1)
1.219 brouard 12335: * 00000000 = 1 & ((h-1) >> (k-1))
12336: * +1= 00000001 =1
1.211 brouard 12337: *
12338: * h=14, k=3 => h'=h-1=13, k'=k-1=2
12339: * h' 1101 =2^3+2^2+0x2^1+2^0
12340: * >>k' 11
12341: * & 00000001
12342: * = 00000001
12343: * +1 = 00000010=2 = codtabm(14,3)
12344: * Reverse h=6 and m=16?
12345: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
12346: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
12347: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
12348: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
12349: * V3=decodtabm(14,3,2**4)=2
12350: * h'=13 1101 =2^3+2^2+0x2^1+2^0
12351: *(h-1) >> (j-1) 0011 =13 >> 2
12352: * &1 000000001
12353: * = 000000001
12354: * +1= 000000010 =2
12355: * 2211
12356: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
12357: * V3=2
1.220 brouard 12358: * codtabm and decodtabm are identical
1.211 brouard 12359: */
12360:
1.145 brouard 12361:
12362: free_ivector(Ndum,-1,NCOVMAX);
12363:
12364:
1.126 brouard 12365:
1.186 brouard 12366: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 12367: strcpy(optionfilegnuplot,optionfilefiname);
12368: if(mle==-3)
1.201 brouard 12369: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 12370: strcat(optionfilegnuplot,".gp");
12371:
12372: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
12373: printf("Problem with file %s",optionfilegnuplot);
12374: }
12375: else{
1.204 brouard 12376: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 12377: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 12378: //fprintf(ficgp,"set missing 'NaNq'\n");
12379: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 12380: }
12381: /* fclose(ficgp);*/
1.186 brouard 12382:
12383:
12384: /* Initialisation of --------- index.htm --------*/
1.126 brouard 12385:
12386: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
12387: if(mle==-3)
1.201 brouard 12388: strcat(optionfilehtm,"-MORT_");
1.126 brouard 12389: strcat(optionfilehtm,".htm");
12390: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 12391: printf("Problem with %s \n",optionfilehtm);
12392: exit(0);
1.126 brouard 12393: }
12394:
12395: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
12396: strcat(optionfilehtmcov,"-cov.htm");
12397: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
12398: printf("Problem with %s \n",optionfilehtmcov), exit(0);
12399: }
12400: else{
12401: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
12402: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12403: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 12404: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
12405: }
12406:
1.324 brouard 12407: 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-2013-2016-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 12408: <hr size=\"2\" color=\"#EC5E5E\"> \n\
12409: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 12410: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12411: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 12412: \n\
12413: <hr size=\"2\" color=\"#EC5E5E\">\
12414: <ul><li><h4>Parameter files</h4>\n\
12415: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
12416: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
12417: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
12418: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
12419: - Date and time at start: %s</ul>\n",\
12420: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
12421: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
12422: fileres,fileres,\
12423: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
12424: fflush(fichtm);
12425:
12426: strcpy(pathr,path);
12427: strcat(pathr,optionfilefiname);
1.184 brouard 12428: #ifdef WIN32
12429: _chdir(optionfilefiname); /* Move to directory named optionfile */
12430: #else
1.126 brouard 12431: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 12432: #endif
12433:
1.126 brouard 12434:
1.220 brouard 12435: /* Calculates basic frequencies. Computes observed prevalence at single age
12436: and for any valid combination of covariates
1.126 brouard 12437: and prints on file fileres'p'. */
1.251 brouard 12438: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 12439: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 12440:
12441: fprintf(fichtm,"\n");
1.286 brouard 12442: 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 12443: ftol, stepm);
12444: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
12445: ncurrv=1;
12446: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
12447: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
12448: ncurrv=i;
12449: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12450: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 12451: ncurrv=i;
12452: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12453: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 12454: ncurrv=i;
12455: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
12456: 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", \
12457: nlstate, ndeath, maxwav, mle, weightopt);
12458:
12459: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
12460: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
12461:
12462:
1.317 brouard 12463: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 12464: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
12465: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 12466: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 12467: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 12468: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12469: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12470: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12471: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 12472:
1.126 brouard 12473: /* For Powell, parameters are in a vector p[] starting at p[1]
12474: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
12475: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
12476:
12477: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 12478: /* For mortality only */
1.126 brouard 12479: if (mle==-3){
1.136 brouard 12480: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 12481: for(i=1;i<=NDIM;i++)
12482: for(j=1;j<=NDIM;j++)
12483: ximort[i][j]=0.;
1.186 brouard 12484: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 12485: cens=ivector(firstobs,lastobs);
12486: ageexmed=vector(firstobs,lastobs);
12487: agecens=vector(firstobs,lastobs);
12488: dcwave=ivector(firstobs,lastobs);
1.223 brouard 12489:
1.126 brouard 12490: for (i=1; i<=imx; i++){
12491: dcwave[i]=-1;
12492: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 12493: if (s[m][i]>nlstate) {
12494: dcwave[i]=m;
12495: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
12496: break;
12497: }
1.126 brouard 12498: }
1.226 brouard 12499:
1.126 brouard 12500: for (i=1; i<=imx; i++) {
12501: if (wav[i]>0){
1.226 brouard 12502: ageexmed[i]=agev[mw[1][i]][i];
12503: j=wav[i];
12504: agecens[i]=1.;
12505:
12506: if (ageexmed[i]> 1 && wav[i] > 0){
12507: agecens[i]=agev[mw[j][i]][i];
12508: cens[i]= 1;
12509: }else if (ageexmed[i]< 1)
12510: cens[i]= -1;
12511: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
12512: cens[i]=0 ;
1.126 brouard 12513: }
12514: else cens[i]=-1;
12515: }
12516:
12517: for (i=1;i<=NDIM;i++) {
12518: for (j=1;j<=NDIM;j++)
1.226 brouard 12519: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 12520: }
12521:
1.302 brouard 12522: p[1]=0.0268; p[NDIM]=0.083;
12523: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 12524:
12525:
1.136 brouard 12526: #ifdef GSL
12527: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 12528: #else
1.126 brouard 12529: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 12530: #endif
1.201 brouard 12531: strcpy(filerespow,"POW-MORT_");
12532: strcat(filerespow,fileresu);
1.126 brouard 12533: if((ficrespow=fopen(filerespow,"w"))==NULL) {
12534: printf("Problem with resultfile: %s\n", filerespow);
12535: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
12536: }
1.136 brouard 12537: #ifdef GSL
12538: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 12539: #else
1.126 brouard 12540: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 12541: #endif
1.126 brouard 12542: /* for (i=1;i<=nlstate;i++)
12543: for(j=1;j<=nlstate+ndeath;j++)
12544: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
12545: */
12546: fprintf(ficrespow,"\n");
1.136 brouard 12547: #ifdef GSL
12548: /* gsl starts here */
12549: T = gsl_multimin_fminimizer_nmsimplex;
12550: gsl_multimin_fminimizer *sfm = NULL;
12551: gsl_vector *ss, *x;
12552: gsl_multimin_function minex_func;
12553:
12554: /* Initial vertex size vector */
12555: ss = gsl_vector_alloc (NDIM);
12556:
12557: if (ss == NULL){
12558: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
12559: }
12560: /* Set all step sizes to 1 */
12561: gsl_vector_set_all (ss, 0.001);
12562:
12563: /* Starting point */
1.126 brouard 12564:
1.136 brouard 12565: x = gsl_vector_alloc (NDIM);
12566:
12567: if (x == NULL){
12568: gsl_vector_free(ss);
12569: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
12570: }
12571:
12572: /* Initialize method and iterate */
12573: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 12574: /* gsl_vector_set(x, 0, 0.0268); */
12575: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 12576: gsl_vector_set(x, 0, p[1]);
12577: gsl_vector_set(x, 1, p[2]);
12578:
12579: minex_func.f = &gompertz_f;
12580: minex_func.n = NDIM;
12581: minex_func.params = (void *)&p; /* ??? */
12582:
12583: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
12584: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
12585:
12586: printf("Iterations beginning .....\n\n");
12587: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
12588:
12589: iteri=0;
12590: while (rval == GSL_CONTINUE){
12591: iteri++;
12592: status = gsl_multimin_fminimizer_iterate(sfm);
12593:
12594: if (status) printf("error: %s\n", gsl_strerror (status));
12595: fflush(0);
12596:
12597: if (status)
12598: break;
12599:
12600: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
12601: ssval = gsl_multimin_fminimizer_size (sfm);
12602:
12603: if (rval == GSL_SUCCESS)
12604: printf ("converged to a local maximum at\n");
12605:
12606: printf("%5d ", iteri);
12607: for (it = 0; it < NDIM; it++){
12608: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
12609: }
12610: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
12611: }
12612:
12613: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
12614:
12615: gsl_vector_free(x); /* initial values */
12616: gsl_vector_free(ss); /* inital step size */
12617: for (it=0; it<NDIM; it++){
12618: p[it+1]=gsl_vector_get(sfm->x,it);
12619: fprintf(ficrespow," %.12lf", p[it]);
12620: }
12621: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
12622: #endif
12623: #ifdef POWELL
12624: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
12625: #endif
1.126 brouard 12626: fclose(ficrespow);
12627:
1.203 brouard 12628: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 12629:
12630: for(i=1; i <=NDIM; i++)
12631: for(j=i+1;j<=NDIM;j++)
1.220 brouard 12632: matcov[i][j]=matcov[j][i];
1.126 brouard 12633:
12634: printf("\nCovariance matrix\n ");
1.203 brouard 12635: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 12636: for(i=1; i <=NDIM; i++) {
12637: for(j=1;j<=NDIM;j++){
1.220 brouard 12638: printf("%f ",matcov[i][j]);
12639: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 12640: }
1.203 brouard 12641: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 12642: }
12643:
12644: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 12645: for (i=1;i<=NDIM;i++) {
1.126 brouard 12646: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 12647: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
12648: }
1.302 brouard 12649: lsurv=vector(agegomp,AGESUP);
12650: lpop=vector(agegomp,AGESUP);
12651: tpop=vector(agegomp,AGESUP);
1.126 brouard 12652: lsurv[agegomp]=100000;
12653:
12654: for (k=agegomp;k<=AGESUP;k++) {
12655: agemortsup=k;
12656: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
12657: }
12658:
12659: for (k=agegomp;k<agemortsup;k++)
12660: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
12661:
12662: for (k=agegomp;k<agemortsup;k++){
12663: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
12664: sumlpop=sumlpop+lpop[k];
12665: }
12666:
12667: tpop[agegomp]=sumlpop;
12668: for (k=agegomp;k<(agemortsup-3);k++){
12669: /* tpop[k+1]=2;*/
12670: tpop[k+1]=tpop[k]-lpop[k];
12671: }
12672:
12673:
12674: printf("\nAge lx qx dx Lx Tx e(x)\n");
12675: for (k=agegomp;k<(agemortsup-2);k++)
12676: 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]);
12677:
12678:
12679: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 12680: ageminpar=50;
12681: agemaxpar=100;
1.194 brouard 12682: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
12683: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12684: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12685: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
12686: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12687: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12688: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12689: }else{
12690: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
12691: 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 12692: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 12693: }
1.201 brouard 12694: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 12695: stepm, weightopt,\
12696: model,imx,p,matcov,agemortsup);
12697:
1.302 brouard 12698: free_vector(lsurv,agegomp,AGESUP);
12699: free_vector(lpop,agegomp,AGESUP);
12700: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 12701: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 12702: free_ivector(dcwave,firstobs,lastobs);
12703: free_vector(agecens,firstobs,lastobs);
12704: free_vector(ageexmed,firstobs,lastobs);
12705: free_ivector(cens,firstobs,lastobs);
1.220 brouard 12706: #ifdef GSL
1.136 brouard 12707: #endif
1.186 brouard 12708: } /* Endof if mle==-3 mortality only */
1.205 brouard 12709: /* Standard */
12710: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
12711: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12712: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 12713: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 12714: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12715: for (k=1; k<=npar;k++)
12716: printf(" %d %8.5f",k,p[k]);
12717: printf("\n");
1.205 brouard 12718: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
12719: /* mlikeli uses func not funcone */
1.247 brouard 12720: /* for(i=1;i<nlstate;i++){ */
12721: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12722: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12723: /* } */
1.205 brouard 12724: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
12725: }
12726: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
12727: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12728: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
12729: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12730: }
12731: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 12732: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12733: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12734: for (k=1; k<=npar;k++)
12735: printf(" %d %8.5f",k,p[k]);
12736: printf("\n");
12737:
12738: /*--------- results files --------------*/
1.283 brouard 12739: /* 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 12740:
12741:
12742: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 12743: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 12744: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 12745:
12746: printf("#model= 1 + age ");
12747: fprintf(ficres,"#model= 1 + age ");
12748: fprintf(ficlog,"#model= 1 + age ");
12749: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
12750: </ul>", model);
12751:
12752: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
12753: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
12754: if(nagesqr==1){
12755: printf(" + age*age ");
12756: fprintf(ficres," + age*age ");
12757: fprintf(ficlog," + age*age ");
12758: fprintf(fichtm, "<th>+ age*age</th>");
12759: }
12760: for(j=1;j <=ncovmodel-2;j++){
12761: if(Typevar[j]==0) {
12762: printf(" + V%d ",Tvar[j]);
12763: fprintf(ficres," + V%d ",Tvar[j]);
12764: fprintf(ficlog," + V%d ",Tvar[j]);
12765: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
12766: }else if(Typevar[j]==1) {
12767: printf(" + V%d*age ",Tvar[j]);
12768: fprintf(ficres," + V%d*age ",Tvar[j]);
12769: fprintf(ficlog," + V%d*age ",Tvar[j]);
12770: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
12771: }else if(Typevar[j]==2) {
12772: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12773: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12774: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12775: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12776: }
12777: }
12778: printf("\n");
12779: fprintf(ficres,"\n");
12780: fprintf(ficlog,"\n");
12781: fprintf(fichtm, "</tr>");
12782: fprintf(fichtm, "\n");
12783:
12784:
1.126 brouard 12785: for(i=1,jk=1; i <=nlstate; i++){
12786: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 12787: if (k != i) {
1.319 brouard 12788: fprintf(fichtm, "<tr>");
1.225 brouard 12789: printf("%d%d ",i,k);
12790: fprintf(ficlog,"%d%d ",i,k);
12791: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 12792: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 12793: for(j=1; j <=ncovmodel; j++){
12794: printf("%12.7f ",p[jk]);
12795: fprintf(ficlog,"%12.7f ",p[jk]);
12796: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 12797: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 12798: jk++;
12799: }
12800: printf("\n");
12801: fprintf(ficlog,"\n");
12802: fprintf(ficres,"\n");
1.319 brouard 12803: fprintf(fichtm, "</tr>\n");
1.225 brouard 12804: }
1.126 brouard 12805: }
12806: }
1.319 brouard 12807: /* fprintf(fichtm,"</tr>\n"); */
12808: fprintf(fichtm,"</table>\n");
12809: fprintf(fichtm, "\n");
12810:
1.203 brouard 12811: if(mle != 0){
12812: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 12813: ftolhess=ftol; /* Usually correct */
1.203 brouard 12814: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
12815: 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");
12816: 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 12817: 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 12818: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
12819: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
12820: if(nagesqr==1){
12821: printf(" + age*age ");
12822: fprintf(ficres," + age*age ");
12823: fprintf(ficlog," + age*age ");
12824: fprintf(fichtm, "<th>+ age*age</th>");
12825: }
12826: for(j=1;j <=ncovmodel-2;j++){
12827: if(Typevar[j]==0) {
12828: printf(" + V%d ",Tvar[j]);
12829: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
12830: }else if(Typevar[j]==1) {
12831: printf(" + V%d*age ",Tvar[j]);
12832: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
12833: }else if(Typevar[j]==2) {
12834: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12835: }
12836: }
12837: fprintf(fichtm, "</tr>\n");
12838:
1.203 brouard 12839: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 12840: for(k=1; k <=(nlstate+ndeath); k++){
12841: if (k != i) {
1.319 brouard 12842: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 12843: printf("%d%d ",i,k);
12844: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 12845: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 12846: for(j=1; j <=ncovmodel; j++){
1.319 brouard 12847: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 12848: 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]));
12849: 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 12850: if(fabs(wald) > 1.96){
1.321 brouard 12851: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 12852: }else{
12853: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
12854: }
1.324 brouard 12855: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 12856: 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 12857: jk++;
12858: }
12859: printf("\n");
12860: fprintf(ficlog,"\n");
1.319 brouard 12861: fprintf(fichtm, "</tr>\n");
1.225 brouard 12862: }
12863: }
1.193 brouard 12864: }
1.203 brouard 12865: } /* end of hesscov and Wald tests */
1.319 brouard 12866: fprintf(fichtm,"</table>\n");
1.225 brouard 12867:
1.203 brouard 12868: /* */
1.126 brouard 12869: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
12870: printf("# Scales (for hessian or gradient estimation)\n");
12871: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
12872: for(i=1,jk=1; i <=nlstate; i++){
12873: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 12874: if (j!=i) {
12875: fprintf(ficres,"%1d%1d",i,j);
12876: printf("%1d%1d",i,j);
12877: fprintf(ficlog,"%1d%1d",i,j);
12878: for(k=1; k<=ncovmodel;k++){
12879: printf(" %.5e",delti[jk]);
12880: fprintf(ficlog," %.5e",delti[jk]);
12881: fprintf(ficres," %.5e",delti[jk]);
12882: jk++;
12883: }
12884: printf("\n");
12885: fprintf(ficlog,"\n");
12886: fprintf(ficres,"\n");
12887: }
1.126 brouard 12888: }
12889: }
12890:
12891: 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 12892: if(mle >= 1) /* To big for the screen */
1.126 brouard 12893: 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");
12894: 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");
12895: /* # 121 Var(a12)\n\ */
12896: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12897: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12898: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12899: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12900: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12901: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12902: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12903:
12904:
12905: /* Just to have a covariance matrix which will be more understandable
12906: even is we still don't want to manage dictionary of variables
12907: */
12908: for(itimes=1;itimes<=2;itimes++){
12909: jj=0;
12910: for(i=1; i <=nlstate; i++){
1.225 brouard 12911: for(j=1; j <=nlstate+ndeath; j++){
12912: if(j==i) continue;
12913: for(k=1; k<=ncovmodel;k++){
12914: jj++;
12915: ca[0]= k+'a'-1;ca[1]='\0';
12916: if(itimes==1){
12917: if(mle>=1)
12918: printf("#%1d%1d%d",i,j,k);
12919: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12920: fprintf(ficres,"#%1d%1d%d",i,j,k);
12921: }else{
12922: if(mle>=1)
12923: printf("%1d%1d%d",i,j,k);
12924: fprintf(ficlog,"%1d%1d%d",i,j,k);
12925: fprintf(ficres,"%1d%1d%d",i,j,k);
12926: }
12927: ll=0;
12928: for(li=1;li <=nlstate; li++){
12929: for(lj=1;lj <=nlstate+ndeath; lj++){
12930: if(lj==li) continue;
12931: for(lk=1;lk<=ncovmodel;lk++){
12932: ll++;
12933: if(ll<=jj){
12934: cb[0]= lk +'a'-1;cb[1]='\0';
12935: if(ll<jj){
12936: if(itimes==1){
12937: if(mle>=1)
12938: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12939: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12940: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12941: }else{
12942: if(mle>=1)
12943: printf(" %.5e",matcov[jj][ll]);
12944: fprintf(ficlog," %.5e",matcov[jj][ll]);
12945: fprintf(ficres," %.5e",matcov[jj][ll]);
12946: }
12947: }else{
12948: if(itimes==1){
12949: if(mle>=1)
12950: printf(" Var(%s%1d%1d)",ca,i,j);
12951: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12952: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12953: }else{
12954: if(mle>=1)
12955: printf(" %.7e",matcov[jj][ll]);
12956: fprintf(ficlog," %.7e",matcov[jj][ll]);
12957: fprintf(ficres," %.7e",matcov[jj][ll]);
12958: }
12959: }
12960: }
12961: } /* end lk */
12962: } /* end lj */
12963: } /* end li */
12964: if(mle>=1)
12965: printf("\n");
12966: fprintf(ficlog,"\n");
12967: fprintf(ficres,"\n");
12968: numlinepar++;
12969: } /* end k*/
12970: } /*end j */
1.126 brouard 12971: } /* end i */
12972: } /* end itimes */
12973:
12974: fflush(ficlog);
12975: fflush(ficres);
1.225 brouard 12976: while(fgets(line, MAXLINE, ficpar)) {
12977: /* If line starts with a # it is a comment */
12978: if (line[0] == '#') {
12979: numlinepar++;
12980: fputs(line,stdout);
12981: fputs(line,ficparo);
12982: fputs(line,ficlog);
1.299 brouard 12983: fputs(line,ficres);
1.225 brouard 12984: continue;
12985: }else
12986: break;
12987: }
12988:
1.209 brouard 12989: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12990: /* ungetc(c,ficpar); */
12991: /* fgets(line, MAXLINE, ficpar); */
12992: /* fputs(line,stdout); */
12993: /* fputs(line,ficparo); */
12994: /* } */
12995: /* ungetc(c,ficpar); */
1.126 brouard 12996:
12997: estepm=0;
1.209 brouard 12998: 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 12999:
13000: if (num_filled != 6) {
13001: 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);
13002: 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);
13003: goto end;
13004: }
13005: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
13006: }
13007: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
13008: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
13009:
1.209 brouard 13010: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 13011: if (estepm==0 || estepm < stepm) estepm=stepm;
13012: if (fage <= 2) {
13013: bage = ageminpar;
13014: fage = agemaxpar;
13015: }
13016:
13017: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 13018: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
13019: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 13020:
1.186 brouard 13021: /* Other stuffs, more or less useful */
1.254 brouard 13022: while(fgets(line, MAXLINE, ficpar)) {
13023: /* If line starts with a # it is a comment */
13024: if (line[0] == '#') {
13025: numlinepar++;
13026: fputs(line,stdout);
13027: fputs(line,ficparo);
13028: fputs(line,ficlog);
1.299 brouard 13029: fputs(line,ficres);
1.254 brouard 13030: continue;
13031: }else
13032: break;
13033: }
13034:
13035: 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){
13036:
13037: if (num_filled != 7) {
13038: 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);
13039: 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);
13040: goto end;
13041: }
13042: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
13043: 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);
13044: 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);
13045: 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 13046: }
1.254 brouard 13047:
13048: while(fgets(line, MAXLINE, ficpar)) {
13049: /* If line starts with a # it is a comment */
13050: if (line[0] == '#') {
13051: numlinepar++;
13052: fputs(line,stdout);
13053: fputs(line,ficparo);
13054: fputs(line,ficlog);
1.299 brouard 13055: fputs(line,ficres);
1.254 brouard 13056: continue;
13057: }else
13058: break;
1.126 brouard 13059: }
13060:
13061:
13062: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
13063: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
13064:
1.254 brouard 13065: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
13066: if (num_filled != 1) {
13067: 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);
13068: 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);
13069: goto end;
13070: }
13071: printf("pop_based=%d\n",popbased);
13072: fprintf(ficlog,"pop_based=%d\n",popbased);
13073: fprintf(ficparo,"pop_based=%d\n",popbased);
13074: fprintf(ficres,"pop_based=%d\n",popbased);
13075: }
13076:
1.258 brouard 13077: /* Results */
1.307 brouard 13078: endishere=0;
1.258 brouard 13079: nresult=0;
1.308 brouard 13080: parameterline=0;
1.258 brouard 13081: do{
13082: if(!fgets(line, MAXLINE, ficpar)){
13083: endishere=1;
1.308 brouard 13084: parameterline=15;
1.258 brouard 13085: }else if (line[0] == '#') {
13086: /* If line starts with a # it is a comment */
1.254 brouard 13087: numlinepar++;
13088: fputs(line,stdout);
13089: fputs(line,ficparo);
13090: fputs(line,ficlog);
1.299 brouard 13091: fputs(line,ficres);
1.254 brouard 13092: continue;
1.258 brouard 13093: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
13094: parameterline=11;
1.296 brouard 13095: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 13096: parameterline=12;
1.307 brouard 13097: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 13098: parameterline=13;
1.307 brouard 13099: }
1.258 brouard 13100: else{
13101: parameterline=14;
1.254 brouard 13102: }
1.308 brouard 13103: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 13104: case 11:
1.296 brouard 13105: 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)){
13106: 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 13107: 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);
13108: 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);
13109: 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);
13110: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 13111: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
13112: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 13113: prvforecast = 1;
13114: }
13115: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 13116: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13117: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
13118: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 13119: prvforecast = 2;
13120: }
13121: else {
13122: 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);
13123: 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);
13124: goto end;
1.258 brouard 13125: }
1.254 brouard 13126: break;
1.258 brouard 13127: case 12:
1.296 brouard 13128: 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)){
13129: 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);
13130: 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);
13131: 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);
13132: 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);
13133: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 13134: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
13135: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 13136: prvbackcast = 1;
13137: }
13138: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 13139: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
13140: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
13141: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 13142: prvbackcast = 2;
13143: }
13144: else {
13145: 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);
13146: 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);
13147: goto end;
1.258 brouard 13148: }
1.230 brouard 13149: break;
1.258 brouard 13150: case 13:
1.307 brouard 13151: num_filled=sscanf(line,"result:%[^\n]\n",resultline);
13152: nresult++; /* Sum of resultlines */
13153: printf("Result %d: result:%s\n",nresult, resultline);
1.318 brouard 13154: if(nresult > MAXRESULTLINESPONE-1){
13155: 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);
13156: 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 13157: goto end;
13158: }
1.310 brouard 13159: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 13160: fprintf(ficparo,"result: %s\n",resultline);
13161: fprintf(ficres,"result: %s\n",resultline);
13162: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 13163: } else
13164: goto end;
1.307 brouard 13165: break;
13166: case 14:
13167: printf("Error: Unknown command '%s'\n",line);
13168: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 13169: if(line[0] == ' ' || line[0] == '\n'){
13170: printf("It should not be an empty line '%s'\n",line);
13171: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
13172: }
1.307 brouard 13173: if(ncovmodel >=2 && nresult==0 ){
13174: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
13175: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 13176: }
1.307 brouard 13177: /* goto end; */
13178: break;
1.308 brouard 13179: case 15:
13180: printf("End of resultlines.\n");
13181: fprintf(ficlog,"End of resultlines.\n");
13182: break;
13183: default: /* parameterline =0 */
1.307 brouard 13184: nresult=1;
13185: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 13186: } /* End switch parameterline */
13187: }while(endishere==0); /* End do */
1.126 brouard 13188:
1.230 brouard 13189: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 13190: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 13191:
13192: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 13193: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 13194: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 13195: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13196: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 13197: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 13198: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
13199: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 13200: }else{
1.270 brouard 13201: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 13202: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
13203: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
13204: if(prvforecast==1){
13205: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
13206: jprojd=jproj1;
13207: mprojd=mproj1;
13208: anprojd=anproj1;
13209: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
13210: jprojf=jproj2;
13211: mprojf=mproj2;
13212: anprojf=anproj2;
13213: } else if(prvforecast == 2){
13214: dateprojd=dateintmean;
13215: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
13216: dateprojf=dateintmean+yrfproj;
13217: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
13218: }
13219: if(prvbackcast==1){
13220: datebackd=(jback1+12*mback1+365*anback1)/365;
13221: jbackd=jback1;
13222: mbackd=mback1;
13223: anbackd=anback1;
13224: datebackf=(jback2+12*mback2+365*anback2)/365;
13225: jbackf=jback2;
13226: mbackf=mback2;
13227: anbackf=anback2;
13228: } else if(prvbackcast == 2){
13229: datebackd=dateintmean;
13230: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
13231: datebackf=dateintmean-yrbproj;
13232: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
13233: }
13234:
13235: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 13236: }
13237: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 13238: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
13239: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 13240:
1.225 brouard 13241: /*------------ free_vector -------------*/
13242: /* chdir(path); */
1.220 brouard 13243:
1.215 brouard 13244: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
13245: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
13246: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
13247: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 13248: free_lvector(num,firstobs,lastobs);
13249: free_vector(agedc,firstobs,lastobs);
1.126 brouard 13250: /*free_matrix(covar,0,NCOVMAX,1,n);*/
13251: /*free_matrix(covar,1,NCOVMAX,1,n);*/
13252: fclose(ficparo);
13253: fclose(ficres);
1.220 brouard 13254:
13255:
1.186 brouard 13256: /* Other results (useful)*/
1.220 brouard 13257:
13258:
1.126 brouard 13259: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 13260: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
13261: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 13262: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 13263: fclose(ficrespl);
13264:
13265: /*------------- h Pij x at various ages ------------*/
1.180 brouard 13266: /*#include "hpijx.h"*/
13267: hPijx(p, bage, fage);
1.145 brouard 13268: fclose(ficrespij);
1.227 brouard 13269:
1.220 brouard 13270: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 13271: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 13272: k=1;
1.126 brouard 13273: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 13274:
1.269 brouard 13275: /* Prevalence for each covariate combination in probs[age][status][cov] */
13276: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13277: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 13278: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 13279: for(k=1;k<=ncovcombmax;k++)
13280: probs[i][j][k]=0.;
1.269 brouard 13281: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
13282: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 13283: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 13284: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13285: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 13286: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 13287: for(k=1;k<=ncovcombmax;k++)
13288: mobaverages[i][j][k]=0.;
1.219 brouard 13289: mobaverage=mobaverages;
13290: if (mobilav!=0) {
1.235 brouard 13291: printf("Movingaveraging observed prevalence\n");
1.258 brouard 13292: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 13293: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
13294: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
13295: printf(" Error in movingaverage mobilav=%d\n",mobilav);
13296: }
1.269 brouard 13297: } else if (mobilavproj !=0) {
1.235 brouard 13298: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 13299: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 13300: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
13301: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
13302: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
13303: }
1.269 brouard 13304: }else{
13305: printf("Internal error moving average\n");
13306: fflush(stdout);
13307: exit(1);
1.219 brouard 13308: }
13309: }/* end if moving average */
1.227 brouard 13310:
1.126 brouard 13311: /*---------- Forecasting ------------------*/
1.296 brouard 13312: if(prevfcast==1){
13313: /* /\* if(stepm ==1){*\/ */
13314: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13315: /*This done previously after freqsummary.*/
13316: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
13317: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
13318:
13319: /* } else if (prvforecast==2){ */
13320: /* /\* if(stepm ==1){*\/ */
13321: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13322: /* } */
13323: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
13324: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 13325: }
1.269 brouard 13326:
1.296 brouard 13327: /* Prevbcasting */
13328: if(prevbcast==1){
1.219 brouard 13329: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13330: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13331: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13332:
13333: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
13334:
13335: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 13336:
1.219 brouard 13337: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
13338: fclose(ficresplb);
13339:
1.222 brouard 13340: hBijx(p, bage, fage, mobaverage);
13341: fclose(ficrespijb);
1.219 brouard 13342:
1.296 brouard 13343: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
13344: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
13345: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
13346: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
13347: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
13348: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
13349:
13350:
1.269 brouard 13351: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13352:
13353:
1.269 brouard 13354: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 13355: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13356: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13357: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 13358: } /* end Prevbcasting */
1.268 brouard 13359:
1.186 brouard 13360:
13361: /* ------ Other prevalence ratios------------ */
1.126 brouard 13362:
1.215 brouard 13363: free_ivector(wav,1,imx);
13364: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
13365: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
13366: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 13367:
13368:
1.127 brouard 13369: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 13370:
1.201 brouard 13371: strcpy(filerese,"E_");
13372: strcat(filerese,fileresu);
1.126 brouard 13373: if((ficreseij=fopen(filerese,"w"))==NULL) {
13374: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13375: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13376: }
1.208 brouard 13377: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
13378: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 13379:
13380: pstamp(ficreseij);
1.219 brouard 13381:
1.235 brouard 13382: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13383: if (cptcovn < 1){i1=1;}
13384:
13385: for(nres=1; nres <= nresult; nres++) /* For each resultline */
13386: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 13387: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 13388: continue;
1.219 brouard 13389: fprintf(ficreseij,"\n#****** ");
1.235 brouard 13390: printf("\n#****** ");
1.225 brouard 13391: for(j=1;j<=cptcoveff;j++) {
1.330 brouard 13392: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
13393: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.235 brouard 13394: }
13395: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13396: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13397: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 13398: }
13399: fprintf(ficreseij,"******\n");
1.235 brouard 13400: printf("******\n");
1.219 brouard 13401:
13402: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13403: oldm=oldms;savm=savms;
1.330 brouard 13404: /* 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 13405: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 13406:
1.219 brouard 13407: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 13408: }
13409: fclose(ficreseij);
1.208 brouard 13410: printf("done evsij\n");fflush(stdout);
13411: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 13412:
1.218 brouard 13413:
1.227 brouard 13414: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 13415:
1.201 brouard 13416: strcpy(filerest,"T_");
13417: strcat(filerest,fileresu);
1.127 brouard 13418: if((ficrest=fopen(filerest,"w"))==NULL) {
13419: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
13420: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
13421: }
1.208 brouard 13422: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
13423: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 13424: strcpy(fileresstde,"STDE_");
13425: strcat(fileresstde,fileresu);
1.126 brouard 13426: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 13427: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
13428: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 13429: }
1.227 brouard 13430: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
13431: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 13432:
1.201 brouard 13433: strcpy(filerescve,"CVE_");
13434: strcat(filerescve,fileresu);
1.126 brouard 13435: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 13436: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
13437: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 13438: }
1.227 brouard 13439: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
13440: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 13441:
1.201 brouard 13442: strcpy(fileresv,"V_");
13443: strcat(fileresv,fileresu);
1.126 brouard 13444: if((ficresvij=fopen(fileresv,"w"))==NULL) {
13445: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
13446: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
13447: }
1.227 brouard 13448: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
13449: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 13450:
1.235 brouard 13451: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13452: if (cptcovn < 1){i1=1;}
13453:
13454: for(nres=1; nres <= nresult; nres++) /* For each resultline */
13455: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 13456: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 13457: continue;
1.321 brouard 13458: printf("\n# model %s \n#****** Result for:", model);
13459: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
13460: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.227 brouard 13461: for(j=1;j<=cptcoveff;j++){
1.330 brouard 13462: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
13463: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
13464: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.227 brouard 13465: }
1.235 brouard 13466: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13467: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13468: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13469: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13470: }
1.208 brouard 13471: fprintf(ficrest,"******\n");
1.227 brouard 13472: fprintf(ficlog,"******\n");
13473: printf("******\n");
1.208 brouard 13474:
13475: fprintf(ficresstdeij,"\n#****** ");
13476: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 13477: for(j=1;j<=cptcoveff;j++) {
1.330 brouard 13478: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
13479: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.208 brouard 13480: }
1.235 brouard 13481: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13482: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13483: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13484: }
1.208 brouard 13485: fprintf(ficresstdeij,"******\n");
13486: fprintf(ficrescveij,"******\n");
13487:
13488: fprintf(ficresvij,"\n#****** ");
1.238 brouard 13489: /* pstamp(ficresvij); */
1.225 brouard 13490: for(j=1;j<=cptcoveff;j++)
1.330 brouard 13491: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]);
1.235 brouard 13492: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13493: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13494: }
1.208 brouard 13495: fprintf(ficresvij,"******\n");
13496:
13497: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13498: oldm=oldms;savm=savms;
1.235 brouard 13499: printf(" cvevsij ");
13500: fprintf(ficlog, " cvevsij ");
13501: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 13502: printf(" end cvevsij \n ");
13503: fprintf(ficlog, " end cvevsij \n ");
13504:
13505: /*
13506: */
13507: /* goto endfree; */
13508:
13509: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13510: pstamp(ficrest);
13511:
1.269 brouard 13512: epj=vector(1,nlstate+1);
1.208 brouard 13513: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 13514: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
13515: cptcod= 0; /* To be deleted */
13516: printf("varevsij vpopbased=%d \n",vpopbased);
13517: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 13518: 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 13519: 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 ");
13520: if(vpopbased==1)
13521: 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);
13522: else
1.288 brouard 13523: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13524: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
13525: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
13526: fprintf(ficrest,"\n");
13527: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 13528: printf("Computing age specific forward period (stable) prevalences in each health state \n");
13529: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13530: for(age=bage; age <=fage ;age++){
1.235 brouard 13531: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 13532: if (vpopbased==1) {
13533: if(mobilav ==0){
13534: for(i=1; i<=nlstate;i++)
13535: prlim[i][i]=probs[(int)age][i][k];
13536: }else{ /* mobilav */
13537: for(i=1; i<=nlstate;i++)
13538: prlim[i][i]=mobaverage[(int)age][i][k];
13539: }
13540: }
1.219 brouard 13541:
1.227 brouard 13542: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
13543: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
13544: /* printf(" age %4.0f ",age); */
13545: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
13546: for(i=1, epj[j]=0.;i <=nlstate;i++) {
13547: epj[j] += prlim[i][i]*eij[i][j][(int)age];
13548: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
13549: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
13550: }
13551: epj[nlstate+1] +=epj[j];
13552: }
13553: /* printf(" age %4.0f \n",age); */
1.219 brouard 13554:
1.227 brouard 13555: for(i=1, vepp=0.;i <=nlstate;i++)
13556: for(j=1;j <=nlstate;j++)
13557: vepp += vareij[i][j][(int)age];
13558: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
13559: for(j=1;j <=nlstate;j++){
13560: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
13561: }
13562: fprintf(ficrest,"\n");
13563: }
1.208 brouard 13564: } /* End vpopbased */
1.269 brouard 13565: free_vector(epj,1,nlstate+1);
1.208 brouard 13566: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
13567: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 13568: printf("done selection\n");fflush(stdout);
13569: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 13570:
1.235 brouard 13571: } /* End k selection */
1.227 brouard 13572:
13573: printf("done State-specific expectancies\n");fflush(stdout);
13574: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
13575:
1.288 brouard 13576: /* variance-covariance of forward period prevalence*/
1.269 brouard 13577: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13578:
1.227 brouard 13579:
1.290 brouard 13580: free_vector(weight,firstobs,lastobs);
1.330 brouard 13581: free_imatrix(Tvardk,1,NCOVMAX,1,2);
1.227 brouard 13582: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 13583: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
13584: free_matrix(anint,1,maxwav,firstobs,lastobs);
13585: free_matrix(mint,1,maxwav,firstobs,lastobs);
13586: free_ivector(cod,firstobs,lastobs);
1.227 brouard 13587: free_ivector(tab,1,NCOVMAX);
13588: fclose(ficresstdeij);
13589: fclose(ficrescveij);
13590: fclose(ficresvij);
13591: fclose(ficrest);
13592: fclose(ficpar);
13593:
13594:
1.126 brouard 13595: /*---------- End : free ----------------*/
1.219 brouard 13596: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 13597: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
13598: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 13599: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
13600: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 13601: } /* mle==-3 arrives here for freeing */
1.227 brouard 13602: /* endfree:*/
13603: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
13604: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
13605: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 13606: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
13607: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
13608: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
13609: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 13610: free_matrix(matcov,1,npar,1,npar);
13611: free_matrix(hess,1,npar,1,npar);
13612: /*free_vector(delti,1,npar);*/
13613: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13614: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 13615: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 13616: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13617:
13618: free_ivector(ncodemax,1,NCOVMAX);
13619: free_ivector(ncodemaxwundef,1,NCOVMAX);
13620: free_ivector(Dummy,-1,NCOVMAX);
13621: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 13622: free_ivector(DummyV,1,NCOVMAX);
13623: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 13624: free_ivector(Typevar,-1,NCOVMAX);
13625: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 13626: free_ivector(TvarsQ,1,NCOVMAX);
13627: free_ivector(TvarsQind,1,NCOVMAX);
13628: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 13629: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 13630: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 13631: free_ivector(TvarFD,1,NCOVMAX);
13632: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 13633: free_ivector(TvarF,1,NCOVMAX);
13634: free_ivector(TvarFind,1,NCOVMAX);
13635: free_ivector(TvarV,1,NCOVMAX);
13636: free_ivector(TvarVind,1,NCOVMAX);
13637: free_ivector(TvarA,1,NCOVMAX);
13638: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 13639: free_ivector(TvarFQ,1,NCOVMAX);
13640: free_ivector(TvarFQind,1,NCOVMAX);
13641: free_ivector(TvarVD,1,NCOVMAX);
13642: free_ivector(TvarVDind,1,NCOVMAX);
13643: free_ivector(TvarVQ,1,NCOVMAX);
13644: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 13645: free_ivector(Tvarsel,1,NCOVMAX);
13646: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 13647: free_ivector(Tposprod,1,NCOVMAX);
13648: free_ivector(Tprod,1,NCOVMAX);
13649: free_ivector(Tvaraff,1,NCOVMAX);
13650: free_ivector(invalidvarcomb,1,ncovcombmax);
13651: free_ivector(Tage,1,NCOVMAX);
13652: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 13653: free_ivector(TmodelInvind,1,NCOVMAX);
13654: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 13655:
13656: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
13657: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 13658: fflush(fichtm);
13659: fflush(ficgp);
13660:
1.227 brouard 13661:
1.126 brouard 13662: if((nberr >0) || (nbwarn>0)){
1.216 brouard 13663: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
13664: 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 13665: }else{
13666: printf("End of Imach\n");
13667: fprintf(ficlog,"End of Imach\n");
13668: }
13669: printf("See log file on %s\n",filelog);
13670: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 13671: /*(void) gettimeofday(&end_time,&tzp);*/
13672: rend_time = time(NULL);
13673: end_time = *localtime(&rend_time);
13674: /* tml = *localtime(&end_time.tm_sec); */
13675: strcpy(strtend,asctime(&end_time));
1.126 brouard 13676: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
13677: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 13678: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 13679:
1.157 brouard 13680: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
13681: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
13682: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 13683: /* printf("Total time was %d uSec.\n", total_usecs);*/
13684: /* if(fileappend(fichtm,optionfilehtm)){ */
13685: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13686: fclose(fichtm);
13687: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13688: fclose(fichtmcov);
13689: fclose(ficgp);
13690: fclose(ficlog);
13691: /*------ End -----------*/
1.227 brouard 13692:
1.281 brouard 13693:
13694: /* Executes gnuplot */
1.227 brouard 13695:
13696: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 13697: #ifdef WIN32
1.227 brouard 13698: if (_chdir(pathcd) != 0)
13699: printf("Can't move to directory %s!\n",path);
13700: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 13701: #else
1.227 brouard 13702: if(chdir(pathcd) != 0)
13703: printf("Can't move to directory %s!\n", path);
13704: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 13705: #endif
1.126 brouard 13706: printf("Current directory %s!\n",pathcd);
13707: /*strcat(plotcmd,CHARSEPARATOR);*/
13708: sprintf(plotcmd,"gnuplot");
1.157 brouard 13709: #ifdef _WIN32
1.126 brouard 13710: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
13711: #endif
13712: if(!stat(plotcmd,&info)){
1.158 brouard 13713: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13714: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 13715: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 13716: }else
13717: strcpy(pplotcmd,plotcmd);
1.157 brouard 13718: #ifdef __unix
1.126 brouard 13719: strcpy(plotcmd,GNUPLOTPROGRAM);
13720: if(!stat(plotcmd,&info)){
1.158 brouard 13721: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13722: }else
13723: strcpy(pplotcmd,plotcmd);
13724: #endif
13725: }else
13726: strcpy(pplotcmd,plotcmd);
13727:
13728: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 13729: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 13730: strcpy(pplotcmd,plotcmd);
1.227 brouard 13731:
1.126 brouard 13732: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 13733: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 13734: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 13735: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 13736: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 13737: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 13738: strcpy(plotcmd,pplotcmd);
13739: }
1.126 brouard 13740: }
1.158 brouard 13741: printf(" Successful, please wait...");
1.126 brouard 13742: while (z[0] != 'q') {
13743: /* chdir(path); */
1.154 brouard 13744: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 13745: scanf("%s",z);
13746: /* if (z[0] == 'c') system("./imach"); */
13747: if (z[0] == 'e') {
1.158 brouard 13748: #ifdef __APPLE__
1.152 brouard 13749: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 13750: #elif __linux
13751: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 13752: #else
1.152 brouard 13753: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 13754: #endif
13755: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
13756: system(pplotcmd);
1.126 brouard 13757: }
13758: else if (z[0] == 'g') system(plotcmd);
13759: else if (z[0] == 'q') exit(0);
13760: }
1.227 brouard 13761: end:
1.126 brouard 13762: while (z[0] != 'q') {
1.195 brouard 13763: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 13764: scanf("%s",z);
13765: }
1.283 brouard 13766: printf("End\n");
1.282 brouard 13767: exit(0);
1.126 brouard 13768: }
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