Annotation of imach/src/imach.c, revision 1.321
1.321 ! brouard 1: /* $Id: imach.c,v 1.320 2022/06/02 05:10:11 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.321 ! brouard 4: Revision 1.320 2022/06/02 05:10:11 brouard
! 5: *** empty log message ***
! 6:
1.320 brouard 7: Revision 1.319 2022/06/02 04:45:11 brouard
8: * imach.c (Module): Adding the Wald tests from the log to the main
9: htm for better display of the maximum likelihood estimators.
10:
1.319 brouard 11: Revision 1.318 2022/05/24 08:10:59 brouard
12: * imach.c (Module): Some attempts to find a bug of wrong estimates
13: of confidencce intervals with product in the equation modelC
14:
1.318 brouard 15: Revision 1.317 2022/05/15 15:06:23 brouard
16: * imach.c (Module): Some minor improvements
17:
1.317 brouard 18: Revision 1.316 2022/05/11 15:11:31 brouard
19: Summary: r27
20:
1.316 brouard 21: Revision 1.315 2022/05/11 15:06:32 brouard
22: *** empty log message ***
23:
1.315 brouard 24: Revision 1.314 2022/04/13 17:43:09 brouard
25: * imach.c (Module): Adding link to text data files
26:
1.314 brouard 27: Revision 1.313 2022/04/11 15:57:42 brouard
28: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
29:
1.313 brouard 30: Revision 1.312 2022/04/05 21:24:39 brouard
31: *** empty log message ***
32:
1.312 brouard 33: Revision 1.311 2022/04/05 21:03:51 brouard
34: Summary: Fixed quantitative covariates
35:
36: Fixed covariates (dummy or quantitative)
37: with missing values have never been allowed but are ERRORS and
38: program quits. Standard deviations of fixed covariates were
39: wrongly computed. Mean and standard deviations of time varying
40: covariates are still not computed.
41:
1.311 brouard 42: Revision 1.310 2022/03/17 08:45:53 brouard
43: Summary: 99r25
44:
45: Improving detection of errors: result lines should be compatible with
46: the model.
47:
1.310 brouard 48: Revision 1.309 2021/05/20 12:39:14 brouard
49: Summary: Version 0.99r24
50:
1.309 brouard 51: Revision 1.308 2021/03/31 13:11:57 brouard
52: Summary: Version 0.99r23
53:
54:
55: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
56:
1.308 brouard 57: Revision 1.307 2021/03/08 18:11:32 brouard
58: Summary: 0.99r22 fixed bug on result:
59:
1.307 brouard 60: Revision 1.306 2021/02/20 15:44:02 brouard
61: Summary: Version 0.99r21
62:
63: * imach.c (Module): Fix bug on quitting after result lines!
64: (Module): Version 0.99r21
65:
1.306 brouard 66: Revision 1.305 2021/02/20 15:28:30 brouard
67: * imach.c (Module): Fix bug on quitting after result lines!
68:
1.305 brouard 69: Revision 1.304 2021/02/12 11:34:20 brouard
70: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
71:
1.304 brouard 72: Revision 1.303 2021/02/11 19:50:15 brouard
73: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
74:
1.303 brouard 75: Revision 1.302 2020/02/22 21:00:05 brouard
76: * (Module): imach.c Update mle=-3 (for computing Life expectancy
77: and life table from the data without any state)
78:
1.302 brouard 79: Revision 1.301 2019/06/04 13:51:20 brouard
80: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
81:
1.301 brouard 82: Revision 1.300 2019/05/22 19:09:45 brouard
83: Summary: version 0.99r19 of May 2019
84:
1.300 brouard 85: Revision 1.299 2019/05/22 18:37:08 brouard
86: Summary: Cleaned 0.99r19
87:
1.299 brouard 88: Revision 1.298 2019/05/22 18:19:56 brouard
89: *** empty log message ***
90:
1.298 brouard 91: Revision 1.297 2019/05/22 17:56:10 brouard
92: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
93:
1.297 brouard 94: Revision 1.296 2019/05/20 13:03:18 brouard
95: Summary: Projection syntax simplified
96:
97:
98: We can now start projections, forward or backward, from the mean date
99: of inteviews up to or down to a number of years of projection:
100: prevforecast=1 yearsfproj=15.3 mobil_average=0
101: or
102: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
103: or
104: prevbackcast=1 yearsbproj=12.3 mobil_average=1
105: or
106: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
107:
1.296 brouard 108: Revision 1.295 2019/05/18 09:52:50 brouard
109: Summary: doxygen tex bug
110:
1.295 brouard 111: Revision 1.294 2019/05/16 14:54:33 brouard
112: Summary: There was some wrong lines added
113:
1.294 brouard 114: Revision 1.293 2019/05/09 15:17:34 brouard
115: *** empty log message ***
116:
1.293 brouard 117: Revision 1.292 2019/05/09 14:17:20 brouard
118: Summary: Some updates
119:
1.292 brouard 120: Revision 1.291 2019/05/09 13:44:18 brouard
121: Summary: Before ncovmax
122:
1.291 brouard 123: Revision 1.290 2019/05/09 13:39:37 brouard
124: Summary: 0.99r18 unlimited number of individuals
125:
126: 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.
127:
1.290 brouard 128: Revision 1.289 2018/12/13 09:16:26 brouard
129: Summary: Bug for young ages (<-30) will be in r17
130:
1.289 brouard 131: Revision 1.288 2018/05/02 20:58:27 brouard
132: Summary: Some bugs fixed
133:
1.288 brouard 134: Revision 1.287 2018/05/01 17:57:25 brouard
135: Summary: Bug fixed by providing frequencies only for non missing covariates
136:
1.287 brouard 137: Revision 1.286 2018/04/27 14:27:04 brouard
138: Summary: some minor bugs
139:
1.286 brouard 140: Revision 1.285 2018/04/21 21:02:16 brouard
141: Summary: Some bugs fixed, valgrind tested
142:
1.285 brouard 143: Revision 1.284 2018/04/20 05:22:13 brouard
144: Summary: Computing mean and stdeviation of fixed quantitative variables
145:
1.284 brouard 146: Revision 1.283 2018/04/19 14:49:16 brouard
147: Summary: Some minor bugs fixed
148:
1.283 brouard 149: Revision 1.282 2018/02/27 22:50:02 brouard
150: *** empty log message ***
151:
1.282 brouard 152: Revision 1.281 2018/02/27 19:25:23 brouard
153: Summary: Adding second argument for quitting
154:
1.281 brouard 155: Revision 1.280 2018/02/21 07:58:13 brouard
156: Summary: 0.99r15
157:
158: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
159:
1.280 brouard 160: Revision 1.279 2017/07/20 13:35:01 brouard
161: Summary: temporary working
162:
1.279 brouard 163: Revision 1.278 2017/07/19 14:09:02 brouard
164: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
165:
1.278 brouard 166: Revision 1.277 2017/07/17 08:53:49 brouard
167: Summary: BOM files can be read now
168:
1.277 brouard 169: Revision 1.276 2017/06/30 15:48:31 brouard
170: Summary: Graphs improvements
171:
1.276 brouard 172: Revision 1.275 2017/06/30 13:39:33 brouard
173: Summary: Saito's color
174:
1.275 brouard 175: Revision 1.274 2017/06/29 09:47:08 brouard
176: Summary: Version 0.99r14
177:
1.274 brouard 178: Revision 1.273 2017/06/27 11:06:02 brouard
179: Summary: More documentation on projections
180:
1.273 brouard 181: Revision 1.272 2017/06/27 10:22:40 brouard
182: Summary: Color of backprojection changed from 6 to 5(yellow)
183:
1.272 brouard 184: Revision 1.271 2017/06/27 10:17:50 brouard
185: Summary: Some bug with rint
186:
1.271 brouard 187: Revision 1.270 2017/05/24 05:45:29 brouard
188: *** empty log message ***
189:
1.270 brouard 190: Revision 1.269 2017/05/23 08:39:25 brouard
191: Summary: Code into subroutine, cleanings
192:
1.269 brouard 193: Revision 1.268 2017/05/18 20:09:32 brouard
194: Summary: backprojection and confidence intervals of backprevalence
195:
1.268 brouard 196: Revision 1.267 2017/05/13 10:25:05 brouard
197: Summary: temporary save for backprojection
198:
1.267 brouard 199: Revision 1.266 2017/05/13 07:26:12 brouard
200: Summary: Version 0.99r13 (improvements and bugs fixed)
201:
1.266 brouard 202: Revision 1.265 2017/04/26 16:22:11 brouard
203: Summary: imach 0.99r13 Some bugs fixed
204:
1.265 brouard 205: Revision 1.264 2017/04/26 06:01:29 brouard
206: Summary: Labels in graphs
207:
1.264 brouard 208: Revision 1.263 2017/04/24 15:23:15 brouard
209: Summary: to save
210:
1.263 brouard 211: Revision 1.262 2017/04/18 16:48:12 brouard
212: *** empty log message ***
213:
1.262 brouard 214: Revision 1.261 2017/04/05 10:14:09 brouard
215: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
216:
1.261 brouard 217: Revision 1.260 2017/04/04 17:46:59 brouard
218: Summary: Gnuplot indexations fixed (humm)
219:
1.260 brouard 220: Revision 1.259 2017/04/04 13:01:16 brouard
221: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
222:
1.259 brouard 223: Revision 1.258 2017/04/03 10:17:47 brouard
224: Summary: Version 0.99r12
225:
226: Some cleanings, conformed with updated documentation.
227:
1.258 brouard 228: Revision 1.257 2017/03/29 16:53:30 brouard
229: Summary: Temp
230:
1.257 brouard 231: Revision 1.256 2017/03/27 05:50:23 brouard
232: Summary: Temporary
233:
1.256 brouard 234: Revision 1.255 2017/03/08 16:02:28 brouard
235: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
236:
1.255 brouard 237: Revision 1.254 2017/03/08 07:13:00 brouard
238: Summary: Fixing data parameter line
239:
1.254 brouard 240: Revision 1.253 2016/12/15 11:59:41 brouard
241: Summary: 0.99 in progress
242:
1.253 brouard 243: Revision 1.252 2016/09/15 21:15:37 brouard
244: *** empty log message ***
245:
1.252 brouard 246: Revision 1.251 2016/09/15 15:01:13 brouard
247: Summary: not working
248:
1.251 brouard 249: Revision 1.250 2016/09/08 16:07:27 brouard
250: Summary: continue
251:
1.250 brouard 252: Revision 1.249 2016/09/07 17:14:18 brouard
253: Summary: Starting values from frequencies
254:
1.249 brouard 255: Revision 1.248 2016/09/07 14:10:18 brouard
256: *** empty log message ***
257:
1.248 brouard 258: Revision 1.247 2016/09/02 11:11:21 brouard
259: *** empty log message ***
260:
1.247 brouard 261: Revision 1.246 2016/09/02 08:49:22 brouard
262: *** empty log message ***
263:
1.246 brouard 264: Revision 1.245 2016/09/02 07:25:01 brouard
265: *** empty log message ***
266:
1.245 brouard 267: Revision 1.244 2016/09/02 07:17:34 brouard
268: *** empty log message ***
269:
1.244 brouard 270: Revision 1.243 2016/09/02 06:45:35 brouard
271: *** empty log message ***
272:
1.243 brouard 273: Revision 1.242 2016/08/30 15:01:20 brouard
274: Summary: Fixing a lots
275:
1.242 brouard 276: Revision 1.241 2016/08/29 17:17:25 brouard
277: Summary: gnuplot problem in Back projection to fix
278:
1.241 brouard 279: Revision 1.240 2016/08/29 07:53:18 brouard
280: Summary: Better
281:
1.240 brouard 282: Revision 1.239 2016/08/26 15:51:03 brouard
283: Summary: Improvement in Powell output in order to copy and paste
284:
285: Author:
286:
1.239 brouard 287: Revision 1.238 2016/08/26 14:23:35 brouard
288: Summary: Starting tests of 0.99
289:
1.238 brouard 290: Revision 1.237 2016/08/26 09:20:19 brouard
291: Summary: to valgrind
292:
1.237 brouard 293: Revision 1.236 2016/08/25 10:50:18 brouard
294: *** empty log message ***
295:
1.236 brouard 296: Revision 1.235 2016/08/25 06:59:23 brouard
297: *** empty log message ***
298:
1.235 brouard 299: Revision 1.234 2016/08/23 16:51:20 brouard
300: *** empty log message ***
301:
1.234 brouard 302: Revision 1.233 2016/08/23 07:40:50 brouard
303: Summary: not working
304:
1.233 brouard 305: Revision 1.232 2016/08/22 14:20:21 brouard
306: Summary: not working
307:
1.232 brouard 308: Revision 1.231 2016/08/22 07:17:15 brouard
309: Summary: not working
310:
1.231 brouard 311: Revision 1.230 2016/08/22 06:55:53 brouard
312: Summary: Not working
313:
1.230 brouard 314: Revision 1.229 2016/07/23 09:45:53 brouard
315: Summary: Completing for func too
316:
1.229 brouard 317: Revision 1.228 2016/07/22 17:45:30 brouard
318: Summary: Fixing some arrays, still debugging
319:
1.227 brouard 320: Revision 1.226 2016/07/12 18:42:34 brouard
321: Summary: temp
322:
1.226 brouard 323: Revision 1.225 2016/07/12 08:40:03 brouard
324: Summary: saving but not running
325:
1.225 brouard 326: Revision 1.224 2016/07/01 13:16:01 brouard
327: Summary: Fixes
328:
1.224 brouard 329: Revision 1.223 2016/02/19 09:23:35 brouard
330: Summary: temporary
331:
1.223 brouard 332: Revision 1.222 2016/02/17 08:14:50 brouard
333: Summary: Probably last 0.98 stable version 0.98r6
334:
1.222 brouard 335: Revision 1.221 2016/02/15 23:35:36 brouard
336: Summary: minor bug
337:
1.220 brouard 338: Revision 1.219 2016/02/15 00:48:12 brouard
339: *** empty log message ***
340:
1.219 brouard 341: Revision 1.218 2016/02/12 11:29:23 brouard
342: Summary: 0.99 Back projections
343:
1.218 brouard 344: Revision 1.217 2015/12/23 17:18:31 brouard
345: Summary: Experimental backcast
346:
1.217 brouard 347: Revision 1.216 2015/12/18 17:32:11 brouard
348: Summary: 0.98r4 Warning and status=-2
349:
350: Version 0.98r4 is now:
351: - displaying an error when status is -1, date of interview unknown and date of death known;
352: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
353: Older changes concerning s=-2, dating from 2005 have been supersed.
354:
1.216 brouard 355: Revision 1.215 2015/12/16 08:52:24 brouard
356: Summary: 0.98r4 working
357:
1.215 brouard 358: Revision 1.214 2015/12/16 06:57:54 brouard
359: Summary: temporary not working
360:
1.214 brouard 361: Revision 1.213 2015/12/11 18:22:17 brouard
362: Summary: 0.98r4
363:
1.213 brouard 364: Revision 1.212 2015/11/21 12:47:24 brouard
365: Summary: minor typo
366:
1.212 brouard 367: Revision 1.211 2015/11/21 12:41:11 brouard
368: Summary: 0.98r3 with some graph of projected cross-sectional
369:
370: Author: Nicolas Brouard
371:
1.211 brouard 372: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 373: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 374: Summary: Adding ftolpl parameter
375: Author: N Brouard
376:
377: We had difficulties to get smoothed confidence intervals. It was due
378: to the period prevalence which wasn't computed accurately. The inner
379: parameter ftolpl is now an outer parameter of the .imach parameter
380: file after estepm. If ftolpl is small 1.e-4 and estepm too,
381: computation are long.
382:
1.209 brouard 383: Revision 1.208 2015/11/17 14:31:57 brouard
384: Summary: temporary
385:
1.208 brouard 386: Revision 1.207 2015/10/27 17:36:57 brouard
387: *** empty log message ***
388:
1.207 brouard 389: Revision 1.206 2015/10/24 07:14:11 brouard
390: *** empty log message ***
391:
1.206 brouard 392: Revision 1.205 2015/10/23 15:50:53 brouard
393: Summary: 0.98r3 some clarification for graphs on likelihood contributions
394:
1.205 brouard 395: Revision 1.204 2015/10/01 16:20:26 brouard
396: Summary: Some new graphs of contribution to likelihood
397:
1.204 brouard 398: Revision 1.203 2015/09/30 17:45:14 brouard
399: Summary: looking at better estimation of the hessian
400:
401: Also a better criteria for convergence to the period prevalence And
402: therefore adding the number of years needed to converge. (The
403: prevalence in any alive state shold sum to one
404:
1.203 brouard 405: Revision 1.202 2015/09/22 19:45:16 brouard
406: Summary: Adding some overall graph on contribution to likelihood. Might change
407:
1.202 brouard 408: Revision 1.201 2015/09/15 17:34:58 brouard
409: Summary: 0.98r0
410:
411: - Some new graphs like suvival functions
412: - Some bugs fixed like model=1+age+V2.
413:
1.201 brouard 414: Revision 1.200 2015/09/09 16:53:55 brouard
415: Summary: Big bug thanks to Flavia
416:
417: Even model=1+age+V2. did not work anymore
418:
1.200 brouard 419: Revision 1.199 2015/09/07 14:09:23 brouard
420: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
421:
1.199 brouard 422: Revision 1.198 2015/09/03 07:14:39 brouard
423: Summary: 0.98q5 Flavia
424:
1.198 brouard 425: Revision 1.197 2015/09/01 18:24:39 brouard
426: *** empty log message ***
427:
1.197 brouard 428: Revision 1.196 2015/08/18 23:17:52 brouard
429: Summary: 0.98q5
430:
1.196 brouard 431: Revision 1.195 2015/08/18 16:28:39 brouard
432: Summary: Adding a hack for testing purpose
433:
434: After reading the title, ftol and model lines, if the comment line has
435: a q, starting with #q, the answer at the end of the run is quit. It
436: permits to run test files in batch with ctest. The former workaround was
437: $ echo q | imach foo.imach
438:
1.195 brouard 439: Revision 1.194 2015/08/18 13:32:00 brouard
440: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
441:
1.194 brouard 442: Revision 1.193 2015/08/04 07:17:42 brouard
443: Summary: 0.98q4
444:
1.193 brouard 445: Revision 1.192 2015/07/16 16:49:02 brouard
446: Summary: Fixing some outputs
447:
1.192 brouard 448: Revision 1.191 2015/07/14 10:00:33 brouard
449: Summary: Some fixes
450:
1.191 brouard 451: Revision 1.190 2015/05/05 08:51:13 brouard
452: Summary: Adding digits in output parameters (7 digits instead of 6)
453:
454: Fix 1+age+.
455:
1.190 brouard 456: Revision 1.189 2015/04/30 14:45:16 brouard
457: Summary: 0.98q2
458:
1.189 brouard 459: Revision 1.188 2015/04/30 08:27:53 brouard
460: *** empty log message ***
461:
1.188 brouard 462: Revision 1.187 2015/04/29 09:11:15 brouard
463: *** empty log message ***
464:
1.187 brouard 465: Revision 1.186 2015/04/23 12:01:52 brouard
466: Summary: V1*age is working now, version 0.98q1
467:
468: Some codes had been disabled in order to simplify and Vn*age was
469: working in the optimization phase, ie, giving correct MLE parameters,
470: but, as usual, outputs were not correct and program core dumped.
471:
1.186 brouard 472: Revision 1.185 2015/03/11 13:26:42 brouard
473: Summary: Inclusion of compile and links command line for Intel Compiler
474:
1.185 brouard 475: Revision 1.184 2015/03/11 11:52:39 brouard
476: Summary: Back from Windows 8. Intel Compiler
477:
1.184 brouard 478: Revision 1.183 2015/03/10 20:34:32 brouard
479: Summary: 0.98q0, trying with directest, mnbrak fixed
480:
481: We use directest instead of original Powell test; probably no
482: incidence on the results, but better justifications;
483: We fixed Numerical Recipes mnbrak routine which was wrong and gave
484: wrong results.
485:
1.183 brouard 486: Revision 1.182 2015/02/12 08:19:57 brouard
487: Summary: Trying to keep directest which seems simpler and more general
488: Author: Nicolas Brouard
489:
1.182 brouard 490: Revision 1.181 2015/02/11 23:22:24 brouard
491: Summary: Comments on Powell added
492:
493: Author:
494:
1.181 brouard 495: Revision 1.180 2015/02/11 17:33:45 brouard
496: Summary: Finishing move from main to function (hpijx and prevalence_limit)
497:
1.180 brouard 498: Revision 1.179 2015/01/04 09:57:06 brouard
499: Summary: back to OS/X
500:
1.179 brouard 501: Revision 1.178 2015/01/04 09:35:48 brouard
502: *** empty log message ***
503:
1.178 brouard 504: Revision 1.177 2015/01/03 18:40:56 brouard
505: Summary: Still testing ilc32 on OSX
506:
1.177 brouard 507: Revision 1.176 2015/01/03 16:45:04 brouard
508: *** empty log message ***
509:
1.176 brouard 510: Revision 1.175 2015/01/03 16:33:42 brouard
511: *** empty log message ***
512:
1.175 brouard 513: Revision 1.174 2015/01/03 16:15:49 brouard
514: Summary: Still in cross-compilation
515:
1.174 brouard 516: Revision 1.173 2015/01/03 12:06:26 brouard
517: Summary: trying to detect cross-compilation
518:
1.173 brouard 519: Revision 1.172 2014/12/27 12:07:47 brouard
520: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
521:
1.172 brouard 522: Revision 1.171 2014/12/23 13:26:59 brouard
523: Summary: Back from Visual C
524:
525: Still problem with utsname.h on Windows
526:
1.171 brouard 527: Revision 1.170 2014/12/23 11:17:12 brouard
528: Summary: Cleaning some \%% back to %%
529:
530: The escape was mandatory for a specific compiler (which one?), but too many warnings.
531:
1.170 brouard 532: Revision 1.169 2014/12/22 23:08:31 brouard
533: Summary: 0.98p
534:
535: Outputs some informations on compiler used, OS etc. Testing on different platforms.
536:
1.169 brouard 537: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 538: Summary: update
1.169 brouard 539:
1.168 brouard 540: Revision 1.167 2014/12/22 13:50:56 brouard
541: Summary: Testing uname and compiler version and if compiled 32 or 64
542:
543: Testing on Linux 64
544:
1.167 brouard 545: Revision 1.166 2014/12/22 11:40:47 brouard
546: *** empty log message ***
547:
1.166 brouard 548: Revision 1.165 2014/12/16 11:20:36 brouard
549: Summary: After compiling on Visual C
550:
551: * imach.c (Module): Merging 1.61 to 1.162
552:
1.165 brouard 553: Revision 1.164 2014/12/16 10:52:11 brouard
554: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
555:
556: * imach.c (Module): Merging 1.61 to 1.162
557:
1.164 brouard 558: Revision 1.163 2014/12/16 10:30:11 brouard
559: * imach.c (Module): Merging 1.61 to 1.162
560:
1.163 brouard 561: Revision 1.162 2014/09/25 11:43:39 brouard
562: Summary: temporary backup 0.99!
563:
1.162 brouard 564: Revision 1.1 2014/09/16 11:06:58 brouard
565: Summary: With some code (wrong) for nlopt
566:
567: Author:
568:
569: Revision 1.161 2014/09/15 20:41:41 brouard
570: Summary: Problem with macro SQR on Intel compiler
571:
1.161 brouard 572: Revision 1.160 2014/09/02 09:24:05 brouard
573: *** empty log message ***
574:
1.160 brouard 575: Revision 1.159 2014/09/01 10:34:10 brouard
576: Summary: WIN32
577: Author: Brouard
578:
1.159 brouard 579: Revision 1.158 2014/08/27 17:11:51 brouard
580: *** empty log message ***
581:
1.158 brouard 582: Revision 1.157 2014/08/27 16:26:55 brouard
583: Summary: Preparing windows Visual studio version
584: Author: Brouard
585:
586: In order to compile on Visual studio, time.h is now correct and time_t
587: and tm struct should be used. difftime should be used but sometimes I
588: just make the differences in raw time format (time(&now).
589: Trying to suppress #ifdef LINUX
590: Add xdg-open for __linux in order to open default browser.
591:
1.157 brouard 592: Revision 1.156 2014/08/25 20:10:10 brouard
593: *** empty log message ***
594:
1.156 brouard 595: Revision 1.155 2014/08/25 18:32:34 brouard
596: Summary: New compile, minor changes
597: Author: Brouard
598:
1.155 brouard 599: Revision 1.154 2014/06/20 17:32:08 brouard
600: Summary: Outputs now all graphs of convergence to period prevalence
601:
1.154 brouard 602: Revision 1.153 2014/06/20 16:45:46 brouard
603: Summary: If 3 live state, convergence to period prevalence on same graph
604: Author: Brouard
605:
1.153 brouard 606: Revision 1.152 2014/06/18 17:54:09 brouard
607: Summary: open browser, use gnuplot on same dir than imach if not found in the path
608:
1.152 brouard 609: Revision 1.151 2014/06/18 16:43:30 brouard
610: *** empty log message ***
611:
1.151 brouard 612: Revision 1.150 2014/06/18 16:42:35 brouard
613: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
614: Author: brouard
615:
1.150 brouard 616: Revision 1.149 2014/06/18 15:51:14 brouard
617: Summary: Some fixes in parameter files errors
618: Author: Nicolas Brouard
619:
1.149 brouard 620: Revision 1.148 2014/06/17 17:38:48 brouard
621: Summary: Nothing new
622: Author: Brouard
623:
624: Just a new packaging for OS/X version 0.98nS
625:
1.148 brouard 626: Revision 1.147 2014/06/16 10:33:11 brouard
627: *** empty log message ***
628:
1.147 brouard 629: Revision 1.146 2014/06/16 10:20:28 brouard
630: Summary: Merge
631: Author: Brouard
632:
633: Merge, before building revised version.
634:
1.146 brouard 635: Revision 1.145 2014/06/10 21:23:15 brouard
636: Summary: Debugging with valgrind
637: Author: Nicolas Brouard
638:
639: Lot of changes in order to output the results with some covariates
640: After the Edimburgh REVES conference 2014, it seems mandatory to
641: improve the code.
642: No more memory valgrind error but a lot has to be done in order to
643: continue the work of splitting the code into subroutines.
644: Also, decodemodel has been improved. Tricode is still not
645: optimal. nbcode should be improved. Documentation has been added in
646: the source code.
647:
1.144 brouard 648: Revision 1.143 2014/01/26 09:45:38 brouard
649: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
650:
651: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
652: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
653:
1.143 brouard 654: Revision 1.142 2014/01/26 03:57:36 brouard
655: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
656:
657: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
658:
1.142 brouard 659: Revision 1.141 2014/01/26 02:42:01 brouard
660: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
661:
1.141 brouard 662: Revision 1.140 2011/09/02 10:37:54 brouard
663: Summary: times.h is ok with mingw32 now.
664:
1.140 brouard 665: Revision 1.139 2010/06/14 07:50:17 brouard
666: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
667: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
668:
1.139 brouard 669: Revision 1.138 2010/04/30 18:19:40 brouard
670: *** empty log message ***
671:
1.138 brouard 672: Revision 1.137 2010/04/29 18:11:38 brouard
673: (Module): Checking covariates for more complex models
674: than V1+V2. A lot of change to be done. Unstable.
675:
1.137 brouard 676: Revision 1.136 2010/04/26 20:30:53 brouard
677: (Module): merging some libgsl code. Fixing computation
678: of likelione (using inter/intrapolation if mle = 0) in order to
679: get same likelihood as if mle=1.
680: Some cleaning of code and comments added.
681:
1.136 brouard 682: Revision 1.135 2009/10/29 15:33:14 brouard
683: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
684:
1.135 brouard 685: Revision 1.134 2009/10/29 13:18:53 brouard
686: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
687:
1.134 brouard 688: Revision 1.133 2009/07/06 10:21:25 brouard
689: just nforces
690:
1.133 brouard 691: Revision 1.132 2009/07/06 08:22:05 brouard
692: Many tings
693:
1.132 brouard 694: Revision 1.131 2009/06/20 16:22:47 brouard
695: Some dimensions resccaled
696:
1.131 brouard 697: Revision 1.130 2009/05/26 06:44:34 brouard
698: (Module): Max Covariate is now set to 20 instead of 8. A
699: lot of cleaning with variables initialized to 0. Trying to make
700: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
701:
1.130 brouard 702: Revision 1.129 2007/08/31 13:49:27 lievre
703: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
704:
1.129 lievre 705: Revision 1.128 2006/06/30 13:02:05 brouard
706: (Module): Clarifications on computing e.j
707:
1.128 brouard 708: Revision 1.127 2006/04/28 18:11:50 brouard
709: (Module): Yes the sum of survivors was wrong since
710: imach-114 because nhstepm was no more computed in the age
711: loop. Now we define nhstepma in the age loop.
712: (Module): In order to speed up (in case of numerous covariates) we
713: compute health expectancies (without variances) in a first step
714: and then all the health expectancies with variances or standard
715: deviation (needs data from the Hessian matrices) which slows the
716: computation.
717: In the future we should be able to stop the program is only health
718: expectancies and graph are needed without standard deviations.
719:
1.127 brouard 720: Revision 1.126 2006/04/28 17:23:28 brouard
721: (Module): Yes the sum of survivors was wrong since
722: imach-114 because nhstepm was no more computed in the age
723: loop. Now we define nhstepma in the age loop.
724: Version 0.98h
725:
1.126 brouard 726: Revision 1.125 2006/04/04 15:20:31 lievre
727: Errors in calculation of health expectancies. Age was not initialized.
728: Forecasting file added.
729:
730: Revision 1.124 2006/03/22 17:13:53 lievre
731: Parameters are printed with %lf instead of %f (more numbers after the comma).
732: The log-likelihood is printed in the log file
733:
734: Revision 1.123 2006/03/20 10:52:43 brouard
735: * imach.c (Module): <title> changed, corresponds to .htm file
736: name. <head> headers where missing.
737:
738: * imach.c (Module): Weights can have a decimal point as for
739: English (a comma might work with a correct LC_NUMERIC environment,
740: otherwise the weight is truncated).
741: Modification of warning when the covariates values are not 0 or
742: 1.
743: Version 0.98g
744:
745: Revision 1.122 2006/03/20 09:45:41 brouard
746: (Module): Weights can have a decimal point as for
747: English (a comma might work with a correct LC_NUMERIC environment,
748: otherwise the weight is truncated).
749: Modification of warning when the covariates values are not 0 or
750: 1.
751: Version 0.98g
752:
753: Revision 1.121 2006/03/16 17:45:01 lievre
754: * imach.c (Module): Comments concerning covariates added
755:
756: * imach.c (Module): refinements in the computation of lli if
757: status=-2 in order to have more reliable computation if stepm is
758: not 1 month. Version 0.98f
759:
760: Revision 1.120 2006/03/16 15:10:38 lievre
761: (Module): refinements in the computation of lli if
762: status=-2 in order to have more reliable computation if stepm is
763: not 1 month. Version 0.98f
764:
765: Revision 1.119 2006/03/15 17:42:26 brouard
766: (Module): Bug if status = -2, the loglikelihood was
767: computed as likelihood omitting the logarithm. Version O.98e
768:
769: Revision 1.118 2006/03/14 18:20:07 brouard
770: (Module): varevsij Comments added explaining the second
771: table of variances if popbased=1 .
772: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
773: (Module): Function pstamp added
774: (Module): Version 0.98d
775:
776: Revision 1.117 2006/03/14 17:16:22 brouard
777: (Module): varevsij Comments added explaining the second
778: table of variances if popbased=1 .
779: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
780: (Module): Function pstamp added
781: (Module): Version 0.98d
782:
783: Revision 1.116 2006/03/06 10:29:27 brouard
784: (Module): Variance-covariance wrong links and
785: varian-covariance of ej. is needed (Saito).
786:
787: Revision 1.115 2006/02/27 12:17:45 brouard
788: (Module): One freematrix added in mlikeli! 0.98c
789:
790: Revision 1.114 2006/02/26 12:57:58 brouard
791: (Module): Some improvements in processing parameter
792: filename with strsep.
793:
794: Revision 1.113 2006/02/24 14:20:24 brouard
795: (Module): Memory leaks checks with valgrind and:
796: datafile was not closed, some imatrix were not freed and on matrix
797: allocation too.
798:
799: Revision 1.112 2006/01/30 09:55:26 brouard
800: (Module): Back to gnuplot.exe instead of wgnuplot.exe
801:
802: Revision 1.111 2006/01/25 20:38:18 brouard
803: (Module): Lots of cleaning and bugs added (Gompertz)
804: (Module): Comments can be added in data file. Missing date values
805: can be a simple dot '.'.
806:
807: Revision 1.110 2006/01/25 00:51:50 brouard
808: (Module): Lots of cleaning and bugs added (Gompertz)
809:
810: Revision 1.109 2006/01/24 19:37:15 brouard
811: (Module): Comments (lines starting with a #) are allowed in data.
812:
813: Revision 1.108 2006/01/19 18:05:42 lievre
814: Gnuplot problem appeared...
815: To be fixed
816:
817: Revision 1.107 2006/01/19 16:20:37 brouard
818: Test existence of gnuplot in imach path
819:
820: Revision 1.106 2006/01/19 13:24:36 brouard
821: Some cleaning and links added in html output
822:
823: Revision 1.105 2006/01/05 20:23:19 lievre
824: *** empty log message ***
825:
826: Revision 1.104 2005/09/30 16:11:43 lievre
827: (Module): sump fixed, loop imx fixed, and simplifications.
828: (Module): If the status is missing at the last wave but we know
829: that the person is alive, then we can code his/her status as -2
830: (instead of missing=-1 in earlier versions) and his/her
831: contributions to the likelihood is 1 - Prob of dying from last
832: health status (= 1-p13= p11+p12 in the easiest case of somebody in
833: the healthy state at last known wave). Version is 0.98
834:
835: Revision 1.103 2005/09/30 15:54:49 lievre
836: (Module): sump fixed, loop imx fixed, and simplifications.
837:
838: Revision 1.102 2004/09/15 17:31:30 brouard
839: Add the possibility to read data file including tab characters.
840:
841: Revision 1.101 2004/09/15 10:38:38 brouard
842: Fix on curr_time
843:
844: Revision 1.100 2004/07/12 18:29:06 brouard
845: Add version for Mac OS X. Just define UNIX in Makefile
846:
847: Revision 1.99 2004/06/05 08:57:40 brouard
848: *** empty log message ***
849:
850: Revision 1.98 2004/05/16 15:05:56 brouard
851: New version 0.97 . First attempt to estimate force of mortality
852: directly from the data i.e. without the need of knowing the health
853: state at each age, but using a Gompertz model: log u =a + b*age .
854: This is the basic analysis of mortality and should be done before any
855: other analysis, in order to test if the mortality estimated from the
856: cross-longitudinal survey is different from the mortality estimated
857: from other sources like vital statistic data.
858:
859: The same imach parameter file can be used but the option for mle should be -3.
860:
1.133 brouard 861: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 862: former routines in order to include the new code within the former code.
863:
864: The output is very simple: only an estimate of the intercept and of
865: the slope with 95% confident intervals.
866:
867: Current limitations:
868: A) Even if you enter covariates, i.e. with the
869: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
870: B) There is no computation of Life Expectancy nor Life Table.
871:
872: Revision 1.97 2004/02/20 13:25:42 lievre
873: Version 0.96d. Population forecasting command line is (temporarily)
874: suppressed.
875:
876: Revision 1.96 2003/07/15 15:38:55 brouard
877: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
878: rewritten within the same printf. Workaround: many printfs.
879:
880: Revision 1.95 2003/07/08 07:54:34 brouard
881: * imach.c (Repository):
882: (Repository): Using imachwizard code to output a more meaningful covariance
883: matrix (cov(a12,c31) instead of numbers.
884:
885: Revision 1.94 2003/06/27 13:00:02 brouard
886: Just cleaning
887:
888: Revision 1.93 2003/06/25 16:33:55 brouard
889: (Module): On windows (cygwin) function asctime_r doesn't
890: exist so I changed back to asctime which exists.
891: (Module): Version 0.96b
892:
893: Revision 1.92 2003/06/25 16:30:45 brouard
894: (Module): On windows (cygwin) function asctime_r doesn't
895: exist so I changed back to asctime which exists.
896:
897: Revision 1.91 2003/06/25 15:30:29 brouard
898: * imach.c (Repository): Duplicated warning errors corrected.
899: (Repository): Elapsed time after each iteration is now output. It
900: helps to forecast when convergence will be reached. Elapsed time
901: is stamped in powell. We created a new html file for the graphs
902: concerning matrix of covariance. It has extension -cov.htm.
903:
904: Revision 1.90 2003/06/24 12:34:15 brouard
905: (Module): Some bugs corrected for windows. Also, when
906: mle=-1 a template is output in file "or"mypar.txt with the design
907: of the covariance matrix to be input.
908:
909: Revision 1.89 2003/06/24 12:30:52 brouard
910: (Module): Some bugs corrected for windows. Also, when
911: mle=-1 a template is output in file "or"mypar.txt with the design
912: of the covariance matrix to be input.
913:
914: Revision 1.88 2003/06/23 17:54:56 brouard
915: * 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.
916:
917: Revision 1.87 2003/06/18 12:26:01 brouard
918: Version 0.96
919:
920: Revision 1.86 2003/06/17 20:04:08 brouard
921: (Module): Change position of html and gnuplot routines and added
922: routine fileappend.
923:
924: Revision 1.85 2003/06/17 13:12:43 brouard
925: * imach.c (Repository): Check when date of death was earlier that
926: current date of interview. It may happen when the death was just
927: prior to the death. In this case, dh was negative and likelihood
928: was wrong (infinity). We still send an "Error" but patch by
929: assuming that the date of death was just one stepm after the
930: interview.
931: (Repository): Because some people have very long ID (first column)
932: we changed int to long in num[] and we added a new lvector for
933: memory allocation. But we also truncated to 8 characters (left
934: truncation)
935: (Repository): No more line truncation errors.
936:
937: Revision 1.84 2003/06/13 21:44:43 brouard
938: * imach.c (Repository): Replace "freqsummary" at a correct
939: place. It differs from routine "prevalence" which may be called
940: many times. Probs is memory consuming and must be used with
941: parcimony.
942: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
943:
944: Revision 1.83 2003/06/10 13:39:11 lievre
945: *** empty log message ***
946:
947: Revision 1.82 2003/06/05 15:57:20 brouard
948: Add log in imach.c and fullversion number is now printed.
949:
950: */
951: /*
952: Interpolated Markov Chain
953:
954: Short summary of the programme:
955:
1.227 brouard 956: This program computes Healthy Life Expectancies or State-specific
957: (if states aren't health statuses) Expectancies from
958: cross-longitudinal data. Cross-longitudinal data consist in:
959:
960: -1- a first survey ("cross") where individuals from different ages
961: are interviewed on their health status or degree of disability (in
962: the case of a health survey which is our main interest)
963:
964: -2- at least a second wave of interviews ("longitudinal") which
965: measure each change (if any) in individual health status. Health
966: expectancies are computed from the time spent in each health state
967: according to a model. More health states you consider, more time is
968: necessary to reach the Maximum Likelihood of the parameters involved
969: in the model. The simplest model is the multinomial logistic model
970: where pij is the probability to be observed in state j at the second
971: wave conditional to be observed in state i at the first
972: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
973: etc , where 'age' is age and 'sex' is a covariate. If you want to
974: have a more complex model than "constant and age", you should modify
975: the program where the markup *Covariates have to be included here
976: again* invites you to do it. More covariates you add, slower the
1.126 brouard 977: convergence.
978:
979: The advantage of this computer programme, compared to a simple
980: multinomial logistic model, is clear when the delay between waves is not
981: identical for each individual. Also, if a individual missed an
982: intermediate interview, the information is lost, but taken into
983: account using an interpolation or extrapolation.
984:
985: hPijx is the probability to be observed in state i at age x+h
986: conditional to the observed state i at age x. The delay 'h' can be
987: split into an exact number (nh*stepm) of unobserved intermediate
988: states. This elementary transition (by month, quarter,
989: semester or year) is modelled as a multinomial logistic. The hPx
990: matrix is simply the matrix product of nh*stepm elementary matrices
991: and the contribution of each individual to the likelihood is simply
992: hPijx.
993:
994: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 995: of the life expectancies. It also computes the period (stable) prevalence.
996:
997: Back prevalence and projections:
1.227 brouard 998:
999: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1000: double agemaxpar, double ftolpl, int *ncvyearp, double
1001: dateprev1,double dateprev2, int firstpass, int lastpass, int
1002: mobilavproj)
1003:
1004: Computes the back prevalence limit for any combination of
1005: covariate values k at any age between ageminpar and agemaxpar and
1006: returns it in **bprlim. In the loops,
1007:
1008: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1009: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1010:
1011: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1012: Computes for any combination of covariates k and any age between bage and fage
1013: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1014: oldm=oldms;savm=savms;
1.227 brouard 1015:
1.267 brouard 1016: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1017: Computes the transition matrix starting at age 'age' over
1018: 'nhstepm*hstepm*stepm' months (i.e. until
1019: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1020: nhstepm*hstepm matrices.
1021:
1022: Returns p3mat[i][j][h] after calling
1023: p3mat[i][j][h]=matprod2(newm,
1024: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1025: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1026: oldm);
1.226 brouard 1027:
1028: Important routines
1029:
1030: - func (or funcone), computes logit (pij) distinguishing
1031: o fixed variables (single or product dummies or quantitative);
1032: o varying variables by:
1033: (1) wave (single, product dummies, quantitative),
1034: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1035: % fixed dummy (treated) or quantitative (not done because time-consuming);
1036: % varying dummy (not done) or quantitative (not done);
1037: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1038: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1039: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1040: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1041: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1042:
1.226 brouard 1043:
1044:
1.133 brouard 1045: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1046: Institut national d'études démographiques, Paris.
1.126 brouard 1047: This software have been partly granted by Euro-REVES, a concerted action
1048: from the European Union.
1049: It is copyrighted identically to a GNU software product, ie programme and
1050: software can be distributed freely for non commercial use. Latest version
1051: can be accessed at http://euroreves.ined.fr/imach .
1052:
1053: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1054: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1055:
1056: **********************************************************************/
1057: /*
1058: main
1059: read parameterfile
1060: read datafile
1061: concatwav
1062: freqsummary
1063: if (mle >= 1)
1064: mlikeli
1065: print results files
1066: if mle==1
1067: computes hessian
1068: read end of parameter file: agemin, agemax, bage, fage, estepm
1069: begin-prev-date,...
1070: open gnuplot file
1071: open html file
1.145 brouard 1072: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1073: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1074: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1075: freexexit2 possible for memory heap.
1076:
1077: h Pij x | pij_nom ficrestpij
1078: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1079: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1080: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1081:
1082: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1083: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1084: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1085: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1086: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1087:
1.126 brouard 1088: forecasting if prevfcast==1 prevforecast call prevalence()
1089: health expectancies
1090: Variance-covariance of DFLE
1091: prevalence()
1092: movingaverage()
1093: varevsij()
1094: if popbased==1 varevsij(,popbased)
1095: total life expectancies
1096: Variance of period (stable) prevalence
1097: end
1098: */
1099:
1.187 brouard 1100: /* #define DEBUG */
1101: /* #define DEBUGBRENT */
1.203 brouard 1102: /* #define DEBUGLINMIN */
1103: /* #define DEBUGHESS */
1104: #define DEBUGHESSIJ
1.224 brouard 1105: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1106: #define POWELL /* Instead of NLOPT */
1.224 brouard 1107: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1108: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1109: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1110: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1111:
1112: #include <math.h>
1113: #include <stdio.h>
1114: #include <stdlib.h>
1115: #include <string.h>
1.226 brouard 1116: #include <ctype.h>
1.159 brouard 1117:
1118: #ifdef _WIN32
1119: #include <io.h>
1.172 brouard 1120: #include <windows.h>
1121: #include <tchar.h>
1.159 brouard 1122: #else
1.126 brouard 1123: #include <unistd.h>
1.159 brouard 1124: #endif
1.126 brouard 1125:
1126: #include <limits.h>
1127: #include <sys/types.h>
1.171 brouard 1128:
1129: #if defined(__GNUC__)
1130: #include <sys/utsname.h> /* Doesn't work on Windows */
1131: #endif
1132:
1.126 brouard 1133: #include <sys/stat.h>
1134: #include <errno.h>
1.159 brouard 1135: /* extern int errno; */
1.126 brouard 1136:
1.157 brouard 1137: /* #ifdef LINUX */
1138: /* #include <time.h> */
1139: /* #include "timeval.h" */
1140: /* #else */
1141: /* #include <sys/time.h> */
1142: /* #endif */
1143:
1.126 brouard 1144: #include <time.h>
1145:
1.136 brouard 1146: #ifdef GSL
1147: #include <gsl/gsl_errno.h>
1148: #include <gsl/gsl_multimin.h>
1149: #endif
1150:
1.167 brouard 1151:
1.162 brouard 1152: #ifdef NLOPT
1153: #include <nlopt.h>
1154: typedef struct {
1155: double (* function)(double [] );
1156: } myfunc_data ;
1157: #endif
1158:
1.126 brouard 1159: /* #include <libintl.h> */
1160: /* #define _(String) gettext (String) */
1161:
1.251 brouard 1162: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1163:
1164: #define GNUPLOTPROGRAM "gnuplot"
1165: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1166: #define FILENAMELENGTH 132
1167:
1168: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1169: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1170:
1.144 brouard 1171: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1172: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1173:
1174: #define NINTERVMAX 8
1.144 brouard 1175: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1176: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.318 brouard 1177: #define NCOVMAX 30 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 1178: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1179: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1180: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1181: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1182: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1183: /* #define AGESUP 130 */
1.288 brouard 1184: /* #define AGESUP 150 */
1185: #define AGESUP 200
1.268 brouard 1186: #define AGEINF 0
1.218 brouard 1187: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1188: #define AGEBASE 40
1.194 brouard 1189: #define AGEOVERFLOW 1.e20
1.164 brouard 1190: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1191: #ifdef _WIN32
1192: #define DIRSEPARATOR '\\'
1193: #define CHARSEPARATOR "\\"
1194: #define ODIRSEPARATOR '/'
1195: #else
1.126 brouard 1196: #define DIRSEPARATOR '/'
1197: #define CHARSEPARATOR "/"
1198: #define ODIRSEPARATOR '\\'
1199: #endif
1200:
1.321 ! brouard 1201: /* $Id: imach.c,v 1.320 2022/06/02 05:10:11 brouard Exp $ */
1.126 brouard 1202: /* $State: Exp $ */
1.196 brouard 1203: #include "version.h"
1204: char version[]=__IMACH_VERSION__;
1.316 brouard 1205: char copyright[]="May 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";
1.321 ! brouard 1206: char fullversion[]="$Revision: 1.320 $ $Date: 2022/06/02 05:10:11 $";
1.126 brouard 1207: char strstart[80];
1208: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1209: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1210: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1211: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1212: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1213: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1214: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1215: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1216: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1217: int cptcovprodnoage=0; /**< Number of covariate products without age */
1218: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1219: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1220: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1221: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1222: int nsd=0; /**< Total number of single dummy variables (output) */
1223: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1224: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1225: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1226: int ntveff=0; /**< ntveff number of effective time varying variables */
1227: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1228: int cptcov=0; /* Working variable */
1.290 brouard 1229: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1230: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1231: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1232: int nlstate=2; /* Number of live states */
1233: int ndeath=1; /* Number of dead states */
1.130 brouard 1234: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1235: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1236: int popbased=0;
1237:
1238: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1239: int maxwav=0; /* Maxim number of waves */
1240: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1241: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1242: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1243: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1244: int mle=1, weightopt=0;
1.126 brouard 1245: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1246: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1247: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1248: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1249: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1250: int selected(int kvar); /* Is covariate kvar selected for printing results */
1251:
1.130 brouard 1252: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1253: double **matprod2(); /* test */
1.126 brouard 1254: double **oldm, **newm, **savm; /* Working pointers to matrices */
1255: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1256: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1257:
1.136 brouard 1258: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1259: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1260: FILE *ficlog, *ficrespow;
1.130 brouard 1261: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1262: double fretone; /* Only one call to likelihood */
1.130 brouard 1263: long ipmx=0; /* Number of contributions */
1.126 brouard 1264: double sw; /* Sum of weights */
1265: char filerespow[FILENAMELENGTH];
1266: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1267: FILE *ficresilk;
1268: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1269: FILE *ficresprobmorprev;
1270: FILE *fichtm, *fichtmcov; /* Html File */
1271: FILE *ficreseij;
1272: char filerese[FILENAMELENGTH];
1273: FILE *ficresstdeij;
1274: char fileresstde[FILENAMELENGTH];
1275: FILE *ficrescveij;
1276: char filerescve[FILENAMELENGTH];
1277: FILE *ficresvij;
1278: char fileresv[FILENAMELENGTH];
1.269 brouard 1279:
1.126 brouard 1280: char title[MAXLINE];
1.234 brouard 1281: char model[MAXLINE]; /**< The model line */
1.217 brouard 1282: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1283: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1284: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1285: char command[FILENAMELENGTH];
1286: int outcmd=0;
1287:
1.217 brouard 1288: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1289: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1290: char filelog[FILENAMELENGTH]; /* Log file */
1291: char filerest[FILENAMELENGTH];
1292: char fileregp[FILENAMELENGTH];
1293: char popfile[FILENAMELENGTH];
1294:
1295: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1296:
1.157 brouard 1297: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1298: /* struct timezone tzp; */
1299: /* extern int gettimeofday(); */
1300: struct tm tml, *gmtime(), *localtime();
1301:
1302: extern time_t time();
1303:
1304: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1305: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1306: struct tm tm;
1307:
1.126 brouard 1308: char strcurr[80], strfor[80];
1309:
1310: char *endptr;
1311: long lval;
1312: double dval;
1313:
1314: #define NR_END 1
1315: #define FREE_ARG char*
1316: #define FTOL 1.0e-10
1317:
1318: #define NRANSI
1.240 brouard 1319: #define ITMAX 200
1320: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1321:
1322: #define TOL 2.0e-4
1323:
1324: #define CGOLD 0.3819660
1325: #define ZEPS 1.0e-10
1326: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1327:
1328: #define GOLD 1.618034
1329: #define GLIMIT 100.0
1330: #define TINY 1.0e-20
1331:
1332: static double maxarg1,maxarg2;
1333: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1334: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1335:
1336: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1337: #define rint(a) floor(a+0.5)
1.166 brouard 1338: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1339: #define mytinydouble 1.0e-16
1.166 brouard 1340: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1341: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1342: /* static double dsqrarg; */
1343: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1344: static double sqrarg;
1345: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1346: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1347: int agegomp= AGEGOMP;
1348:
1349: int imx;
1350: int stepm=1;
1351: /* Stepm, step in month: minimum step interpolation*/
1352:
1353: int estepm;
1354: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1355:
1356: int m,nb;
1357: long *num;
1.197 brouard 1358: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1359: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1360: covariate for which somebody answered excluding
1361: undefined. Usually 2: 0 and 1. */
1362: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1363: covariate for which somebody answered including
1364: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1365: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1366: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1367: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1368: double *ageexmed,*agecens;
1369: double dateintmean=0;
1.296 brouard 1370: double anprojd, mprojd, jprojd; /* For eventual projections */
1371: double anprojf, mprojf, jprojf;
1.126 brouard 1372:
1.296 brouard 1373: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1374: double anbackf, mbackf, jbackf;
1375: double jintmean,mintmean,aintmean;
1.126 brouard 1376: double *weight;
1377: int **s; /* Status */
1.141 brouard 1378: double *agedc;
1.145 brouard 1379: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1380: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1381: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1382: double **coqvar; /* Fixed quantitative covariate nqv */
1383: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1384: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1385: double idx;
1386: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1387: /* Some documentation */
1388: /* Design original data
1389: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1390: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1391: * ntv=3 nqtv=1
1392: * cptcovn number of covariates (not including constant and age) = # of + plus 1 = 10+1=11
1393: * For time varying covariate, quanti or dummies
1394: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1395: * cotvar[wav][ntv+iv][i]= [3+(1 to nqtv)][i]=(V12) quanti
1396: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1397: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1398: * covar[k,i], value of kth fixed covariate dummy or quanti :
1399: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1400: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1401: * k= 1 2 3 4 5 6 7 8 9 10 11
1402: */
1403: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1404: /* 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
1405: # States 1=Coresidence, 2 Living alone, 3 Institution
1406: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1407: */
1.319 brouard 1408: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1409: /* k 1 2 3 4 5 6 7 8 9 */
1410: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 *//*0 for simple covariate (dummy, quantitative,*/
1411: /* fixed or varying), 1 for age product, 2 for*/
1412: /* product */
1413: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1414: /*(single or product without age), 2 dummy*/
1415: /* with age product, 3 quant with age product*/
1416: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1417: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1418: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1419: /*TvarsDind[k] 2 3 9 */ /* position K of single dummy cova */
1420: /* nsq 1 2 */ /* Counting single quantit tv */
1421: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1422: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1423: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1424: /* cptcovage 1 2 */ /* Counting cov*age in the model equation */
1425: /* Tage[cptcovage]=k 5 8 */ /* Position in the model of ith cov*age */
1426: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1427: /* 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 1428: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1429: /* Type */
1430: /* V 1 2 3 4 5 */
1431: /* F F V V V */
1432: /* D Q D D Q */
1433: /* */
1434: int *TvarsD;
1435: int *TvarsDind;
1436: int *TvarsQ;
1437: int *TvarsQind;
1438:
1.318 brouard 1439: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1440: int nresult=0;
1.258 brouard 1441: int parameterline=0; /* # of the parameter (type) line */
1.318 brouard 1442: int TKresult[MAXRESULTLINESPONE];
1443: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */
1444: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */
1445: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For dummy variable , variable # (output) */
1446: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1447: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1448: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , variable # (output) */
1449:
1450: /* 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
1451: # States 1=Coresidence, 2 Living alone, 3 Institution
1452: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1453: */
1.234 brouard 1454: /* 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 1455: 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 */
1456: 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 */
1457: 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 */
1458: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1459: 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 */
1460: 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 1461: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1462: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1463: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1464: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1465: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1466: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1467: 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 */
1468: 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 */
1469:
1.230 brouard 1470: int *Tvarsel; /**< Selected covariates for output */
1471: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1472: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1473: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1474: 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 1475: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1476: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1477: int *Tage;
1.227 brouard 1478: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1479: 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 1480: 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*/
1481: 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 1482: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1483: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1484: int **Tvard;
1485: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1486: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1487: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1488: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1489: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1490: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1491: double *lsurv, *lpop, *tpop;
1492:
1.231 brouard 1493: #define FD 1; /* Fixed dummy covariate */
1494: #define FQ 2; /* Fixed quantitative covariate */
1495: #define FP 3; /* Fixed product covariate */
1496: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1497: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1498: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1499: #define VD 10; /* Varying dummy covariate */
1500: #define VQ 11; /* Varying quantitative covariate */
1501: #define VP 12; /* Varying product covariate */
1502: #define VPDD 13; /* Varying product dummy*dummy covariate */
1503: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1504: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1505: #define APFD 16; /* Age product * fixed dummy covariate */
1506: #define APFQ 17; /* Age product * fixed quantitative covariate */
1507: #define APVD 18; /* Age product * varying dummy covariate */
1508: #define APVQ 19; /* Age product * varying quantitative covariate */
1509:
1510: #define FTYPE 1; /* Fixed covariate */
1511: #define VTYPE 2; /* Varying covariate (loop in wave) */
1512: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1513:
1514: struct kmodel{
1515: int maintype; /* main type */
1516: int subtype; /* subtype */
1517: };
1518: struct kmodel modell[NCOVMAX];
1519:
1.143 brouard 1520: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1521: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1522:
1523: /**************** split *************************/
1524: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1525: {
1526: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1527: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1528: */
1529: char *ss; /* pointer */
1.186 brouard 1530: int l1=0, l2=0; /* length counters */
1.126 brouard 1531:
1532: l1 = strlen(path ); /* length of path */
1533: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1534: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1535: if ( ss == NULL ) { /* no directory, so determine current directory */
1536: strcpy( name, path ); /* we got the fullname name because no directory */
1537: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1538: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1539: /* get current working directory */
1540: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1541: #ifdef WIN32
1542: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1543: #else
1544: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1545: #endif
1.126 brouard 1546: return( GLOCK_ERROR_GETCWD );
1547: }
1548: /* got dirc from getcwd*/
1549: printf(" DIRC = %s \n",dirc);
1.205 brouard 1550: } else { /* strip directory from path */
1.126 brouard 1551: ss++; /* after this, the filename */
1552: l2 = strlen( ss ); /* length of filename */
1553: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1554: strcpy( name, ss ); /* save file name */
1555: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1556: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1557: printf(" DIRC2 = %s \n",dirc);
1558: }
1559: /* We add a separator at the end of dirc if not exists */
1560: l1 = strlen( dirc ); /* length of directory */
1561: if( dirc[l1-1] != DIRSEPARATOR ){
1562: dirc[l1] = DIRSEPARATOR;
1563: dirc[l1+1] = 0;
1564: printf(" DIRC3 = %s \n",dirc);
1565: }
1566: ss = strrchr( name, '.' ); /* find last / */
1567: if (ss >0){
1568: ss++;
1569: strcpy(ext,ss); /* save extension */
1570: l1= strlen( name);
1571: l2= strlen(ss)+1;
1572: strncpy( finame, name, l1-l2);
1573: finame[l1-l2]= 0;
1574: }
1575:
1576: return( 0 ); /* we're done */
1577: }
1578:
1579:
1580: /******************************************/
1581:
1582: void replace_back_to_slash(char *s, char*t)
1583: {
1584: int i;
1585: int lg=0;
1586: i=0;
1587: lg=strlen(t);
1588: for(i=0; i<= lg; i++) {
1589: (s[i] = t[i]);
1590: if (t[i]== '\\') s[i]='/';
1591: }
1592: }
1593:
1.132 brouard 1594: char *trimbb(char *out, char *in)
1.137 brouard 1595: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1596: char *s;
1597: s=out;
1598: while (*in != '\0'){
1.137 brouard 1599: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1600: in++;
1601: }
1602: *out++ = *in++;
1603: }
1604: *out='\0';
1605: return s;
1606: }
1607:
1.187 brouard 1608: /* char *substrchaine(char *out, char *in, char *chain) */
1609: /* { */
1610: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1611: /* char *s, *t; */
1612: /* t=in;s=out; */
1613: /* while ((*in != *chain) && (*in != '\0')){ */
1614: /* *out++ = *in++; */
1615: /* } */
1616:
1617: /* /\* *in matches *chain *\/ */
1618: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1619: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1620: /* } */
1621: /* in--; chain--; */
1622: /* while ( (*in != '\0')){ */
1623: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1624: /* *out++ = *in++; */
1625: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1626: /* } */
1627: /* *out='\0'; */
1628: /* out=s; */
1629: /* return out; */
1630: /* } */
1631: char *substrchaine(char *out, char *in, char *chain)
1632: {
1633: /* Substract chain 'chain' from 'in', return and output 'out' */
1634: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1635:
1636: char *strloc;
1637:
1638: strcpy (out, in);
1639: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1640: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1641: if(strloc != NULL){
1642: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1643: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1644: /* strcpy (strloc, strloc +strlen(chain));*/
1645: }
1646: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1647: return out;
1648: }
1649:
1650:
1.145 brouard 1651: char *cutl(char *blocc, char *alocc, char *in, char occ)
1652: {
1.187 brouard 1653: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1654: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1655: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1656: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1657: */
1.160 brouard 1658: char *s, *t;
1.145 brouard 1659: t=in;s=in;
1660: while ((*in != occ) && (*in != '\0')){
1661: *alocc++ = *in++;
1662: }
1663: if( *in == occ){
1664: *(alocc)='\0';
1665: s=++in;
1666: }
1667:
1668: if (s == t) {/* occ not found */
1669: *(alocc-(in-s))='\0';
1670: in=s;
1671: }
1672: while ( *in != '\0'){
1673: *blocc++ = *in++;
1674: }
1675:
1676: *blocc='\0';
1677: return t;
1678: }
1.137 brouard 1679: char *cutv(char *blocc, char *alocc, char *in, char occ)
1680: {
1.187 brouard 1681: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1682: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1683: gives blocc="abcdef2ghi" and alocc="j".
1684: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1685: */
1686: char *s, *t;
1687: t=in;s=in;
1688: while (*in != '\0'){
1689: while( *in == occ){
1690: *blocc++ = *in++;
1691: s=in;
1692: }
1693: *blocc++ = *in++;
1694: }
1695: if (s == t) /* occ not found */
1696: *(blocc-(in-s))='\0';
1697: else
1698: *(blocc-(in-s)-1)='\0';
1699: in=s;
1700: while ( *in != '\0'){
1701: *alocc++ = *in++;
1702: }
1703:
1704: *alocc='\0';
1705: return s;
1706: }
1707:
1.126 brouard 1708: int nbocc(char *s, char occ)
1709: {
1710: int i,j=0;
1711: int lg=20;
1712: i=0;
1713: lg=strlen(s);
1714: for(i=0; i<= lg; i++) {
1.234 brouard 1715: if (s[i] == occ ) j++;
1.126 brouard 1716: }
1717: return j;
1718: }
1719:
1.137 brouard 1720: /* void cutv(char *u,char *v, char*t, char occ) */
1721: /* { */
1722: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1723: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1724: /* gives u="abcdef2ghi" and v="j" *\/ */
1725: /* int i,lg,j,p=0; */
1726: /* i=0; */
1727: /* lg=strlen(t); */
1728: /* for(j=0; j<=lg-1; j++) { */
1729: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1730: /* } */
1.126 brouard 1731:
1.137 brouard 1732: /* for(j=0; j<p; j++) { */
1733: /* (u[j] = t[j]); */
1734: /* } */
1735: /* u[p]='\0'; */
1.126 brouard 1736:
1.137 brouard 1737: /* for(j=0; j<= lg; j++) { */
1738: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1739: /* } */
1740: /* } */
1.126 brouard 1741:
1.160 brouard 1742: #ifdef _WIN32
1743: char * strsep(char **pp, const char *delim)
1744: {
1745: char *p, *q;
1746:
1747: if ((p = *pp) == NULL)
1748: return 0;
1749: if ((q = strpbrk (p, delim)) != NULL)
1750: {
1751: *pp = q + 1;
1752: *q = '\0';
1753: }
1754: else
1755: *pp = 0;
1756: return p;
1757: }
1758: #endif
1759:
1.126 brouard 1760: /********************** nrerror ********************/
1761:
1762: void nrerror(char error_text[])
1763: {
1764: fprintf(stderr,"ERREUR ...\n");
1765: fprintf(stderr,"%s\n",error_text);
1766: exit(EXIT_FAILURE);
1767: }
1768: /*********************** vector *******************/
1769: double *vector(int nl, int nh)
1770: {
1771: double *v;
1772: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1773: if (!v) nrerror("allocation failure in vector");
1774: return v-nl+NR_END;
1775: }
1776:
1777: /************************ free vector ******************/
1778: void free_vector(double*v, int nl, int nh)
1779: {
1780: free((FREE_ARG)(v+nl-NR_END));
1781: }
1782:
1783: /************************ivector *******************************/
1784: int *ivector(long nl,long nh)
1785: {
1786: int *v;
1787: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1788: if (!v) nrerror("allocation failure in ivector");
1789: return v-nl+NR_END;
1790: }
1791:
1792: /******************free ivector **************************/
1793: void free_ivector(int *v, long nl, long nh)
1794: {
1795: free((FREE_ARG)(v+nl-NR_END));
1796: }
1797:
1798: /************************lvector *******************************/
1799: long *lvector(long nl,long nh)
1800: {
1801: long *v;
1802: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1803: if (!v) nrerror("allocation failure in ivector");
1804: return v-nl+NR_END;
1805: }
1806:
1807: /******************free lvector **************************/
1808: void free_lvector(long *v, long nl, long nh)
1809: {
1810: free((FREE_ARG)(v+nl-NR_END));
1811: }
1812:
1813: /******************* imatrix *******************************/
1814: int **imatrix(long nrl, long nrh, long ncl, long nch)
1815: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1816: {
1817: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1818: int **m;
1819:
1820: /* allocate pointers to rows */
1821: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1822: if (!m) nrerror("allocation failure 1 in matrix()");
1823: m += NR_END;
1824: m -= nrl;
1825:
1826:
1827: /* allocate rows and set pointers to them */
1828: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1829: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1830: m[nrl] += NR_END;
1831: m[nrl] -= ncl;
1832:
1833: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1834:
1835: /* return pointer to array of pointers to rows */
1836: return m;
1837: }
1838:
1839: /****************** free_imatrix *************************/
1840: void free_imatrix(m,nrl,nrh,ncl,nch)
1841: int **m;
1842: long nch,ncl,nrh,nrl;
1843: /* free an int matrix allocated by imatrix() */
1844: {
1845: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1846: free((FREE_ARG) (m+nrl-NR_END));
1847: }
1848:
1849: /******************* matrix *******************************/
1850: double **matrix(long nrl, long nrh, long ncl, long nch)
1851: {
1852: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1853: double **m;
1854:
1855: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1856: if (!m) nrerror("allocation failure 1 in matrix()");
1857: m += NR_END;
1858: m -= nrl;
1859:
1860: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1861: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1862: m[nrl] += NR_END;
1863: m[nrl] -= ncl;
1864:
1865: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1866: return m;
1.145 brouard 1867: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1868: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1869: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1870: */
1871: }
1872:
1873: /*************************free matrix ************************/
1874: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1875: {
1876: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1877: free((FREE_ARG)(m+nrl-NR_END));
1878: }
1879:
1880: /******************* ma3x *******************************/
1881: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1882: {
1883: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1884: double ***m;
1885:
1886: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1887: if (!m) nrerror("allocation failure 1 in matrix()");
1888: m += NR_END;
1889: m -= nrl;
1890:
1891: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1892: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1893: m[nrl] += NR_END;
1894: m[nrl] -= ncl;
1895:
1896: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1897:
1898: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1899: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1900: m[nrl][ncl] += NR_END;
1901: m[nrl][ncl] -= nll;
1902: for (j=ncl+1; j<=nch; j++)
1903: m[nrl][j]=m[nrl][j-1]+nlay;
1904:
1905: for (i=nrl+1; i<=nrh; i++) {
1906: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1907: for (j=ncl+1; j<=nch; j++)
1908: m[i][j]=m[i][j-1]+nlay;
1909: }
1910: return m;
1911: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1912: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1913: */
1914: }
1915:
1916: /*************************free ma3x ************************/
1917: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1918: {
1919: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1920: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1921: free((FREE_ARG)(m+nrl-NR_END));
1922: }
1923:
1924: /*************** function subdirf ***********/
1925: char *subdirf(char fileres[])
1926: {
1927: /* Caution optionfilefiname is hidden */
1928: strcpy(tmpout,optionfilefiname);
1929: strcat(tmpout,"/"); /* Add to the right */
1930: strcat(tmpout,fileres);
1931: return tmpout;
1932: }
1933:
1934: /*************** function subdirf2 ***********/
1935: char *subdirf2(char fileres[], char *preop)
1936: {
1.314 brouard 1937: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
1938: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 1939: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 1940: /* Caution optionfilefiname is hidden */
1941: strcpy(tmpout,optionfilefiname);
1942: strcat(tmpout,"/");
1943: strcat(tmpout,preop);
1944: strcat(tmpout,fileres);
1945: return tmpout;
1946: }
1947:
1948: /*************** function subdirf3 ***********/
1949: char *subdirf3(char fileres[], char *preop, char *preop2)
1950: {
1951:
1952: /* Caution optionfilefiname is hidden */
1953: strcpy(tmpout,optionfilefiname);
1954: strcat(tmpout,"/");
1955: strcat(tmpout,preop);
1956: strcat(tmpout,preop2);
1957: strcat(tmpout,fileres);
1958: return tmpout;
1959: }
1.213 brouard 1960:
1961: /*************** function subdirfext ***********/
1962: char *subdirfext(char fileres[], char *preop, char *postop)
1963: {
1964:
1965: strcpy(tmpout,preop);
1966: strcat(tmpout,fileres);
1967: strcat(tmpout,postop);
1968: return tmpout;
1969: }
1.126 brouard 1970:
1.213 brouard 1971: /*************** function subdirfext3 ***********/
1972: char *subdirfext3(char fileres[], char *preop, char *postop)
1973: {
1974:
1975: /* Caution optionfilefiname is hidden */
1976: strcpy(tmpout,optionfilefiname);
1977: strcat(tmpout,"/");
1978: strcat(tmpout,preop);
1979: strcat(tmpout,fileres);
1980: strcat(tmpout,postop);
1981: return tmpout;
1982: }
1983:
1.162 brouard 1984: char *asc_diff_time(long time_sec, char ascdiff[])
1985: {
1986: long sec_left, days, hours, minutes;
1987: days = (time_sec) / (60*60*24);
1988: sec_left = (time_sec) % (60*60*24);
1989: hours = (sec_left) / (60*60) ;
1990: sec_left = (sec_left) %(60*60);
1991: minutes = (sec_left) /60;
1992: sec_left = (sec_left) % (60);
1993: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1994: return ascdiff;
1995: }
1996:
1.126 brouard 1997: /***************** f1dim *************************/
1998: extern int ncom;
1999: extern double *pcom,*xicom;
2000: extern double (*nrfunc)(double []);
2001:
2002: double f1dim(double x)
2003: {
2004: int j;
2005: double f;
2006: double *xt;
2007:
2008: xt=vector(1,ncom);
2009: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2010: f=(*nrfunc)(xt);
2011: free_vector(xt,1,ncom);
2012: return f;
2013: }
2014:
2015: /*****************brent *************************/
2016: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2017: {
2018: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2019: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2020: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2021: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2022: * returned function value.
2023: */
1.126 brouard 2024: int iter;
2025: double a,b,d,etemp;
1.159 brouard 2026: double fu=0,fv,fw,fx;
1.164 brouard 2027: double ftemp=0.;
1.126 brouard 2028: double p,q,r,tol1,tol2,u,v,w,x,xm;
2029: double e=0.0;
2030:
2031: a=(ax < cx ? ax : cx);
2032: b=(ax > cx ? ax : cx);
2033: x=w=v=bx;
2034: fw=fv=fx=(*f)(x);
2035: for (iter=1;iter<=ITMAX;iter++) {
2036: xm=0.5*(a+b);
2037: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2038: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2039: printf(".");fflush(stdout);
2040: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2041: #ifdef DEBUGBRENT
1.126 brouard 2042: 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);
2043: 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);
2044: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2045: #endif
2046: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2047: *xmin=x;
2048: return fx;
2049: }
2050: ftemp=fu;
2051: if (fabs(e) > tol1) {
2052: r=(x-w)*(fx-fv);
2053: q=(x-v)*(fx-fw);
2054: p=(x-v)*q-(x-w)*r;
2055: q=2.0*(q-r);
2056: if (q > 0.0) p = -p;
2057: q=fabs(q);
2058: etemp=e;
2059: e=d;
2060: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2061: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2062: else {
1.224 brouard 2063: d=p/q;
2064: u=x+d;
2065: if (u-a < tol2 || b-u < tol2)
2066: d=SIGN(tol1,xm-x);
1.126 brouard 2067: }
2068: } else {
2069: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2070: }
2071: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2072: fu=(*f)(u);
2073: if (fu <= fx) {
2074: if (u >= x) a=x; else b=x;
2075: SHFT(v,w,x,u)
1.183 brouard 2076: SHFT(fv,fw,fx,fu)
2077: } else {
2078: if (u < x) a=u; else b=u;
2079: if (fu <= fw || w == x) {
1.224 brouard 2080: v=w;
2081: w=u;
2082: fv=fw;
2083: fw=fu;
1.183 brouard 2084: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2085: v=u;
2086: fv=fu;
1.183 brouard 2087: }
2088: }
1.126 brouard 2089: }
2090: nrerror("Too many iterations in brent");
2091: *xmin=x;
2092: return fx;
2093: }
2094:
2095: /****************** mnbrak ***********************/
2096:
2097: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2098: double (*func)(double))
1.183 brouard 2099: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2100: the downhill direction (defined by the function as evaluated at the initial points) and returns
2101: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2102: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2103: */
1.126 brouard 2104: double ulim,u,r,q, dum;
2105: double fu;
1.187 brouard 2106:
2107: double scale=10.;
2108: int iterscale=0;
2109:
2110: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2111: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2112:
2113:
2114: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2115: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2116: /* *bx = *ax - (*ax - *bx)/scale; */
2117: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2118: /* } */
2119:
1.126 brouard 2120: if (*fb > *fa) {
2121: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2122: SHFT(dum,*fb,*fa,dum)
2123: }
1.126 brouard 2124: *cx=(*bx)+GOLD*(*bx-*ax);
2125: *fc=(*func)(*cx);
1.183 brouard 2126: #ifdef DEBUG
1.224 brouard 2127: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2128: 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 2129: #endif
1.224 brouard 2130: 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 2131: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2132: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2133: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2134: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2135: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2136: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2137: fu=(*func)(u);
1.163 brouard 2138: #ifdef DEBUG
2139: /* f(x)=A(x-u)**2+f(u) */
2140: double A, fparabu;
2141: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2142: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2143: 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);
2144: 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 2145: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2146: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2147: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2148: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2149: #endif
1.184 brouard 2150: #ifdef MNBRAKORIGINAL
1.183 brouard 2151: #else
1.191 brouard 2152: /* if (fu > *fc) { */
2153: /* #ifdef DEBUG */
2154: /* printf("mnbrak4 fu > fc \n"); */
2155: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2156: /* #endif */
2157: /* /\* 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 *\\/ *\/ */
2158: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2159: /* dum=u; /\* Shifting c and u *\/ */
2160: /* u = *cx; */
2161: /* *cx = dum; */
2162: /* dum = fu; */
2163: /* fu = *fc; */
2164: /* *fc =dum; */
2165: /* } else { /\* end *\/ */
2166: /* #ifdef DEBUG */
2167: /* printf("mnbrak3 fu < fc \n"); */
2168: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2169: /* #endif */
2170: /* dum=u; /\* Shifting c and u *\/ */
2171: /* u = *cx; */
2172: /* *cx = dum; */
2173: /* dum = fu; */
2174: /* fu = *fc; */
2175: /* *fc =dum; */
2176: /* } */
1.224 brouard 2177: #ifdef DEBUGMNBRAK
2178: double A, fparabu;
2179: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2180: fparabu= *fa - A*(*ax-u)*(*ax-u);
2181: 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);
2182: 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 2183: #endif
1.191 brouard 2184: dum=u; /* Shifting c and u */
2185: u = *cx;
2186: *cx = dum;
2187: dum = fu;
2188: fu = *fc;
2189: *fc =dum;
1.183 brouard 2190: #endif
1.162 brouard 2191: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2192: #ifdef DEBUG
1.224 brouard 2193: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2194: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2195: #endif
1.126 brouard 2196: fu=(*func)(u);
2197: if (fu < *fc) {
1.183 brouard 2198: #ifdef DEBUG
1.224 brouard 2199: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2200: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2201: #endif
2202: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2203: SHFT(*fb,*fc,fu,(*func)(u))
2204: #ifdef DEBUG
2205: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2206: #endif
2207: }
1.162 brouard 2208: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2209: #ifdef DEBUG
1.224 brouard 2210: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2211: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2212: #endif
1.126 brouard 2213: u=ulim;
2214: fu=(*func)(u);
1.183 brouard 2215: } else { /* u could be left to b (if r > q parabola has a maximum) */
2216: #ifdef DEBUG
1.224 brouard 2217: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2218: 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 2219: #endif
1.126 brouard 2220: u=(*cx)+GOLD*(*cx-*bx);
2221: fu=(*func)(u);
1.224 brouard 2222: #ifdef DEBUG
2223: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2224: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2225: #endif
1.183 brouard 2226: } /* end tests */
1.126 brouard 2227: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2228: SHFT(*fa,*fb,*fc,fu)
2229: #ifdef DEBUG
1.224 brouard 2230: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2231: 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 2232: #endif
2233: } /* 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 2234: }
2235:
2236: /*************** linmin ************************/
1.162 brouard 2237: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2238: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2239: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2240: the value of func at the returned location p . This is actually all accomplished by calling the
2241: routines mnbrak and brent .*/
1.126 brouard 2242: int ncom;
2243: double *pcom,*xicom;
2244: double (*nrfunc)(double []);
2245:
1.224 brouard 2246: #ifdef LINMINORIGINAL
1.126 brouard 2247: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2248: #else
2249: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2250: #endif
1.126 brouard 2251: {
2252: double brent(double ax, double bx, double cx,
2253: double (*f)(double), double tol, double *xmin);
2254: double f1dim(double x);
2255: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2256: double *fc, double (*func)(double));
2257: int j;
2258: double xx,xmin,bx,ax;
2259: double fx,fb,fa;
1.187 brouard 2260:
1.203 brouard 2261: #ifdef LINMINORIGINAL
2262: #else
2263: double scale=10., axs, xxs; /* Scale added for infinity */
2264: #endif
2265:
1.126 brouard 2266: ncom=n;
2267: pcom=vector(1,n);
2268: xicom=vector(1,n);
2269: nrfunc=func;
2270: for (j=1;j<=n;j++) {
2271: pcom[j]=p[j];
1.202 brouard 2272: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2273: }
1.187 brouard 2274:
1.203 brouard 2275: #ifdef LINMINORIGINAL
2276: xx=1.;
2277: #else
2278: axs=0.0;
2279: xxs=1.;
2280: do{
2281: xx= xxs;
2282: #endif
1.187 brouard 2283: ax=0.;
2284: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2285: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2286: /* 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)) */
2287: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2288: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2289: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2290: /* 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 2291: #ifdef LINMINORIGINAL
2292: #else
2293: if (fx != fx){
1.224 brouard 2294: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2295: printf("|");
2296: fprintf(ficlog,"|");
1.203 brouard 2297: #ifdef DEBUGLINMIN
1.224 brouard 2298: 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 2299: #endif
2300: }
1.224 brouard 2301: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2302: #endif
2303:
1.191 brouard 2304: #ifdef DEBUGLINMIN
2305: 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 2306: 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 2307: #endif
1.224 brouard 2308: #ifdef LINMINORIGINAL
2309: #else
1.317 brouard 2310: if(fb == fx){ /* Flat function in the direction */
2311: xmin=xx;
1.224 brouard 2312: *flat=1;
1.317 brouard 2313: }else{
1.224 brouard 2314: *flat=0;
2315: #endif
2316: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2317: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2318: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2319: /* fmin = f(p[j] + xmin * xi[j]) */
2320: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2321: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2322: #ifdef DEBUG
1.224 brouard 2323: 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);
2324: 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);
2325: #endif
2326: #ifdef LINMINORIGINAL
2327: #else
2328: }
1.126 brouard 2329: #endif
1.191 brouard 2330: #ifdef DEBUGLINMIN
2331: printf("linmin end ");
1.202 brouard 2332: fprintf(ficlog,"linmin end ");
1.191 brouard 2333: #endif
1.126 brouard 2334: for (j=1;j<=n;j++) {
1.203 brouard 2335: #ifdef LINMINORIGINAL
2336: xi[j] *= xmin;
2337: #else
2338: #ifdef DEBUGLINMIN
2339: if(xxs <1.0)
2340: printf(" before xi[%d]=%12.8f", j,xi[j]);
2341: #endif
2342: 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) */
2343: #ifdef DEBUGLINMIN
2344: if(xxs <1.0)
2345: 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 );
2346: #endif
2347: #endif
1.187 brouard 2348: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2349: }
1.191 brouard 2350: #ifdef DEBUGLINMIN
1.203 brouard 2351: printf("\n");
1.191 brouard 2352: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2353: 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 2354: for (j=1;j<=n;j++) {
1.202 brouard 2355: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2356: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2357: if(j % ncovmodel == 0){
1.191 brouard 2358: printf("\n");
1.202 brouard 2359: fprintf(ficlog,"\n");
2360: }
1.191 brouard 2361: }
1.203 brouard 2362: #else
1.191 brouard 2363: #endif
1.126 brouard 2364: free_vector(xicom,1,n);
2365: free_vector(pcom,1,n);
2366: }
2367:
2368:
2369: /*************** powell ************************/
1.162 brouard 2370: /*
1.317 brouard 2371: Minimization of a function func of n variables. Input consists in an initial starting point
2372: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2373: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2374: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2375: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2376: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2377: */
1.224 brouard 2378: #ifdef LINMINORIGINAL
2379: #else
2380: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2381: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2382: #endif
1.126 brouard 2383: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2384: double (*func)(double []))
2385: {
1.224 brouard 2386: #ifdef LINMINORIGINAL
2387: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2388: double (*func)(double []));
1.224 brouard 2389: #else
1.241 brouard 2390: void linmin(double p[], double xi[], int n, double *fret,
2391: double (*func)(double []),int *flat);
1.224 brouard 2392: #endif
1.239 brouard 2393: int i,ibig,j,jk,k;
1.126 brouard 2394: double del,t,*pt,*ptt,*xit;
1.181 brouard 2395: double directest;
1.126 brouard 2396: double fp,fptt;
2397: double *xits;
2398: int niterf, itmp;
2399:
2400: pt=vector(1,n);
2401: ptt=vector(1,n);
2402: xit=vector(1,n);
2403: xits=vector(1,n);
2404: *fret=(*func)(p);
2405: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2406: rcurr_time = time(NULL);
1.126 brouard 2407: for (*iter=1;;++(*iter)) {
1.187 brouard 2408: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2409: ibig=0;
2410: del=0.0;
1.157 brouard 2411: rlast_time=rcurr_time;
2412: /* (void) gettimeofday(&curr_time,&tzp); */
2413: rcurr_time = time(NULL);
2414: curr_time = *localtime(&rcurr_time);
2415: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2416: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2417: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2418: for (i=1;i<=n;i++) {
1.126 brouard 2419: fprintf(ficrespow," %.12lf", p[i]);
2420: }
1.239 brouard 2421: fprintf(ficrespow,"\n");fflush(ficrespow);
2422: printf("\n#model= 1 + age ");
2423: fprintf(ficlog,"\n#model= 1 + age ");
2424: if(nagesqr==1){
1.241 brouard 2425: printf(" + age*age ");
2426: fprintf(ficlog," + age*age ");
1.239 brouard 2427: }
2428: for(j=1;j <=ncovmodel-2;j++){
2429: if(Typevar[j]==0) {
2430: printf(" + V%d ",Tvar[j]);
2431: fprintf(ficlog," + V%d ",Tvar[j]);
2432: }else if(Typevar[j]==1) {
2433: printf(" + V%d*age ",Tvar[j]);
2434: fprintf(ficlog," + V%d*age ",Tvar[j]);
2435: }else if(Typevar[j]==2) {
2436: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2437: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2438: }
2439: }
1.126 brouard 2440: printf("\n");
1.239 brouard 2441: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2442: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2443: fprintf(ficlog,"\n");
1.239 brouard 2444: for(i=1,jk=1; i <=nlstate; i++){
2445: for(k=1; k <=(nlstate+ndeath); k++){
2446: if (k != i) {
2447: printf("%d%d ",i,k);
2448: fprintf(ficlog,"%d%d ",i,k);
2449: for(j=1; j <=ncovmodel; j++){
2450: printf("%12.7f ",p[jk]);
2451: fprintf(ficlog,"%12.7f ",p[jk]);
2452: jk++;
2453: }
2454: printf("\n");
2455: fprintf(ficlog,"\n");
2456: }
2457: }
2458: }
1.241 brouard 2459: if(*iter <=3 && *iter >1){
1.157 brouard 2460: tml = *localtime(&rcurr_time);
2461: strcpy(strcurr,asctime(&tml));
2462: rforecast_time=rcurr_time;
1.126 brouard 2463: itmp = strlen(strcurr);
2464: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2465: strcurr[itmp-1]='\0';
1.162 brouard 2466: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2467: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2468: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2469: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2470: forecast_time = *localtime(&rforecast_time);
2471: strcpy(strfor,asctime(&forecast_time));
2472: itmp = strlen(strfor);
2473: if(strfor[itmp-1]=='\n')
2474: strfor[itmp-1]='\0';
2475: 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);
2476: 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 2477: }
2478: }
1.187 brouard 2479: for (i=1;i<=n;i++) { /* For each direction i */
2480: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2481: fptt=(*fret);
2482: #ifdef DEBUG
1.203 brouard 2483: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2484: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2485: #endif
1.203 brouard 2486: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2487: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2488: #ifdef LINMINORIGINAL
1.188 brouard 2489: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2490: #else
2491: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2492: flatdir[i]=flat; /* Function is vanishing in that direction i */
2493: #endif
2494: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2495: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2496: /* because that direction will be replaced unless the gain del is small */
2497: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2498: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2499: /* with the new direction. */
2500: del=fabs(fptt-(*fret));
2501: ibig=i;
1.126 brouard 2502: }
2503: #ifdef DEBUG
2504: printf("%d %.12e",i,(*fret));
2505: fprintf(ficlog,"%d %.12e",i,(*fret));
2506: for (j=1;j<=n;j++) {
1.224 brouard 2507: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2508: printf(" x(%d)=%.12e",j,xit[j]);
2509: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2510: }
2511: for(j=1;j<=n;j++) {
1.225 brouard 2512: printf(" p(%d)=%.12e",j,p[j]);
2513: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2514: }
2515: printf("\n");
2516: fprintf(ficlog,"\n");
2517: #endif
1.187 brouard 2518: } /* end loop on each direction i */
2519: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2520: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2521: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2522: for(j=1;j<=n;j++) {
2523: if(flatdir[j] >0){
2524: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2525: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2526: }
1.319 brouard 2527: /* printf("\n"); */
2528: /* fprintf(ficlog,"\n"); */
2529: }
1.243 brouard 2530: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2531: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2532: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2533: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2534: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2535: /* decreased of more than 3.84 */
2536: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2537: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2538: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2539:
1.188 brouard 2540: /* Starting the program with initial values given by a former maximization will simply change */
2541: /* the scales of the directions and the directions, because the are reset to canonical directions */
2542: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2543: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2544: #ifdef DEBUG
2545: int k[2],l;
2546: k[0]=1;
2547: k[1]=-1;
2548: printf("Max: %.12e",(*func)(p));
2549: fprintf(ficlog,"Max: %.12e",(*func)(p));
2550: for (j=1;j<=n;j++) {
2551: printf(" %.12e",p[j]);
2552: fprintf(ficlog," %.12e",p[j]);
2553: }
2554: printf("\n");
2555: fprintf(ficlog,"\n");
2556: for(l=0;l<=1;l++) {
2557: for (j=1;j<=n;j++) {
2558: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2559: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2560: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2561: }
2562: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2563: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2564: }
2565: #endif
2566:
2567: free_vector(xit,1,n);
2568: free_vector(xits,1,n);
2569: free_vector(ptt,1,n);
2570: free_vector(pt,1,n);
2571: return;
1.192 brouard 2572: } /* enough precision */
1.240 brouard 2573: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2574: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2575: ptt[j]=2.0*p[j]-pt[j];
2576: xit[j]=p[j]-pt[j];
2577: pt[j]=p[j];
2578: }
1.181 brouard 2579: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2580: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2581: if (*iter <=4) {
1.225 brouard 2582: #else
2583: #endif
1.224 brouard 2584: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2585: #else
1.161 brouard 2586: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2587: #endif
1.162 brouard 2588: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2589: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2590: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2591: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2592: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2593: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2594: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2595: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2596: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2597: /* Even if f3 <f1, directest can be negative and t >0 */
2598: /* mu² and del² are equal when f3=f1 */
2599: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2600: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2601: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2602: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2603: #ifdef NRCORIGINAL
2604: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2605: #else
2606: 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 2607: t= t- del*SQR(fp-fptt);
1.183 brouard 2608: #endif
1.202 brouard 2609: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2610: #ifdef DEBUG
1.181 brouard 2611: 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);
2612: 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 2613: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2614: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2615: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2616: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2617: 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);
2618: 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);
2619: #endif
1.183 brouard 2620: #ifdef POWELLORIGINAL
2621: if (t < 0.0) { /* Then we use it for new direction */
2622: #else
1.182 brouard 2623: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2624: 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 2625: 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 2626: 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 2627: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2628: }
1.181 brouard 2629: if (directest < 0.0) { /* Then we use it for new direction */
2630: #endif
1.191 brouard 2631: #ifdef DEBUGLINMIN
1.234 brouard 2632: printf("Before linmin in direction P%d-P0\n",n);
2633: for (j=1;j<=n;j++) {
2634: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2635: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2636: if(j % ncovmodel == 0){
2637: printf("\n");
2638: fprintf(ficlog,"\n");
2639: }
2640: }
1.224 brouard 2641: #endif
2642: #ifdef LINMINORIGINAL
1.234 brouard 2643: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2644: #else
1.234 brouard 2645: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2646: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2647: #endif
1.234 brouard 2648:
1.191 brouard 2649: #ifdef DEBUGLINMIN
1.234 brouard 2650: for (j=1;j<=n;j++) {
2651: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2652: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2653: if(j % ncovmodel == 0){
2654: printf("\n");
2655: fprintf(ficlog,"\n");
2656: }
2657: }
1.224 brouard 2658: #endif
1.234 brouard 2659: for (j=1;j<=n;j++) {
2660: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2661: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2662: }
1.224 brouard 2663: #ifdef LINMINORIGINAL
2664: #else
1.234 brouard 2665: for (j=1, flatd=0;j<=n;j++) {
2666: if(flatdir[j]>0)
2667: flatd++;
2668: }
2669: if(flatd >0){
1.255 brouard 2670: printf("%d flat directions: ",flatd);
2671: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2672: for (j=1;j<=n;j++) {
2673: if(flatdir[j]>0){
2674: printf("%d ",j);
2675: fprintf(ficlog,"%d ",j);
2676: }
2677: }
2678: printf("\n");
2679: fprintf(ficlog,"\n");
1.319 brouard 2680: #ifdef FLATSUP
2681: free_vector(xit,1,n);
2682: free_vector(xits,1,n);
2683: free_vector(ptt,1,n);
2684: free_vector(pt,1,n);
2685: return;
2686: #endif
1.234 brouard 2687: }
1.191 brouard 2688: #endif
1.234 brouard 2689: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2690: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2691:
1.126 brouard 2692: #ifdef DEBUG
1.234 brouard 2693: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2694: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2695: for(j=1;j<=n;j++){
2696: printf(" %lf",xit[j]);
2697: fprintf(ficlog," %lf",xit[j]);
2698: }
2699: printf("\n");
2700: fprintf(ficlog,"\n");
1.126 brouard 2701: #endif
1.192 brouard 2702: } /* end of t or directest negative */
1.224 brouard 2703: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2704: #else
1.234 brouard 2705: } /* end if (fptt < fp) */
1.192 brouard 2706: #endif
1.225 brouard 2707: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2708: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2709: #else
1.224 brouard 2710: #endif
1.234 brouard 2711: } /* loop iteration */
1.126 brouard 2712: }
1.234 brouard 2713:
1.126 brouard 2714: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2715:
1.235 brouard 2716: 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 2717: {
1.279 brouard 2718: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2719: * (and selected quantitative values in nres)
2720: * by left multiplying the unit
2721: * matrix by transitions matrix until convergence is reached with precision ftolpl
2722: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2723: * Wx is row vector: population in state 1, population in state 2, population dead
2724: * or prevalence in state 1, prevalence in state 2, 0
2725: * newm is the matrix after multiplications, its rows are identical at a factor.
2726: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2727: * Output is prlim.
2728: * Initial matrix pimij
2729: */
1.206 brouard 2730: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2731: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2732: /* 0, 0 , 1} */
2733: /*
2734: * and after some iteration: */
2735: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2736: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2737: /* 0, 0 , 1} */
2738: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2739: /* {0.51571254859325999, 0.4842874514067399, */
2740: /* 0.51326036147820708, 0.48673963852179264} */
2741: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2742:
1.126 brouard 2743: int i, ii,j,k;
1.209 brouard 2744: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2745: /* double **matprod2(); */ /* test */
1.218 brouard 2746: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2747: double **newm;
1.209 brouard 2748: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2749: int ncvloop=0;
1.288 brouard 2750: int first=0;
1.169 brouard 2751:
1.209 brouard 2752: min=vector(1,nlstate);
2753: max=vector(1,nlstate);
2754: meandiff=vector(1,nlstate);
2755:
1.218 brouard 2756: /* Starting with matrix unity */
1.126 brouard 2757: for (ii=1;ii<=nlstate+ndeath;ii++)
2758: for (j=1;j<=nlstate+ndeath;j++){
2759: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2760: }
1.169 brouard 2761:
2762: cov[1]=1.;
2763:
2764: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2765: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2766: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2767: ncvloop++;
1.126 brouard 2768: newm=savm;
2769: /* Covariates have to be included here again */
1.138 brouard 2770: cov[2]=agefin;
1.319 brouard 2771: if(nagesqr==1){
2772: cov[3]= agefin*agefin;
2773: }
1.234 brouard 2774: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2775: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2776: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.319 brouard 2777: /* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; */
1.235 brouard 2778: /* 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 2779: }
2780: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2781: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.319 brouard 2782: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2783: /* cov[++k1]=Tqresult[nres][k]; */
1.235 brouard 2784: /* 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 2785: }
1.237 brouard 2786: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.319 brouard 2787: if(Dummy[Tage[k]]==2){ /* dummy with age */
1.234 brouard 2788: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 2789: /* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
2790: } else if(Dummy[Tage[k]]==3){ /* quantitative with age */
2791: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2792: /* cov[++k1]=Tqresult[nres][k]; */
1.234 brouard 2793: }
1.235 brouard 2794: /* 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 2795: }
1.237 brouard 2796: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2797: /* 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]); */
1.237 brouard 2798: if(Dummy[Tvard[k][1]==0]){
2799: if(Dummy[Tvard[k][2]==0]){
2800: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
1.319 brouard 2801: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.237 brouard 2802: }else{
2803: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
1.319 brouard 2804: /* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; */
1.237 brouard 2805: }
2806: }else{
2807: if(Dummy[Tvard[k][2]==0]){
2808: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
1.319 brouard 2809: /* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; */
1.237 brouard 2810: }else{
2811: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
1.319 brouard 2812: /* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
1.237 brouard 2813: }
2814: }
1.234 brouard 2815: }
1.138 brouard 2816: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2817: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2818: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2819: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2820: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 2821: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2822: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2823:
1.126 brouard 2824: savm=oldm;
2825: oldm=newm;
1.209 brouard 2826:
2827: for(j=1; j<=nlstate; j++){
2828: max[j]=0.;
2829: min[j]=1.;
2830: }
2831: for(i=1;i<=nlstate;i++){
2832: sumnew=0;
2833: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2834: for(j=1; j<=nlstate; j++){
2835: prlim[i][j]= newm[i][j]/(1-sumnew);
2836: max[j]=FMAX(max[j],prlim[i][j]);
2837: min[j]=FMIN(min[j],prlim[i][j]);
2838: }
2839: }
2840:
1.126 brouard 2841: maxmax=0.;
1.209 brouard 2842: for(j=1; j<=nlstate; j++){
2843: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2844: maxmax=FMAX(maxmax,meandiff[j]);
2845: /* 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 2846: } /* j loop */
1.203 brouard 2847: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2848: /* 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 2849: if(maxmax < ftolpl){
1.209 brouard 2850: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2851: free_vector(min,1,nlstate);
2852: free_vector(max,1,nlstate);
2853: free_vector(meandiff,1,nlstate);
1.126 brouard 2854: return prlim;
2855: }
1.288 brouard 2856: } /* agefin loop */
1.208 brouard 2857: /* After some age loop it doesn't converge */
1.288 brouard 2858: if(!first){
2859: first=1;
2860: 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 2861: 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);
2862: }else if (first >=1 && first <10){
2863: 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);
2864: first++;
2865: }else if (first ==10){
2866: 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);
2867: 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");
2868: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
2869: first++;
1.288 brouard 2870: }
2871:
1.209 brouard 2872: /* 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); */
2873: free_vector(min,1,nlstate);
2874: free_vector(max,1,nlstate);
2875: free_vector(meandiff,1,nlstate);
1.208 brouard 2876:
1.169 brouard 2877: return prlim; /* should not reach here */
1.126 brouard 2878: }
2879:
1.217 brouard 2880:
2881: /**** Back Prevalence limit (stable or period prevalence) ****************/
2882:
1.218 brouard 2883: /* 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) */
2884: /* 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 2885: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2886: {
1.264 brouard 2887: /* 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 2888: matrix by transitions matrix until convergence is reached with precision ftolpl */
2889: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2890: /* Wx is row vector: population in state 1, population in state 2, population dead */
2891: /* or prevalence in state 1, prevalence in state 2, 0 */
2892: /* newm is the matrix after multiplications, its rows are identical at a factor */
2893: /* Initial matrix pimij */
2894: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2895: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2896: /* 0, 0 , 1} */
2897: /*
2898: * and after some iteration: */
2899: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2900: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2901: /* 0, 0 , 1} */
2902: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2903: /* {0.51571254859325999, 0.4842874514067399, */
2904: /* 0.51326036147820708, 0.48673963852179264} */
2905: /* If we start from prlim again, prlim tends to a constant matrix */
2906:
2907: int i, ii,j,k;
1.247 brouard 2908: int first=0;
1.217 brouard 2909: double *min, *max, *meandiff, maxmax,sumnew=0.;
2910: /* double **matprod2(); */ /* test */
2911: double **out, cov[NCOVMAX+1], **bmij();
2912: double **newm;
1.218 brouard 2913: double **dnewm, **doldm, **dsavm; /* for use */
2914: double **oldm, **savm; /* for use */
2915:
1.217 brouard 2916: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2917: int ncvloop=0;
2918:
2919: min=vector(1,nlstate);
2920: max=vector(1,nlstate);
2921: meandiff=vector(1,nlstate);
2922:
1.266 brouard 2923: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2924: oldm=oldms; savm=savms;
2925:
2926: /* Starting with matrix unity */
2927: for (ii=1;ii<=nlstate+ndeath;ii++)
2928: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2929: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2930: }
2931:
2932: cov[1]=1.;
2933:
2934: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2935: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2936: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 2937: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2938: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2939: ncvloop++;
1.218 brouard 2940: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2941: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2942: /* Covariates have to be included here again */
2943: cov[2]=agefin;
1.319 brouard 2944: if(nagesqr==1){
1.217 brouard 2945: cov[3]= agefin*agefin;;
1.319 brouard 2946: }
1.242 brouard 2947: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2948: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2949: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2950: /* 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 2951: }
2952: /* for (k=1; k<=cptcovn;k++) { */
2953: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2954: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2955: /* /\* 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])]); *\/ */
2956: /* } */
2957: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2958: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2959: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2960: /* 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]); */
2961: }
2962: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2963: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2964: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2965: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2966: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.319 brouard 2967: /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age *\/ ERROR ???*/
2968: if(Dummy[Tage[k]]== 2){ /* dummy with age */
1.242 brouard 2969: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 2970: } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */
2971: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.242 brouard 2972: }
2973: /* 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]); */
2974: }
2975: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2976: /* 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]); */
2977: if(Dummy[Tvard[k][1]==0]){
2978: if(Dummy[Tvard[k][2]==0]){
2979: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2980: }else{
2981: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2982: }
2983: }else{
2984: if(Dummy[Tvard[k][2]==0]){
2985: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2986: }else{
2987: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2988: }
2989: }
1.217 brouard 2990: }
2991:
2992: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2993: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2994: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2995: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2996: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2997: /* ij should be linked to the correct index of cov */
2998: /* age and covariate values ij are in 'cov', but we need to pass
2999: * ij for the observed prevalence at age and status and covariate
3000: * number: prevacurrent[(int)agefin][ii][ij]
3001: */
3002: /* 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 *\/ */
3003: /* 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 *\/ */
3004: 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 3005: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3006: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3007: /* for(i=1; i<=nlstate+ndeath; i++) { */
3008: /* printf("%d newm= ",i); */
3009: /* for(j=1;j<=nlstate+ndeath;j++) { */
3010: /* printf("%f ",newm[i][j]); */
3011: /* } */
3012: /* printf("oldm * "); */
3013: /* for(j=1;j<=nlstate+ndeath;j++) { */
3014: /* printf("%f ",oldm[i][j]); */
3015: /* } */
1.268 brouard 3016: /* printf(" bmmij "); */
1.266 brouard 3017: /* for(j=1;j<=nlstate+ndeath;j++) { */
3018: /* printf("%f ",pmmij[i][j]); */
3019: /* } */
3020: /* printf("\n"); */
3021: /* } */
3022: /* } */
1.217 brouard 3023: savm=oldm;
3024: oldm=newm;
1.266 brouard 3025:
1.217 brouard 3026: for(j=1; j<=nlstate; j++){
3027: max[j]=0.;
3028: min[j]=1.;
3029: }
3030: for(j=1; j<=nlstate; j++){
3031: for(i=1;i<=nlstate;i++){
1.234 brouard 3032: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3033: bprlim[i][j]= newm[i][j];
3034: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3035: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3036: }
3037: }
1.218 brouard 3038:
1.217 brouard 3039: maxmax=0.;
3040: for(i=1; i<=nlstate; i++){
1.318 brouard 3041: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3042: maxmax=FMAX(maxmax,meandiff[i]);
3043: /* 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 3044: } /* i loop */
1.217 brouard 3045: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3046: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3047: if(maxmax < ftolpl){
1.220 brouard 3048: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3049: free_vector(min,1,nlstate);
3050: free_vector(max,1,nlstate);
3051: free_vector(meandiff,1,nlstate);
3052: return bprlim;
3053: }
1.288 brouard 3054: } /* agefin loop */
1.217 brouard 3055: /* After some age loop it doesn't converge */
1.288 brouard 3056: if(!first){
1.247 brouard 3057: first=1;
3058: 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\
3059: 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);
3060: }
3061: 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 3062: 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);
3063: /* 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); */
3064: free_vector(min,1,nlstate);
3065: free_vector(max,1,nlstate);
3066: free_vector(meandiff,1,nlstate);
3067:
3068: return bprlim; /* should not reach here */
3069: }
3070:
1.126 brouard 3071: /*************** transition probabilities ***************/
3072:
3073: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3074: {
1.138 brouard 3075: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3076: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3077: model to the ncovmodel covariates (including constant and age).
3078: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3079: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3080: ncth covariate in the global vector x is given by the formula:
3081: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3082: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3083: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3084: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3085: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3086: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3087: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3088: */
3089: double s1, lnpijopii;
1.126 brouard 3090: /*double t34;*/
1.164 brouard 3091: int i,j, nc, ii, jj;
1.126 brouard 3092:
1.223 brouard 3093: for(i=1; i<= nlstate; i++){
3094: for(j=1; j<i;j++){
3095: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3096: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3097: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3098: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3099: }
3100: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3101: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3102: }
3103: for(j=i+1; j<=nlstate+ndeath;j++){
3104: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3105: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3106: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3107: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3108: }
3109: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3110: }
3111: }
1.218 brouard 3112:
1.223 brouard 3113: for(i=1; i<= nlstate; i++){
3114: s1=0;
3115: for(j=1; j<i; j++){
3116: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3117: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3118: }
3119: for(j=i+1; j<=nlstate+ndeath; j++){
3120: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3121: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3122: }
3123: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3124: ps[i][i]=1./(s1+1.);
3125: /* Computing other pijs */
3126: for(j=1; j<i; j++)
3127: ps[i][j]= exp(ps[i][j])*ps[i][i];
3128: for(j=i+1; j<=nlstate+ndeath; j++)
3129: ps[i][j]= exp(ps[i][j])*ps[i][i];
3130: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3131: } /* end i */
1.218 brouard 3132:
1.223 brouard 3133: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3134: for(jj=1; jj<= nlstate+ndeath; jj++){
3135: ps[ii][jj]=0;
3136: ps[ii][ii]=1;
3137: }
3138: }
1.294 brouard 3139:
3140:
1.223 brouard 3141: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3142: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3143: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3144: /* } */
3145: /* printf("\n "); */
3146: /* } */
3147: /* printf("\n ");printf("%lf ",cov[2]);*/
3148: /*
3149: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3150: goto end;*/
1.266 brouard 3151: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3152: }
3153:
1.218 brouard 3154: /*************** backward transition probabilities ***************/
3155:
3156: /* 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 ) */
3157: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3158: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3159: {
1.302 brouard 3160: /* 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 3161: * 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 3162: */
1.218 brouard 3163: int i, ii, j,k;
1.222 brouard 3164:
3165: double **out, **pmij();
3166: double sumnew=0.;
1.218 brouard 3167: double agefin;
1.292 brouard 3168: 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 3169: double **dnewm, **dsavm, **doldm;
3170: double **bbmij;
3171:
1.218 brouard 3172: doldm=ddoldms; /* global pointers */
1.222 brouard 3173: dnewm=ddnewms;
3174: dsavm=ddsavms;
1.318 brouard 3175:
3176: /* Debug */
3177: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3178: agefin=cov[2];
1.268 brouard 3179: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3180: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3181: the observed prevalence (with this covariate ij) at beginning of transition */
3182: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3183:
3184: /* P_x */
1.266 brouard 3185: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 3186: /* outputs pmmij which is a stochastic matrix in row */
3187:
3188: /* Diag(w_x) */
1.292 brouard 3189: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3190: sumnew=0.;
1.269 brouard 3191: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3192: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3193: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3194: sumnew+=prevacurrent[(int)agefin][ii][ij];
3195: }
3196: if(sumnew >0.01){ /* At least some value in the prevalence */
3197: for (ii=1;ii<=nlstate+ndeath;ii++){
3198: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3199: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3200: }
3201: }else{
3202: for (ii=1;ii<=nlstate+ndeath;ii++){
3203: for (j=1;j<=nlstate+ndeath;j++)
3204: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3205: }
3206: /* if(sumnew <0.9){ */
3207: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3208: /* } */
3209: }
3210: k3=0.0; /* We put the last diagonal to 0 */
3211: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3212: doldm[ii][ii]= k3;
3213: }
3214: /* End doldm, At the end doldm is diag[(w_i)] */
3215:
1.292 brouard 3216: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3217: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3218:
1.292 brouard 3219: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3220: /* 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 3221: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3222: sumnew=0.;
1.222 brouard 3223: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3224: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3225: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3226: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3227: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3228: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3229: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3230: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3231: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3232: /* }else */
1.268 brouard 3233: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3234: } /*End ii */
3235: } /* 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 */
3236:
1.292 brouard 3237: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3238: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3239: /* end bmij */
1.266 brouard 3240: return ps; /*pointer is unchanged */
1.218 brouard 3241: }
1.217 brouard 3242: /*************** transition probabilities ***************/
3243:
1.218 brouard 3244: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3245: {
3246: /* According to parameters values stored in x and the covariate's values stored in cov,
3247: computes the probability to be observed in state j being in state i by appying the
3248: model to the ncovmodel covariates (including constant and age).
3249: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3250: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3251: ncth covariate in the global vector x is given by the formula:
3252: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3253: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3254: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3255: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3256: Outputs ps[i][j] the probability to be observed in j being in j according to
3257: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3258: */
3259: double s1, lnpijopii;
3260: /*double t34;*/
3261: int i,j, nc, ii, jj;
3262:
1.234 brouard 3263: for(i=1; i<= nlstate; i++){
3264: for(j=1; j<i;j++){
3265: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3266: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3267: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3268: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3269: }
3270: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3271: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3272: }
3273: for(j=i+1; j<=nlstate+ndeath;j++){
3274: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3275: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3276: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3277: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3278: }
3279: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3280: }
3281: }
3282:
3283: for(i=1; i<= nlstate; i++){
3284: s1=0;
3285: for(j=1; j<i; j++){
3286: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3287: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3288: }
3289: for(j=i+1; j<=nlstate+ndeath; j++){
3290: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3291: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3292: }
3293: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3294: ps[i][i]=1./(s1+1.);
3295: /* Computing other pijs */
3296: for(j=1; j<i; j++)
3297: ps[i][j]= exp(ps[i][j])*ps[i][i];
3298: for(j=i+1; j<=nlstate+ndeath; j++)
3299: ps[i][j]= exp(ps[i][j])*ps[i][i];
3300: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3301: } /* end i */
3302:
3303: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3304: for(jj=1; jj<= nlstate+ndeath; jj++){
3305: ps[ii][jj]=0;
3306: ps[ii][ii]=1;
3307: }
3308: }
1.296 brouard 3309: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3310: for(jj=1; jj<= nlstate+ndeath; jj++){
3311: s1=0.;
3312: for(ii=1; ii<= nlstate+ndeath; ii++){
3313: s1+=ps[ii][jj];
3314: }
3315: for(ii=1; ii<= nlstate; ii++){
3316: ps[ii][jj]=ps[ii][jj]/s1;
3317: }
3318: }
3319: /* Transposition */
3320: for(jj=1; jj<= nlstate+ndeath; jj++){
3321: for(ii=jj; ii<= nlstate+ndeath; ii++){
3322: s1=ps[ii][jj];
3323: ps[ii][jj]=ps[jj][ii];
3324: ps[jj][ii]=s1;
3325: }
3326: }
3327: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3328: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3329: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3330: /* } */
3331: /* printf("\n "); */
3332: /* } */
3333: /* printf("\n ");printf("%lf ",cov[2]);*/
3334: /*
3335: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3336: goto end;*/
3337: return ps;
1.217 brouard 3338: }
3339:
3340:
1.126 brouard 3341: /**************** Product of 2 matrices ******************/
3342:
1.145 brouard 3343: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3344: {
3345: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3346: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3347: /* in, b, out are matrice of pointers which should have been initialized
3348: before: only the contents of out is modified. The function returns
3349: a pointer to pointers identical to out */
1.145 brouard 3350: int i, j, k;
1.126 brouard 3351: for(i=nrl; i<= nrh; i++)
1.145 brouard 3352: for(k=ncolol; k<=ncoloh; k++){
3353: out[i][k]=0.;
3354: for(j=ncl; j<=nch; j++)
3355: out[i][k] +=in[i][j]*b[j][k];
3356: }
1.126 brouard 3357: return out;
3358: }
3359:
3360:
3361: /************* Higher Matrix Product ***************/
3362:
1.235 brouard 3363: 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 3364: {
1.218 brouard 3365: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3366: 'nhstepm*hstepm*stepm' months (i.e. until
3367: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3368: nhstepm*hstepm matrices.
3369: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3370: (typically every 2 years instead of every month which is too big
3371: for the memory).
3372: Model is determined by parameters x and covariates have to be
3373: included manually here.
3374:
3375: */
3376:
3377: int i, j, d, h, k;
1.131 brouard 3378: double **out, cov[NCOVMAX+1];
1.126 brouard 3379: double **newm;
1.187 brouard 3380: double agexact;
1.214 brouard 3381: double agebegin, ageend;
1.126 brouard 3382:
3383: /* Hstepm could be zero and should return the unit matrix */
3384: for (i=1;i<=nlstate+ndeath;i++)
3385: for (j=1;j<=nlstate+ndeath;j++){
3386: oldm[i][j]=(i==j ? 1.0 : 0.0);
3387: po[i][j][0]=(i==j ? 1.0 : 0.0);
3388: }
3389: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3390: for(h=1; h <=nhstepm; h++){
3391: for(d=1; d <=hstepm; d++){
3392: newm=savm;
3393: /* Covariates have to be included here again */
3394: cov[1]=1.;
1.214 brouard 3395: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3396: cov[2]=agexact;
1.319 brouard 3397: if(nagesqr==1){
1.227 brouard 3398: cov[3]= agexact*agexact;
1.319 brouard 3399: }
1.235 brouard 3400: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
1.319 brouard 3401: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3402: /* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 */
3403: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3404: /* k 1 2 3 4 5 6 7 8 9 */
3405: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
3406: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
3407: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
3408: /*TvarsDind[k] 2 3 9 */ /* position K of single dummy cova */
1.235 brouard 3409: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3410: /* printf("hpxij 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)); */
3411: }
3412: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3413: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.319 brouard 3414: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
1.235 brouard 3415: /* 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]); */
3416: }
1.319 brouard 3417: for (k=1; k<=cptcovage;k++){ /* For product with age V1+V1*age +V4 +age*V3 */
3418: /* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*/
3419: /* */
3420: if(Dummy[Tage[k]]== 2){ /* dummy with age */
3421: /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age *\/ */
1.235 brouard 3422: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 3423: } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */
3424: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.235 brouard 3425: }
3426: /* 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]); */
3427: }
1.319 brouard 3428: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 3429: /* printf("hPxij 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]); */
1.319 brouard 3430: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
3431: if(Dummy[Tvard[k][1]==0]){
3432: if(Dummy[Tvard[k][2]==0]){
3433: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3434: }else{
3435: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
3436: }
3437: }else{
3438: if(Dummy[Tvard[k][2]==0]){
3439: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
3440: }else{
3441: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
3442: }
3443: }
1.235 brouard 3444: }
3445: /* for (k=1; k<=cptcovn;k++) */
3446: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3447: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3448: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3449: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3450: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3451:
3452:
1.126 brouard 3453: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3454: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3455: /* right multiplication of oldm by the current matrix */
1.126 brouard 3456: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3457: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3458: /* if((int)age == 70){ */
3459: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3460: /* for(i=1; i<=nlstate+ndeath; i++) { */
3461: /* printf("%d pmmij ",i); */
3462: /* for(j=1;j<=nlstate+ndeath;j++) { */
3463: /* printf("%f ",pmmij[i][j]); */
3464: /* } */
3465: /* printf(" oldm "); */
3466: /* for(j=1;j<=nlstate+ndeath;j++) { */
3467: /* printf("%f ",oldm[i][j]); */
3468: /* } */
3469: /* printf("\n"); */
3470: /* } */
3471: /* } */
1.126 brouard 3472: savm=oldm;
3473: oldm=newm;
3474: }
3475: for(i=1; i<=nlstate+ndeath; i++)
3476: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3477: po[i][j][h]=newm[i][j];
3478: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3479: }
1.128 brouard 3480: /*printf("h=%d ",h);*/
1.126 brouard 3481: } /* end h */
1.267 brouard 3482: /* printf("\n H=%d \n",h); */
1.126 brouard 3483: return po;
3484: }
3485:
1.217 brouard 3486: /************* Higher Back Matrix Product ***************/
1.218 brouard 3487: /* 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 3488: 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 3489: {
1.266 brouard 3490: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3491: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3492: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3493: nhstepm*hstepm matrices.
3494: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3495: (typically every 2 years instead of every month which is too big
1.217 brouard 3496: for the memory).
1.218 brouard 3497: Model is determined by parameters x and covariates have to be
1.266 brouard 3498: included manually here. Then we use a call to bmij(x and cov)
3499: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3500: */
1.217 brouard 3501:
3502: int i, j, d, h, k;
1.266 brouard 3503: double **out, cov[NCOVMAX+1], **bmij();
3504: double **newm, ***newmm;
1.217 brouard 3505: double agexact;
3506: double agebegin, ageend;
1.222 brouard 3507: double **oldm, **savm;
1.217 brouard 3508:
1.266 brouard 3509: newmm=po; /* To be saved */
3510: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3511: /* Hstepm could be zero and should return the unit matrix */
3512: for (i=1;i<=nlstate+ndeath;i++)
3513: for (j=1;j<=nlstate+ndeath;j++){
3514: oldm[i][j]=(i==j ? 1.0 : 0.0);
3515: po[i][j][0]=(i==j ? 1.0 : 0.0);
3516: }
3517: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3518: for(h=1; h <=nhstepm; h++){
3519: for(d=1; d <=hstepm; d++){
3520: newm=savm;
3521: /* Covariates have to be included here again */
3522: cov[1]=1.;
1.271 brouard 3523: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3524: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3525: /* Debug */
3526: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3527: cov[2]=agexact;
3528: if(nagesqr==1)
1.222 brouard 3529: cov[3]= agexact*agexact;
1.266 brouard 3530: for (k=1; k<=cptcovn;k++){
3531: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3532: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3533: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3534: /* 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)); */
3535: }
1.267 brouard 3536: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3537: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3538: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3539: /* 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]); */
3540: }
1.319 brouard 3541: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 *//* For product with age */
3542: /* if(Dummy[Tvar[Tage[k]]]== 2){ /\* dummy with age error!!!*\/ */
3543: if(Dummy[Tage[k]]== 2){ /* dummy with age */
1.267 brouard 3544: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.319 brouard 3545: } else if(Dummy[Tage[k]]== 3){ /* quantitative with age */
1.267 brouard 3546: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3547: }
3548: /* 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]); */
3549: }
3550: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3551: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3552: }
1.217 brouard 3553: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3554: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3555:
1.218 brouard 3556: /* Careful transposed matrix */
1.266 brouard 3557: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3558: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3559: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3560: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3561: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3562: /* if((int)age == 70){ */
3563: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3564: /* for(i=1; i<=nlstate+ndeath; i++) { */
3565: /* printf("%d pmmij ",i); */
3566: /* for(j=1;j<=nlstate+ndeath;j++) { */
3567: /* printf("%f ",pmmij[i][j]); */
3568: /* } */
3569: /* printf(" oldm "); */
3570: /* for(j=1;j<=nlstate+ndeath;j++) { */
3571: /* printf("%f ",oldm[i][j]); */
3572: /* } */
3573: /* printf("\n"); */
3574: /* } */
3575: /* } */
3576: savm=oldm;
3577: oldm=newm;
3578: }
3579: for(i=1; i<=nlstate+ndeath; i++)
3580: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3581: po[i][j][h]=newm[i][j];
1.268 brouard 3582: /* if(h==nhstepm) */
3583: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3584: }
1.268 brouard 3585: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3586: } /* end h */
1.268 brouard 3587: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3588: return po;
3589: }
3590:
3591:
1.162 brouard 3592: #ifdef NLOPT
3593: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3594: double fret;
3595: double *xt;
3596: int j;
3597: myfunc_data *d2 = (myfunc_data *) pd;
3598: /* xt = (p1-1); */
3599: xt=vector(1,n);
3600: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3601:
3602: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3603: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3604: printf("Function = %.12lf ",fret);
3605: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3606: printf("\n");
3607: free_vector(xt,1,n);
3608: return fret;
3609: }
3610: #endif
1.126 brouard 3611:
3612: /*************** log-likelihood *************/
3613: double func( double *x)
3614: {
1.226 brouard 3615: int i, ii, j, k, mi, d, kk;
3616: int ioffset=0;
3617: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3618: double **out;
3619: double lli; /* Individual log likelihood */
3620: int s1, s2;
1.228 brouard 3621: 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 3622: double bbh, survp;
3623: long ipmx;
3624: double agexact;
3625: /*extern weight */
3626: /* We are differentiating ll according to initial status */
3627: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3628: /*for(i=1;i<imx;i++)
3629: printf(" %d\n",s[4][i]);
3630: */
1.162 brouard 3631:
1.226 brouard 3632: ++countcallfunc;
1.162 brouard 3633:
1.226 brouard 3634: cov[1]=1.;
1.126 brouard 3635:
1.226 brouard 3636: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3637: ioffset=0;
1.226 brouard 3638: if(mle==1){
3639: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3640: /* Computes the values of the ncovmodel covariates of the model
3641: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3642: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3643: to be observed in j being in i according to the model.
3644: */
1.243 brouard 3645: ioffset=2+nagesqr ;
1.233 brouard 3646: /* Fixed */
1.319 brouard 3647: for (k=1; k<=ncovf;k++){ /* For each fixed covariate dummu or quant or prod */
3648: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
3649: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
3650: /* 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 3651: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.319 brouard 3652: 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)*/
3653: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 3654: }
1.226 brouard 3655: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 3656: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 3657: has been calculated etc */
3658: /* For an individual i, wav[i] gives the number of effective waves */
3659: /* We compute the contribution to Likelihood of each effective transition
3660: mw[mi][i] is real wave of the mi th effectve wave */
3661: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3662: s2=s[mw[mi+1][i]][i];
3663: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3664: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3665: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3666: */
3667: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 3668: 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*/
3669: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? */
1.242 brouard 3670: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3671: }
3672: for (ii=1;ii<=nlstate+ndeath;ii++)
3673: for (j=1;j<=nlstate+ndeath;j++){
3674: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3675: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3676: }
3677: for(d=0; d<dh[mi][i]; d++){
3678: newm=savm;
3679: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3680: cov[2]=agexact;
3681: if(nagesqr==1)
3682: cov[3]= agexact*agexact; /* Should be changed here */
3683: for (kk=1; kk<=cptcovage;kk++) {
1.318 brouard 3684: if(!FixedV[Tvar[Tage[kk]]])
3685: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
3686: else
3687: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3688: }
3689: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3690: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3691: savm=oldm;
3692: oldm=newm;
3693: } /* end mult */
3694:
3695: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3696: /* But now since version 0.9 we anticipate for bias at large stepm.
3697: * If stepm is larger than one month (smallest stepm) and if the exact delay
3698: * (in months) between two waves is not a multiple of stepm, we rounded to
3699: * the nearest (and in case of equal distance, to the lowest) interval but now
3700: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3701: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3702: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3703: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3704: * -stepm/2 to stepm/2 .
3705: * For stepm=1 the results are the same as for previous versions of Imach.
3706: * For stepm > 1 the results are less biased than in previous versions.
3707: */
1.234 brouard 3708: s1=s[mw[mi][i]][i];
3709: s2=s[mw[mi+1][i]][i];
3710: bbh=(double)bh[mi][i]/(double)stepm;
3711: /* bias bh is positive if real duration
3712: * is higher than the multiple of stepm and negative otherwise.
3713: */
3714: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3715: if( s2 > nlstate){
3716: /* i.e. if s2 is a death state and if the date of death is known
3717: then the contribution to the likelihood is the probability to
3718: die between last step unit time and current step unit time,
3719: which is also equal to probability to die before dh
3720: minus probability to die before dh-stepm .
3721: In version up to 0.92 likelihood was computed
3722: as if date of death was unknown. Death was treated as any other
3723: health state: the date of the interview describes the actual state
3724: and not the date of a change in health state. The former idea was
3725: to consider that at each interview the state was recorded
3726: (healthy, disable or death) and IMaCh was corrected; but when we
3727: introduced the exact date of death then we should have modified
3728: the contribution of an exact death to the likelihood. This new
3729: contribution is smaller and very dependent of the step unit
3730: stepm. It is no more the probability to die between last interview
3731: and month of death but the probability to survive from last
3732: interview up to one month before death multiplied by the
3733: probability to die within a month. Thanks to Chris
3734: Jackson for correcting this bug. Former versions increased
3735: mortality artificially. The bad side is that we add another loop
3736: which slows down the processing. The difference can be up to 10%
3737: lower mortality.
3738: */
3739: /* If, at the beginning of the maximization mostly, the
3740: cumulative probability or probability to be dead is
3741: constant (ie = 1) over time d, the difference is equal to
3742: 0. out[s1][3] = savm[s1][3]: probability, being at state
3743: s1 at precedent wave, to be dead a month before current
3744: wave is equal to probability, being at state s1 at
3745: precedent wave, to be dead at mont of the current
3746: wave. Then the observed probability (that this person died)
3747: is null according to current estimated parameter. In fact,
3748: it should be very low but not zero otherwise the log go to
3749: infinity.
3750: */
1.183 brouard 3751: /* #ifdef INFINITYORIGINAL */
3752: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3753: /* #else */
3754: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3755: /* lli=log(mytinydouble); */
3756: /* else */
3757: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3758: /* #endif */
1.226 brouard 3759: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3760:
1.226 brouard 3761: } else if ( s2==-1 ) { /* alive */
3762: for (j=1,survp=0. ; j<=nlstate; j++)
3763: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3764: /*survp += out[s1][j]; */
3765: lli= log(survp);
3766: }
3767: else if (s2==-4) {
3768: for (j=3,survp=0. ; j<=nlstate; j++)
3769: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3770: lli= log(survp);
3771: }
3772: else if (s2==-5) {
3773: for (j=1,survp=0. ; j<=2; j++)
3774: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3775: lli= log(survp);
3776: }
3777: else{
3778: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3779: /* 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 */
3780: }
3781: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3782: /*if(lli ==000.0)*/
3783: /*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); */
3784: ipmx +=1;
3785: sw += weight[i];
3786: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3787: /* if (lli < log(mytinydouble)){ */
3788: /* 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); */
3789: /* 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]); */
3790: /* } */
3791: } /* end of wave */
3792: } /* end of individual */
3793: } else if(mle==2){
3794: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 3795: ioffset=2+nagesqr ;
3796: for (k=1; k<=ncovf;k++)
3797: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 3798: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 3799: for(k=1; k <= ncovv ; k++){
3800: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3801: }
1.226 brouard 3802: for (ii=1;ii<=nlstate+ndeath;ii++)
3803: for (j=1;j<=nlstate+ndeath;j++){
3804: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3805: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3806: }
3807: for(d=0; d<=dh[mi][i]; d++){
3808: newm=savm;
3809: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3810: cov[2]=agexact;
3811: if(nagesqr==1)
3812: cov[3]= agexact*agexact;
3813: for (kk=1; kk<=cptcovage;kk++) {
3814: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3815: }
3816: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3817: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3818: savm=oldm;
3819: oldm=newm;
3820: } /* end mult */
3821:
3822: s1=s[mw[mi][i]][i];
3823: s2=s[mw[mi+1][i]][i];
3824: bbh=(double)bh[mi][i]/(double)stepm;
3825: 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 */
3826: ipmx +=1;
3827: sw += weight[i];
3828: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3829: } /* end of wave */
3830: } /* end of individual */
3831: } else if(mle==3){ /* exponential inter-extrapolation */
3832: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3833: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3834: for(mi=1; mi<= wav[i]-1; mi++){
3835: for (ii=1;ii<=nlstate+ndeath;ii++)
3836: for (j=1;j<=nlstate+ndeath;j++){
3837: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3838: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3839: }
3840: for(d=0; d<dh[mi][i]; d++){
3841: newm=savm;
3842: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3843: cov[2]=agexact;
3844: if(nagesqr==1)
3845: cov[3]= agexact*agexact;
3846: for (kk=1; kk<=cptcovage;kk++) {
3847: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3848: }
3849: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3850: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3851: savm=oldm;
3852: oldm=newm;
3853: } /* end mult */
3854:
3855: s1=s[mw[mi][i]][i];
3856: s2=s[mw[mi+1][i]][i];
3857: bbh=(double)bh[mi][i]/(double)stepm;
3858: 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 */
3859: ipmx +=1;
3860: sw += weight[i];
3861: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3862: } /* end of wave */
3863: } /* end of individual */
3864: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3865: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3866: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3867: for(mi=1; mi<= wav[i]-1; mi++){
3868: for (ii=1;ii<=nlstate+ndeath;ii++)
3869: for (j=1;j<=nlstate+ndeath;j++){
3870: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3871: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3872: }
3873: for(d=0; d<dh[mi][i]; d++){
3874: newm=savm;
3875: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3876: cov[2]=agexact;
3877: if(nagesqr==1)
3878: cov[3]= agexact*agexact;
3879: for (kk=1; kk<=cptcovage;kk++) {
3880: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3881: }
1.126 brouard 3882:
1.226 brouard 3883: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3884: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3885: savm=oldm;
3886: oldm=newm;
3887: } /* end mult */
3888:
3889: s1=s[mw[mi][i]][i];
3890: s2=s[mw[mi+1][i]][i];
3891: if( s2 > nlstate){
3892: lli=log(out[s1][s2] - savm[s1][s2]);
3893: } else if ( s2==-1 ) { /* alive */
3894: for (j=1,survp=0. ; j<=nlstate; j++)
3895: survp += out[s1][j];
3896: lli= log(survp);
3897: }else{
3898: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3899: }
3900: ipmx +=1;
3901: sw += weight[i];
3902: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3903: /* 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 3904: } /* end of wave */
3905: } /* end of individual */
3906: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3907: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3908: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3909: for(mi=1; mi<= wav[i]-1; mi++){
3910: for (ii=1;ii<=nlstate+ndeath;ii++)
3911: for (j=1;j<=nlstate+ndeath;j++){
3912: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3913: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3914: }
3915: for(d=0; d<dh[mi][i]; d++){
3916: newm=savm;
3917: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3918: cov[2]=agexact;
3919: if(nagesqr==1)
3920: cov[3]= agexact*agexact;
3921: for (kk=1; kk<=cptcovage;kk++) {
3922: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3923: }
1.126 brouard 3924:
1.226 brouard 3925: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3926: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3927: savm=oldm;
3928: oldm=newm;
3929: } /* end mult */
3930:
3931: s1=s[mw[mi][i]][i];
3932: s2=s[mw[mi+1][i]][i];
3933: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3934: ipmx +=1;
3935: sw += weight[i];
3936: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3937: /*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]);*/
3938: } /* end of wave */
3939: } /* end of individual */
3940: } /* End of if */
3941: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3942: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3943: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3944: return -l;
1.126 brouard 3945: }
3946:
3947: /*************** log-likelihood *************/
3948: double funcone( double *x)
3949: {
1.228 brouard 3950: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3951: int i, ii, j, k, mi, d, kk;
1.228 brouard 3952: int ioffset=0;
1.131 brouard 3953: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3954: double **out;
3955: double lli; /* Individual log likelihood */
3956: double llt;
3957: int s1, s2;
1.228 brouard 3958: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3959:
1.126 brouard 3960: double bbh, survp;
1.187 brouard 3961: double agexact;
1.214 brouard 3962: double agebegin, ageend;
1.126 brouard 3963: /*extern weight */
3964: /* We are differentiating ll according to initial status */
3965: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3966: /*for(i=1;i<imx;i++)
3967: printf(" %d\n",s[4][i]);
3968: */
3969: cov[1]=1.;
3970:
3971: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3972: ioffset=0;
3973: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3974: /* ioffset=2+nagesqr+cptcovage; */
3975: ioffset=2+nagesqr;
1.232 brouard 3976: /* Fixed */
1.224 brouard 3977: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3978: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.311 brouard 3979: 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 3980: 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)*/
3981: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3982: /* cov[2+6]=covar[Tvar[6]][i]; */
3983: /* cov[2+6]=covar[2][i]; V2 */
3984: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3985: /* cov[2+7]=covar[Tvar[7]][i]; */
3986: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3987: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3988: /* cov[2+9]=covar[Tvar[9]][i]; */
3989: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3990: }
1.232 brouard 3991: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3992: /* 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?)*\/ */
3993: /* } */
1.231 brouard 3994: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3995: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3996: /* } */
1.225 brouard 3997:
1.233 brouard 3998:
3999: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 4000: /* Wave varying (but not age varying) */
4001: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 4002: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
4003: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
4004: }
1.232 brouard 4005: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 4006: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4007: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
4008: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
4009: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
4010: /* 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 4011: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4012: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4013: /* /\* 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]); *\/ */
4014: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4015: /* } */
1.126 brouard 4016: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4017: for (j=1;j<=nlstate+ndeath;j++){
4018: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4019: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4020: }
1.214 brouard 4021:
4022: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4023: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4024: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4025: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4026: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4027: and mw[mi+1][i]. dh depends on stepm.*/
4028: newm=savm;
1.247 brouard 4029: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4030: cov[2]=agexact;
4031: if(nagesqr==1)
4032: cov[3]= agexact*agexact;
4033: for (kk=1; kk<=cptcovage;kk++) {
4034: if(!FixedV[Tvar[Tage[kk]]])
4035: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4036: else
4037: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
4038: }
4039: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4040: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4041: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4042: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4043: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4044: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4045: savm=oldm;
4046: oldm=newm;
1.126 brouard 4047: } /* end mult */
4048:
4049: s1=s[mw[mi][i]][i];
4050: s2=s[mw[mi+1][i]][i];
1.217 brouard 4051: /* if(s2==-1){ */
1.268 brouard 4052: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4053: /* /\* exit(1); *\/ */
4054: /* } */
1.126 brouard 4055: bbh=(double)bh[mi][i]/(double)stepm;
4056: /* bias is positive if real duration
4057: * is higher than the multiple of stepm and negative otherwise.
4058: */
4059: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4060: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4061: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4062: for (j=1,survp=0. ; j<=nlstate; j++)
4063: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4064: lli= log(survp);
1.126 brouard 4065: }else if (mle==1){
1.242 brouard 4066: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4067: } else if(mle==2){
1.242 brouard 4068: 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 4069: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4070: 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 4071: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4072: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4073: } else{ /* mle=0 back to 1 */
1.242 brouard 4074: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4075: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4076: } /* End of if */
4077: ipmx +=1;
4078: sw += weight[i];
4079: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 4080: /*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 4081: if(globpr){
1.246 brouard 4082: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4083: %11.6f %11.6f %11.6f ", \
1.242 brouard 4084: 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 4085: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 4086: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4087: llt +=ll[k]*gipmx/gsw;
4088: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
4089: }
4090: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 4091: }
1.232 brouard 4092: } /* end of wave */
4093: } /* end of individual */
4094: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4095: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4096: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4097: if(globpr==0){ /* First time we count the contributions and weights */
4098: gipmx=ipmx;
4099: gsw=sw;
4100: }
4101: return -l;
1.126 brouard 4102: }
4103:
4104:
4105: /*************** function likelione ***********/
1.292 brouard 4106: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4107: {
4108: /* This routine should help understanding what is done with
4109: the selection of individuals/waves and
4110: to check the exact contribution to the likelihood.
4111: Plotting could be done.
4112: */
4113: int k;
4114:
4115: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4116: strcpy(fileresilk,"ILK_");
1.202 brouard 4117: strcat(fileresilk,fileresu);
1.126 brouard 4118: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4119: printf("Problem with resultfile: %s\n", fileresilk);
4120: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4121: }
1.214 brouard 4122: 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");
4123: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4124: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4125: for(k=1; k<=nlstate; k++)
4126: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
4127: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
4128: }
4129:
1.292 brouard 4130: *fretone=(*func)(p);
1.126 brouard 4131: if(*globpri !=0){
4132: fclose(ficresilk);
1.205 brouard 4133: if (mle ==0)
4134: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4135: else if(mle >=1)
4136: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4137: 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 4138: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4139:
4140: for (k=1; k<= nlstate ; k++) {
1.211 brouard 4141: 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 4142: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4143: }
1.207 brouard 4144: 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 4145: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4146: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 4147: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4148: fflush(fichtm);
1.205 brouard 4149: }
1.126 brouard 4150: return;
4151: }
4152:
4153:
4154: /*********** Maximum Likelihood Estimation ***************/
4155:
4156: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4157: {
1.319 brouard 4158: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4159: double **xi;
4160: double fret;
4161: double fretone; /* Only one call to likelihood */
4162: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4163:
4164: #ifdef NLOPT
4165: int creturn;
4166: nlopt_opt opt;
4167: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4168: double *lb;
4169: double minf; /* the minimum objective value, upon return */
4170: double * p1; /* Shifted parameters from 0 instead of 1 */
4171: myfunc_data dinst, *d = &dinst;
4172: #endif
4173:
4174:
1.126 brouard 4175: xi=matrix(1,npar,1,npar);
4176: for (i=1;i<=npar;i++)
4177: for (j=1;j<=npar;j++)
4178: xi[i][j]=(i==j ? 1.0 : 0.0);
4179: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4180: strcpy(filerespow,"POW_");
1.126 brouard 4181: strcat(filerespow,fileres);
4182: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4183: printf("Problem with resultfile: %s\n", filerespow);
4184: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4185: }
4186: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4187: for (i=1;i<=nlstate;i++)
4188: for(j=1;j<=nlstate+ndeath;j++)
4189: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4190: fprintf(ficrespow,"\n");
1.162 brouard 4191: #ifdef POWELL
1.319 brouard 4192: #ifdef LINMINORIGINAL
4193: #else /* LINMINORIGINAL */
4194:
4195: flatdir=ivector(1,npar);
4196: for (j=1;j<=npar;j++) flatdir[j]=0;
4197: #endif /*LINMINORIGINAL */
4198:
4199: #ifdef FLATSUP
4200: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4201: /* reorganizing p by suppressing flat directions */
4202: for(i=1, jk=1; i <=nlstate; i++){
4203: for(k=1; k <=(nlstate+ndeath); k++){
4204: if (k != i) {
4205: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4206: if(flatdir[jk]==1){
4207: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4208: }
4209: for(j=1; j <=ncovmodel; j++){
4210: printf("%12.7f ",p[jk]);
4211: jk++;
4212: }
4213: printf("\n");
4214: }
4215: }
4216: }
4217: /* skipping */
4218: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4219: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
4220: for(k=1; k <=(nlstate+ndeath); k++){
4221: if (k != i) {
4222: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4223: if(flatdir[jk]==1){
4224: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
4225: for(j=1; j <=ncovmodel; jk++,j++){
4226: printf(" p[%d]=%12.7f",jk, p[jk]);
4227: /*q[jjk]=p[jk];*/
4228: }
4229: }else{
4230: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
4231: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
4232: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
4233: /*q[jjk]=p[jk];*/
4234: }
4235: }
4236: printf("\n");
4237: }
4238: fflush(stdout);
4239: }
4240: }
4241: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4242: #else /* FLATSUP */
1.126 brouard 4243: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 4244: #endif /* FLATSUP */
4245:
4246: #ifdef LINMINORIGINAL
4247: #else
4248: free_ivector(flatdir,1,npar);
4249: #endif /* LINMINORIGINAL*/
4250: #endif /* POWELL */
1.126 brouard 4251:
1.162 brouard 4252: #ifdef NLOPT
4253: #ifdef NEWUOA
4254: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4255: #else
4256: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4257: #endif
4258: lb=vector(0,npar-1);
4259: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4260: nlopt_set_lower_bounds(opt, lb);
4261: nlopt_set_initial_step1(opt, 0.1);
4262:
4263: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4264: d->function = func;
4265: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4266: nlopt_set_min_objective(opt, myfunc, d);
4267: nlopt_set_xtol_rel(opt, ftol);
4268: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4269: printf("nlopt failed! %d\n",creturn);
4270: }
4271: else {
4272: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4273: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4274: iter=1; /* not equal */
4275: }
4276: nlopt_destroy(opt);
4277: #endif
1.319 brouard 4278: #ifdef FLATSUP
4279: /* npared = npar -flatd/ncovmodel; */
4280: /* xired= matrix(1,npared,1,npared); */
4281: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
4282: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
4283: /* free_matrix(xire,1,npared,1,npared); */
4284: #else /* FLATSUP */
4285: #endif /* FLATSUP */
1.126 brouard 4286: free_matrix(xi,1,npar,1,npar);
4287: fclose(ficrespow);
1.203 brouard 4288: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4289: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4290: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4291:
4292: }
4293:
4294: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4295: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4296: {
4297: double **a,**y,*x,pd;
1.203 brouard 4298: /* double **hess; */
1.164 brouard 4299: int i, j;
1.126 brouard 4300: int *indx;
4301:
4302: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4303: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4304: void lubksb(double **a, int npar, int *indx, double b[]) ;
4305: void ludcmp(double **a, int npar, int *indx, double *d) ;
4306: double gompertz(double p[]);
1.203 brouard 4307: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4308:
4309: printf("\nCalculation of the hessian matrix. Wait...\n");
4310: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4311: for (i=1;i<=npar;i++){
1.203 brouard 4312: printf("%d-",i);fflush(stdout);
4313: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4314:
4315: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4316:
4317: /* printf(" %f ",p[i]);
4318: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4319: }
4320:
4321: for (i=1;i<=npar;i++) {
4322: for (j=1;j<=npar;j++) {
4323: if (j>i) {
1.203 brouard 4324: printf(".%d-%d",i,j);fflush(stdout);
4325: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4326: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4327:
4328: hess[j][i]=hess[i][j];
4329: /*printf(" %lf ",hess[i][j]);*/
4330: }
4331: }
4332: }
4333: printf("\n");
4334: fprintf(ficlog,"\n");
4335:
4336: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4337: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4338:
4339: a=matrix(1,npar,1,npar);
4340: y=matrix(1,npar,1,npar);
4341: x=vector(1,npar);
4342: indx=ivector(1,npar);
4343: for (i=1;i<=npar;i++)
4344: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4345: ludcmp(a,npar,indx,&pd);
4346:
4347: for (j=1;j<=npar;j++) {
4348: for (i=1;i<=npar;i++) x[i]=0;
4349: x[j]=1;
4350: lubksb(a,npar,indx,x);
4351: for (i=1;i<=npar;i++){
4352: matcov[i][j]=x[i];
4353: }
4354: }
4355:
4356: printf("\n#Hessian matrix#\n");
4357: fprintf(ficlog,"\n#Hessian matrix#\n");
4358: for (i=1;i<=npar;i++) {
4359: for (j=1;j<=npar;j++) {
1.203 brouard 4360: printf("%.6e ",hess[i][j]);
4361: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4362: }
4363: printf("\n");
4364: fprintf(ficlog,"\n");
4365: }
4366:
1.203 brouard 4367: /* printf("\n#Covariance matrix#\n"); */
4368: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4369: /* for (i=1;i<=npar;i++) { */
4370: /* for (j=1;j<=npar;j++) { */
4371: /* printf("%.6e ",matcov[i][j]); */
4372: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4373: /* } */
4374: /* printf("\n"); */
4375: /* fprintf(ficlog,"\n"); */
4376: /* } */
4377:
1.126 brouard 4378: /* Recompute Inverse */
1.203 brouard 4379: /* for (i=1;i<=npar;i++) */
4380: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4381: /* ludcmp(a,npar,indx,&pd); */
4382:
4383: /* printf("\n#Hessian matrix recomputed#\n"); */
4384:
4385: /* for (j=1;j<=npar;j++) { */
4386: /* for (i=1;i<=npar;i++) x[i]=0; */
4387: /* x[j]=1; */
4388: /* lubksb(a,npar,indx,x); */
4389: /* for (i=1;i<=npar;i++){ */
4390: /* y[i][j]=x[i]; */
4391: /* printf("%.3e ",y[i][j]); */
4392: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4393: /* } */
4394: /* printf("\n"); */
4395: /* fprintf(ficlog,"\n"); */
4396: /* } */
4397:
4398: /* Verifying the inverse matrix */
4399: #ifdef DEBUGHESS
4400: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4401:
1.203 brouard 4402: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4403: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4404:
4405: for (j=1;j<=npar;j++) {
4406: for (i=1;i<=npar;i++){
1.203 brouard 4407: printf("%.2f ",y[i][j]);
4408: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4409: }
4410: printf("\n");
4411: fprintf(ficlog,"\n");
4412: }
1.203 brouard 4413: #endif
1.126 brouard 4414:
4415: free_matrix(a,1,npar,1,npar);
4416: free_matrix(y,1,npar,1,npar);
4417: free_vector(x,1,npar);
4418: free_ivector(indx,1,npar);
1.203 brouard 4419: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4420:
4421:
4422: }
4423:
4424: /*************** hessian matrix ****************/
4425: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4426: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4427: int i;
4428: int l=1, lmax=20;
1.203 brouard 4429: double k1,k2, res, fx;
1.132 brouard 4430: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4431: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4432: int k=0,kmax=10;
4433: double l1;
4434:
4435: fx=func(x);
4436: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4437: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4438: l1=pow(10,l);
4439: delts=delt;
4440: for(k=1 ; k <kmax; k=k+1){
4441: delt = delta*(l1*k);
4442: p2[theta]=x[theta] +delt;
1.145 brouard 4443: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4444: p2[theta]=x[theta]-delt;
4445: k2=func(p2)-fx;
4446: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4447: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4448:
1.203 brouard 4449: #ifdef DEBUGHESSII
1.126 brouard 4450: 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);
4451: 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);
4452: #endif
4453: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4454: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4455: k=kmax;
4456: }
4457: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4458: k=kmax; l=lmax*10;
1.126 brouard 4459: }
4460: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4461: delts=delt;
4462: }
1.203 brouard 4463: } /* End loop k */
1.126 brouard 4464: }
4465: delti[theta]=delts;
4466: return res;
4467:
4468: }
4469:
1.203 brouard 4470: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4471: {
4472: int i;
1.164 brouard 4473: int l=1, lmax=20;
1.126 brouard 4474: double k1,k2,k3,k4,res,fx;
1.132 brouard 4475: double p2[MAXPARM+1];
1.203 brouard 4476: int k, kmax=1;
4477: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4478:
4479: int firstime=0;
1.203 brouard 4480:
1.126 brouard 4481: fx=func(x);
1.203 brouard 4482: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4483: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4484: p2[thetai]=x[thetai]+delti[thetai]*k;
4485: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4486: k1=func(p2)-fx;
4487:
1.203 brouard 4488: p2[thetai]=x[thetai]+delti[thetai]*k;
4489: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4490: k2=func(p2)-fx;
4491:
1.203 brouard 4492: p2[thetai]=x[thetai]-delti[thetai]*k;
4493: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4494: k3=func(p2)-fx;
4495:
1.203 brouard 4496: p2[thetai]=x[thetai]-delti[thetai]*k;
4497: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4498: k4=func(p2)-fx;
1.203 brouard 4499: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4500: if(k1*k2*k3*k4 <0.){
1.208 brouard 4501: firstime=1;
1.203 brouard 4502: kmax=kmax+10;
1.208 brouard 4503: }
4504: if(kmax >=10 || firstime ==1){
1.246 brouard 4505: 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);
4506: 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 4507: 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);
4508: 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);
4509: }
4510: #ifdef DEBUGHESSIJ
4511: v1=hess[thetai][thetai];
4512: v2=hess[thetaj][thetaj];
4513: cv12=res;
4514: /* Computing eigen value of Hessian matrix */
4515: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4516: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4517: if ((lc2 <0) || (lc1 <0) ){
4518: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4519: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4520: 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);
4521: 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);
4522: }
1.126 brouard 4523: #endif
4524: }
4525: return res;
4526: }
4527:
1.203 brouard 4528: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4529: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4530: /* { */
4531: /* int i; */
4532: /* int l=1, lmax=20; */
4533: /* double k1,k2,k3,k4,res,fx; */
4534: /* double p2[MAXPARM+1]; */
4535: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4536: /* int k=0,kmax=10; */
4537: /* double l1; */
4538:
4539: /* fx=func(x); */
4540: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4541: /* l1=pow(10,l); */
4542: /* delts=delt; */
4543: /* for(k=1 ; k <kmax; k=k+1){ */
4544: /* delt = delti*(l1*k); */
4545: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4546: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4547: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4548: /* k1=func(p2)-fx; */
4549:
4550: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4551: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4552: /* k2=func(p2)-fx; */
4553:
4554: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4555: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4556: /* k3=func(p2)-fx; */
4557:
4558: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4559: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4560: /* k4=func(p2)-fx; */
4561: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4562: /* #ifdef DEBUGHESSIJ */
4563: /* 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); */
4564: /* 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); */
4565: /* #endif */
4566: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4567: /* k=kmax; */
4568: /* } */
4569: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4570: /* k=kmax; l=lmax*10; */
4571: /* } */
4572: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4573: /* delts=delt; */
4574: /* } */
4575: /* } /\* End loop k *\/ */
4576: /* } */
4577: /* delti[theta]=delts; */
4578: /* return res; */
4579: /* } */
4580:
4581:
1.126 brouard 4582: /************** Inverse of matrix **************/
4583: void ludcmp(double **a, int n, int *indx, double *d)
4584: {
4585: int i,imax,j,k;
4586: double big,dum,sum,temp;
4587: double *vv;
4588:
4589: vv=vector(1,n);
4590: *d=1.0;
4591: for (i=1;i<=n;i++) {
4592: big=0.0;
4593: for (j=1;j<=n;j++)
4594: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4595: if (big == 0.0){
4596: printf(" Singular Hessian matrix at row %d:\n",i);
4597: for (j=1;j<=n;j++) {
4598: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4599: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4600: }
4601: fflush(ficlog);
4602: fclose(ficlog);
4603: nrerror("Singular matrix in routine ludcmp");
4604: }
1.126 brouard 4605: vv[i]=1.0/big;
4606: }
4607: for (j=1;j<=n;j++) {
4608: for (i=1;i<j;i++) {
4609: sum=a[i][j];
4610: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4611: a[i][j]=sum;
4612: }
4613: big=0.0;
4614: for (i=j;i<=n;i++) {
4615: sum=a[i][j];
4616: for (k=1;k<j;k++)
4617: sum -= a[i][k]*a[k][j];
4618: a[i][j]=sum;
4619: if ( (dum=vv[i]*fabs(sum)) >= big) {
4620: big=dum;
4621: imax=i;
4622: }
4623: }
4624: if (j != imax) {
4625: for (k=1;k<=n;k++) {
4626: dum=a[imax][k];
4627: a[imax][k]=a[j][k];
4628: a[j][k]=dum;
4629: }
4630: *d = -(*d);
4631: vv[imax]=vv[j];
4632: }
4633: indx[j]=imax;
4634: if (a[j][j] == 0.0) a[j][j]=TINY;
4635: if (j != n) {
4636: dum=1.0/(a[j][j]);
4637: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4638: }
4639: }
4640: free_vector(vv,1,n); /* Doesn't work */
4641: ;
4642: }
4643:
4644: void lubksb(double **a, int n, int *indx, double b[])
4645: {
4646: int i,ii=0,ip,j;
4647: double sum;
4648:
4649: for (i=1;i<=n;i++) {
4650: ip=indx[i];
4651: sum=b[ip];
4652: b[ip]=b[i];
4653: if (ii)
4654: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4655: else if (sum) ii=i;
4656: b[i]=sum;
4657: }
4658: for (i=n;i>=1;i--) {
4659: sum=b[i];
4660: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4661: b[i]=sum/a[i][i];
4662: }
4663: }
4664:
4665: void pstamp(FILE *fichier)
4666: {
1.196 brouard 4667: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4668: }
4669:
1.297 brouard 4670: void date2dmy(double date,double *day, double *month, double *year){
4671: double yp=0., yp1=0., yp2=0.;
4672:
4673: yp1=modf(date,&yp);/* extracts integral of date in yp and
4674: fractional in yp1 */
4675: *year=yp;
4676: yp2=modf((yp1*12),&yp);
4677: *month=yp;
4678: yp1=modf((yp2*30.5),&yp);
4679: *day=yp;
4680: if(*day==0) *day=1;
4681: if(*month==0) *month=1;
4682: }
4683:
1.253 brouard 4684:
4685:
1.126 brouard 4686: /************ Frequencies ********************/
1.251 brouard 4687: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4688: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4689: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4690: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4691:
1.265 brouard 4692: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4693: int iind=0, iage=0;
4694: int mi; /* Effective wave */
4695: int first;
4696: double ***freq; /* Frequencies */
1.268 brouard 4697: 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 */
4698: 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 4699: double *meanq, *stdq, *idq;
1.226 brouard 4700: double **meanqt;
4701: double *pp, **prop, *posprop, *pospropt;
4702: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4703: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4704: double agebegin, ageend;
4705:
4706: pp=vector(1,nlstate);
1.251 brouard 4707: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4708: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4709: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4710: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4711: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4712: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4713: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4714: meanqt=matrix(1,lastpass,1,nqtveff);
4715: strcpy(fileresp,"P_");
4716: strcat(fileresp,fileresu);
4717: /*strcat(fileresphtm,fileresu);*/
4718: if((ficresp=fopen(fileresp,"w"))==NULL) {
4719: printf("Problem with prevalence resultfile: %s\n", fileresp);
4720: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4721: exit(0);
4722: }
1.240 brouard 4723:
1.226 brouard 4724: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4725: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4726: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4727: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4728: fflush(ficlog);
4729: exit(70);
4730: }
4731: else{
4732: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4733: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4734: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4735: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4736: }
1.319 brouard 4737: 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 4738:
1.226 brouard 4739: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4740: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4741: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4742: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4743: fflush(ficlog);
4744: exit(70);
1.240 brouard 4745: } else{
1.226 brouard 4746: 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 4747: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4748: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4749: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4750: }
1.319 brouard 4751: 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 4752:
1.253 brouard 4753: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4754: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4755: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4756: j1=0;
1.126 brouard 4757:
1.227 brouard 4758: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4759: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4760: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4761:
4762:
1.226 brouard 4763: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4764: reference=low_education V1=0,V2=0
4765: med_educ V1=1 V2=0,
4766: high_educ V1=0 V2=1
4767: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4768: */
1.249 brouard 4769: dateintsum=0;
4770: k2cpt=0;
4771:
1.253 brouard 4772: if(cptcoveff == 0 )
1.265 brouard 4773: nl=1; /* Constant and age model only */
1.253 brouard 4774: else
4775: nl=2;
1.265 brouard 4776:
4777: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4778: /* Loop on nj=1 or 2 if dummy covariates j!=0
4779: * Loop on j1(1 to 2**cptcoveff) covariate combination
4780: * freq[s1][s2][iage] =0.
4781: * Loop on iind
4782: * ++freq[s1][s2][iage] weighted
4783: * end iind
4784: * if covariate and j!0
4785: * headers Variable on one line
4786: * endif cov j!=0
4787: * header of frequency table by age
4788: * Loop on age
4789: * pp[s1]+=freq[s1][s2][iage] weighted
4790: * pos+=freq[s1][s2][iage] weighted
4791: * Loop on s1 initial state
4792: * fprintf(ficresp
4793: * end s1
4794: * end age
4795: * if j!=0 computes starting values
4796: * end compute starting values
4797: * end j1
4798: * end nl
4799: */
1.253 brouard 4800: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4801: if(nj==1)
4802: j=0; /* First pass for the constant */
1.265 brouard 4803: else{
1.253 brouard 4804: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4805: }
1.251 brouard 4806: first=1;
1.265 brouard 4807: 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 4808: posproptt=0.;
4809: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4810: scanf("%d", i);*/
4811: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4812: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4813: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4814: freq[i][s2][m]=0;
1.251 brouard 4815:
4816: for (i=1; i<=nlstate; i++) {
1.240 brouard 4817: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4818: prop[i][m]=0;
4819: posprop[i]=0;
4820: pospropt[i]=0;
4821: }
1.283 brouard 4822: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4823: idq[z1]=0.;
4824: meanq[z1]=0.;
4825: stdq[z1]=0.;
1.283 brouard 4826: }
4827: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4828: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4829: /* meanqt[m][z1]=0.; */
4830: /* } */
4831: /* } */
1.251 brouard 4832: /* dateintsum=0; */
4833: /* k2cpt=0; */
4834:
1.265 brouard 4835: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4836: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4837: bool=1;
4838: if(j !=0){
4839: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4840: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4841: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4842: /* if(Tvaraff[z1] ==-20){ */
4843: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4844: /* }else if(Tvaraff[z1] ==-10){ */
4845: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4846: /* }else */
4847: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4848: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4849: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4850: /* 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",
4851: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4852: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4853: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4854: } /* Onlyf fixed */
4855: } /* end z1 */
4856: } /* cptcovn > 0 */
4857: } /* end any */
4858: }/* end j==0 */
1.265 brouard 4859: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4860: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4861: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4862: m=mw[mi][iind];
4863: if(j!=0){
4864: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4865: for (z1=1; z1<=cptcoveff; z1++) {
4866: if( Fixed[Tmodelind[z1]]==1){
4867: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4868: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4869: value is -1, we don't select. It differs from the
4870: constant and age model which counts them. */
4871: bool=0; /* not selected */
4872: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4873: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4874: bool=0;
4875: }
4876: }
4877: }
4878: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4879: } /* end j==0 */
4880: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4881: if(bool==1){ /*Selected */
1.251 brouard 4882: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4883: and mw[mi+1][iind]. dh depends on stepm. */
4884: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4885: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4886: if(m >=firstpass && m <=lastpass){
4887: k2=anint[m][iind]+(mint[m][iind]/12.);
4888: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4889: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4890: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4891: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4892: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4893: if (m<lastpass) {
4894: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4895: /* 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]); */
4896: if(s[m][iind]==-1)
4897: 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.));
4898: 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 4899: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
4900: if(!isnan(covar[ncovcol+z1][iind])){
4901: idq[z1]=idq[z1]+weight[iind];
4902: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
4903: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
4904: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
4905: }
1.284 brouard 4906: }
1.251 brouard 4907: /* if((int)agev[m][iind] == 55) */
4908: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4909: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4910: 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 4911: }
1.251 brouard 4912: } /* end if between passes */
4913: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4914: dateintsum=dateintsum+k2; /* on all covariates ?*/
4915: k2cpt++;
4916: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4917: }
1.251 brouard 4918: }else{
4919: bool=1;
4920: }/* end bool 2 */
4921: } /* end m */
1.284 brouard 4922: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
4923: /* idq[z1]=idq[z1]+weight[iind]; */
4924: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
4925: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
4926: /* } */
1.251 brouard 4927: } /* end bool */
4928: } /* end iind = 1 to imx */
1.319 brouard 4929: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 4930: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4931:
4932:
4933: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4934: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4935: pstamp(ficresp);
1.251 brouard 4936: if (cptcoveff>0 && j!=0){
1.265 brouard 4937: pstamp(ficresp);
1.251 brouard 4938: printf( "\n#********** Variable ");
4939: fprintf(ficresp, "\n#********** Variable ");
4940: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4941: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4942: fprintf(ficlog, "\n#********** Variable ");
4943: for (z1=1; z1<=cptcoveff; z1++){
4944: if(!FixedV[Tvaraff[z1]]){
4945: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4946: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4947: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4948: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4949: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4950: }else{
1.251 brouard 4951: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4952: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4953: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4954: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4955: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4956: }
4957: }
4958: printf( "**********\n#");
4959: fprintf(ficresp, "**********\n#");
4960: fprintf(ficresphtm, "**********</h3>\n");
4961: fprintf(ficresphtmfr, "**********</h3>\n");
4962: fprintf(ficlog, "**********\n");
4963: }
1.284 brouard 4964: /*
4965: Printing means of quantitative variables if any
4966: */
4967: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 4968: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 4969: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 4970: if(weightopt==1){
4971: printf(" Weighted mean and standard deviation of");
4972: fprintf(ficlog," Weighted mean and standard deviation of");
4973: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
4974: }
1.311 brouard 4975: /* mu = \frac{w x}{\sum w}
4976: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
4977: */
4978: 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]));
4979: 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]));
4980: 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 4981: }
4982: /* for (z1=1; z1<= nqtveff; z1++) { */
4983: /* for(m=1;m<=lastpass;m++){ */
4984: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
4985: /* } */
4986: /* } */
1.283 brouard 4987:
1.251 brouard 4988: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4989: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4990: fprintf(ficresp, " Age");
4991: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.251 brouard 4992: for(i=1; i<=nlstate;i++) {
1.265 brouard 4993: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4994: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4995: }
1.265 brouard 4996: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4997: fprintf(ficresphtm, "\n");
4998:
4999: /* Header of frequency table by age */
5000: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5001: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5002: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5003: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5004: if(s2!=0 && m!=0)
5005: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5006: }
1.226 brouard 5007: }
1.251 brouard 5008: fprintf(ficresphtmfr, "\n");
5009:
5010: /* For each age */
5011: for(iage=iagemin; iage <= iagemax+3; iage++){
5012: fprintf(ficresphtm,"<tr>");
5013: if(iage==iagemax+1){
5014: fprintf(ficlog,"1");
5015: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5016: }else if(iage==iagemax+2){
5017: fprintf(ficlog,"0");
5018: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5019: }else if(iage==iagemax+3){
5020: fprintf(ficlog,"Total");
5021: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5022: }else{
1.240 brouard 5023: if(first==1){
1.251 brouard 5024: first=0;
5025: printf("See log file for details...\n");
5026: }
5027: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5028: fprintf(ficlog,"Age %d", iage);
5029: }
1.265 brouard 5030: for(s1=1; s1 <=nlstate ; s1++){
5031: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5032: pp[s1] += freq[s1][m][iage];
1.251 brouard 5033: }
1.265 brouard 5034: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5035: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5036: pos += freq[s1][m][iage];
5037: if(pp[s1]>=1.e-10){
1.251 brouard 5038: if(first==1){
1.265 brouard 5039: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5040: }
1.265 brouard 5041: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5042: }else{
5043: if(first==1)
1.265 brouard 5044: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5045: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5046: }
5047: }
5048:
1.265 brouard 5049: for(s1=1; s1 <=nlstate ; s1++){
5050: /* posprop[s1]=0; */
5051: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5052: pp[s1] += freq[s1][m][iage];
5053: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5054:
5055: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5056: pos += pp[s1]; /* pos is the total number of transitions until this age */
5057: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5058: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5059: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5060: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5061: }
5062:
5063: /* Writing ficresp */
5064: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
5065: if( iage <= iagemax){
5066: fprintf(ficresp," %d",iage);
5067: }
5068: }else if( nj==2){
5069: if( iage <= iagemax){
5070: fprintf(ficresp," %d",iage);
5071: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
5072: }
1.240 brouard 5073: }
1.265 brouard 5074: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5075: if(pos>=1.e-5){
1.251 brouard 5076: if(first==1)
1.265 brouard 5077: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5078: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5079: }else{
5080: if(first==1)
1.265 brouard 5081: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5082: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5083: }
5084: if( iage <= iagemax){
5085: if(pos>=1.e-5){
1.265 brouard 5086: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
5087: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5088: }else if( nj==2){
5089: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5090: }
5091: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5092: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5093: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5094: } else{
5095: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
5096: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5097: }
1.240 brouard 5098: }
1.265 brouard 5099: pospropt[s1] +=posprop[s1];
5100: } /* end loop s1 */
1.251 brouard 5101: /* pospropt=0.; */
1.265 brouard 5102: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5103: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5104: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5105: if(first==1){
1.265 brouard 5106: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5107: }
1.265 brouard 5108: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5109: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5110: }
1.265 brouard 5111: if(s1!=0 && m!=0)
5112: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5113: }
1.265 brouard 5114: } /* end loop s1 */
1.251 brouard 5115: posproptt=0.;
1.265 brouard 5116: for(s1=1; s1 <=nlstate; s1++){
5117: posproptt += pospropt[s1];
1.251 brouard 5118: }
5119: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5120: fprintf(ficresphtm,"</tr>\n");
5121: if((cptcoveff==0 && nj==1)|| nj==2 ) {
5122: if(iage <= iagemax)
5123: fprintf(ficresp,"\n");
1.240 brouard 5124: }
1.251 brouard 5125: if(first==1)
5126: printf("Others in log...\n");
5127: fprintf(ficlog,"\n");
5128: } /* end loop age iage */
1.265 brouard 5129:
1.251 brouard 5130: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5131: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5132: if(posproptt < 1.e-5){
1.265 brouard 5133: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5134: }else{
1.265 brouard 5135: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5136: }
1.226 brouard 5137: }
1.251 brouard 5138: fprintf(ficresphtm,"</tr>\n");
5139: fprintf(ficresphtm,"</table>\n");
5140: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5141: if(posproptt < 1.e-5){
1.251 brouard 5142: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5143: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5144: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5145: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5146: invalidvarcomb[j1]=1;
1.226 brouard 5147: }else{
1.251 brouard 5148: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
5149: invalidvarcomb[j1]=0;
1.226 brouard 5150: }
1.251 brouard 5151: fprintf(ficresphtmfr,"</table>\n");
5152: fprintf(ficlog,"\n");
5153: if(j!=0){
5154: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5155: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5156: for(k=1; k <=(nlstate+ndeath); k++){
5157: if (k != i) {
1.265 brouard 5158: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5159: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5160: if(j1==1){ /* All dummy covariates to zero */
5161: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5162: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5163: printf("%d%d ",i,k);
5164: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5165: 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]));
5166: 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]));
5167: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5168: }
1.253 brouard 5169: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5170: for(iage=iagemin; iage <= iagemax+3; iage++){
5171: x[iage]= (double)iage;
5172: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5173: /* 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 5174: }
1.268 brouard 5175: /* Some are not finite, but linreg will ignore these ages */
5176: no=0;
1.253 brouard 5177: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5178: pstart[s1]=b;
5179: pstart[s1-1]=a;
1.252 brouard 5180: }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 */
5181: 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]);
5182: 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 5183: 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 5184: printf("%d%d ",i,k);
5185: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5186: 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 5187: }else{ /* Other cases, like quantitative fixed or varying covariates */
5188: ;
5189: }
5190: /* printf("%12.7f )", param[i][jj][k]); */
5191: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5192: s1++;
1.251 brouard 5193: } /* end jj */
5194: } /* end k!= i */
5195: } /* end k */
1.265 brouard 5196: } /* end i, s1 */
1.251 brouard 5197: } /* end j !=0 */
5198: } /* end selected combination of covariate j1 */
5199: if(j==0){ /* We can estimate starting values from the occurences in each case */
5200: printf("#Freqsummary: Starting values for the constants:\n");
5201: fprintf(ficlog,"\n");
1.265 brouard 5202: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5203: for(k=1; k <=(nlstate+ndeath); k++){
5204: if (k != i) {
5205: printf("%d%d ",i,k);
5206: fprintf(ficlog,"%d%d ",i,k);
5207: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5208: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5209: if(jj==1){ /* Age has to be done */
1.265 brouard 5210: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5211: 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]));
5212: 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 5213: }
5214: /* printf("%12.7f )", param[i][jj][k]); */
5215: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5216: s1++;
1.250 brouard 5217: }
1.251 brouard 5218: printf("\n");
5219: fprintf(ficlog,"\n");
1.250 brouard 5220: }
5221: }
1.284 brouard 5222: } /* end of state i */
1.251 brouard 5223: printf("#Freqsummary\n");
5224: fprintf(ficlog,"\n");
1.265 brouard 5225: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5226: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5227: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5228: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5229: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5230: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5231: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5232: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5233: /* } */
5234: }
1.265 brouard 5235: } /* end loop s1 */
1.251 brouard 5236:
5237: printf("\n");
5238: fprintf(ficlog,"\n");
5239: } /* end j=0 */
1.249 brouard 5240: } /* end j */
1.252 brouard 5241:
1.253 brouard 5242: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5243: for(i=1, jk=1; i <=nlstate; i++){
5244: for(j=1; j <=nlstate+ndeath; j++){
5245: if(j!=i){
5246: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5247: printf("%1d%1d",i,j);
5248: fprintf(ficparo,"%1d%1d",i,j);
5249: for(k=1; k<=ncovmodel;k++){
5250: /* printf(" %lf",param[i][j][k]); */
5251: /* fprintf(ficparo," %lf",param[i][j][k]); */
5252: p[jk]=pstart[jk];
5253: printf(" %f ",pstart[jk]);
5254: fprintf(ficparo," %f ",pstart[jk]);
5255: jk++;
5256: }
5257: printf("\n");
5258: fprintf(ficparo,"\n");
5259: }
5260: }
5261: }
5262: } /* end mle=-2 */
1.226 brouard 5263: dateintmean=dateintsum/k2cpt;
1.296 brouard 5264: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5265:
1.226 brouard 5266: fclose(ficresp);
5267: fclose(ficresphtm);
5268: fclose(ficresphtmfr);
1.283 brouard 5269: free_vector(idq,1,nqfveff);
1.226 brouard 5270: free_vector(meanq,1,nqfveff);
1.284 brouard 5271: free_vector(stdq,1,nqfveff);
1.226 brouard 5272: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5273: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5274: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5275: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5276: free_vector(pospropt,1,nlstate);
5277: free_vector(posprop,1,nlstate);
1.251 brouard 5278: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5279: free_vector(pp,1,nlstate);
5280: /* End of freqsummary */
5281: }
1.126 brouard 5282:
1.268 brouard 5283: /* Simple linear regression */
5284: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5285:
5286: /* y=a+bx regression */
5287: double sumx = 0.0; /* sum of x */
5288: double sumx2 = 0.0; /* sum of x**2 */
5289: double sumxy = 0.0; /* sum of x * y */
5290: double sumy = 0.0; /* sum of y */
5291: double sumy2 = 0.0; /* sum of y**2 */
5292: double sume2 = 0.0; /* sum of square or residuals */
5293: double yhat;
5294:
5295: double denom=0;
5296: int i;
5297: int ne=*no;
5298:
5299: for ( i=ifi, ne=0;i<=ila;i++) {
5300: if(!isfinite(x[i]) || !isfinite(y[i])){
5301: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5302: continue;
5303: }
5304: ne=ne+1;
5305: sumx += x[i];
5306: sumx2 += x[i]*x[i];
5307: sumxy += x[i] * y[i];
5308: sumy += y[i];
5309: sumy2 += y[i]*y[i];
5310: denom = (ne * sumx2 - sumx*sumx);
5311: /* 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); */
5312: }
5313:
5314: denom = (ne * sumx2 - sumx*sumx);
5315: if (denom == 0) {
5316: // vertical, slope m is infinity
5317: *b = INFINITY;
5318: *a = 0;
5319: if (r) *r = 0;
5320: return 1;
5321: }
5322:
5323: *b = (ne * sumxy - sumx * sumy) / denom;
5324: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5325: if (r!=NULL) {
5326: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5327: sqrt((sumx2 - sumx*sumx/ne) *
5328: (sumy2 - sumy*sumy/ne));
5329: }
5330: *no=ne;
5331: for ( i=ifi, ne=0;i<=ila;i++) {
5332: if(!isfinite(x[i]) || !isfinite(y[i])){
5333: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5334: continue;
5335: }
5336: ne=ne+1;
5337: yhat = y[i] - *a -*b* x[i];
5338: sume2 += yhat * yhat ;
5339:
5340: denom = (ne * sumx2 - sumx*sumx);
5341: /* 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); */
5342: }
5343: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5344: *sa= *sb * sqrt(sumx2/ne);
5345:
5346: return 0;
5347: }
5348:
1.126 brouard 5349: /************ Prevalence ********************/
1.227 brouard 5350: 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)
5351: {
5352: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5353: in each health status at the date of interview (if between dateprev1 and dateprev2).
5354: We still use firstpass and lastpass as another selection.
5355: */
1.126 brouard 5356:
1.227 brouard 5357: int i, m, jk, j1, bool, z1,j, iv;
5358: int mi; /* Effective wave */
5359: int iage;
5360: double agebegin, ageend;
5361:
5362: double **prop;
5363: double posprop;
5364: double y2; /* in fractional years */
5365: int iagemin, iagemax;
5366: int first; /** to stop verbosity which is redirected to log file */
5367:
5368: iagemin= (int) agemin;
5369: iagemax= (int) agemax;
5370: /*pp=vector(1,nlstate);*/
1.251 brouard 5371: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5372: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5373: j1=0;
1.222 brouard 5374:
1.227 brouard 5375: /*j=cptcoveff;*/
5376: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5377:
1.288 brouard 5378: first=0;
1.227 brouard 5379: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5380: for (i=1; i<=nlstate; i++)
1.251 brouard 5381: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5382: prop[i][iage]=0.0;
5383: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5384: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5385: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5386:
5387: for (i=1; i<=imx; i++) { /* Each individual */
5388: bool=1;
5389: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5390: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5391: m=mw[mi][i];
5392: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5393: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5394: for (z1=1; z1<=cptcoveff; z1++){
5395: if( Fixed[Tmodelind[z1]]==1){
5396: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5397: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5398: bool=0;
5399: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5400: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5401: bool=0;
5402: }
5403: }
5404: if(bool==1){ /* Otherwise we skip that wave/person */
5405: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5406: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5407: if(m >=firstpass && m <=lastpass){
5408: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5409: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5410: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5411: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5412: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5413: 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);
5414: exit(1);
5415: }
5416: if (s[m][i]>0 && s[m][i]<=nlstate) {
5417: /*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]]);*/
5418: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5419: prop[s[m][i]][iagemax+3] += weight[i];
5420: } /* end valid statuses */
5421: } /* end selection of dates */
5422: } /* end selection of waves */
5423: } /* end bool */
5424: } /* end wave */
5425: } /* end individual */
5426: for(i=iagemin; i <= iagemax+3; i++){
5427: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5428: posprop += prop[jk][i];
5429: }
5430:
5431: for(jk=1; jk <=nlstate ; jk++){
5432: if( i <= iagemax){
5433: if(posprop>=1.e-5){
5434: probs[i][jk][j1]= prop[jk][i]/posprop;
5435: } else{
1.288 brouard 5436: if(!first){
5437: first=1;
1.266 brouard 5438: 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]);
5439: }else{
1.288 brouard 5440: 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 5441: }
5442: }
5443: }
5444: }/* end jk */
5445: }/* end i */
1.222 brouard 5446: /*} *//* end i1 */
1.227 brouard 5447: } /* end j1 */
1.222 brouard 5448:
1.227 brouard 5449: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5450: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5451: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5452: } /* End of prevalence */
1.126 brouard 5453:
5454: /************* Waves Concatenation ***************/
5455:
5456: 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)
5457: {
1.298 brouard 5458: /* 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 5459: Death is a valid wave (if date is known).
5460: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5461: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 5462: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 5463: */
1.126 brouard 5464:
1.224 brouard 5465: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5466: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5467: double sum=0., jmean=0.;*/
1.224 brouard 5468: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5469: int j, k=0,jk, ju, jl;
5470: double sum=0.;
5471: first=0;
1.214 brouard 5472: firstwo=0;
1.217 brouard 5473: firsthree=0;
1.218 brouard 5474: firstfour=0;
1.164 brouard 5475: jmin=100000;
1.126 brouard 5476: jmax=-1;
5477: jmean=0.;
1.224 brouard 5478:
5479: /* Treating live states */
1.214 brouard 5480: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5481: mi=0; /* First valid wave */
1.227 brouard 5482: mli=0; /* Last valid wave */
1.309 brouard 5483: m=firstpass; /* Loop on waves */
5484: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 5485: 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 */
5486: mli=m-1;/* mw[++mi][i]=m-1; */
5487: }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 5488: 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 5489: mli=m;
1.224 brouard 5490: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5491: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5492: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5493: }
1.309 brouard 5494: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 5495: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5496: break;
1.224 brouard 5497: #else
1.317 brouard 5498: 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 5499: if(firsthree == 0){
1.302 brouard 5500: 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 5501: firsthree=1;
1.317 brouard 5502: }else if(firsthree >=1 && firsthree < 10){
5503: 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);
5504: firsthree++;
5505: }else if(firsthree == 10){
5506: printf("Information, too many Information flags: no more reported to log either\n");
5507: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
5508: firsthree++;
5509: }else{
5510: firsthree++;
1.227 brouard 5511: }
1.309 brouard 5512: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 5513: mli=m;
5514: }
5515: if(s[m][i]==-2){ /* Vital status is really unknown */
5516: nbwarn++;
1.309 brouard 5517: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 5518: 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);
5519: 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);
5520: }
5521: break;
5522: }
5523: break;
1.224 brouard 5524: #endif
1.227 brouard 5525: }/* End m >= lastpass */
1.126 brouard 5526: }/* end while */
1.224 brouard 5527:
1.227 brouard 5528: /* 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 5529: /* After last pass */
1.224 brouard 5530: /* Treating death states */
1.214 brouard 5531: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5532: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5533: /* } */
1.126 brouard 5534: mi++; /* Death is another wave */
5535: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5536: /* Only death is a correct wave */
1.126 brouard 5537: mw[mi][i]=m;
1.257 brouard 5538: } /* else not in a death state */
1.224 brouard 5539: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5540: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5541: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 5542: 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 5543: nbwarn++;
5544: if(firstfiv==0){
1.309 brouard 5545: 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 5546: firstfiv=1;
5547: }else{
1.309 brouard 5548: 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 5549: }
1.309 brouard 5550: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
5551: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 5552: nberr++;
5553: if(firstwo==0){
1.309 brouard 5554: 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 5555: firstwo=1;
5556: }
1.309 brouard 5557: 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 5558: }
1.257 brouard 5559: }else{ /* if date of interview is unknown */
1.227 brouard 5560: /* death is known but not confirmed by death status at any wave */
5561: if(firstfour==0){
1.309 brouard 5562: 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 5563: firstfour=1;
5564: }
1.309 brouard 5565: 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 5566: }
1.224 brouard 5567: } /* end if date of death is known */
5568: #endif
1.309 brouard 5569: wav[i]=mi; /* mi should be the last effective wave (or mli), */
5570: /* wav[i]=mw[mi][i]; */
1.126 brouard 5571: if(mi==0){
5572: nbwarn++;
5573: if(first==0){
1.227 brouard 5574: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5575: first=1;
1.126 brouard 5576: }
5577: if(first==1){
1.227 brouard 5578: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5579: }
5580: } /* end mi==0 */
5581: } /* End individuals */
1.214 brouard 5582: /* wav and mw are no more changed */
1.223 brouard 5583:
1.317 brouard 5584: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
5585: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
5586:
5587:
1.126 brouard 5588: for(i=1; i<=imx; i++){
5589: for(mi=1; mi<wav[i];mi++){
5590: if (stepm <=0)
1.227 brouard 5591: dh[mi][i]=1;
1.126 brouard 5592: else{
1.260 brouard 5593: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5594: if (agedc[i] < 2*AGESUP) {
5595: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5596: if(j==0) j=1; /* Survives at least one month after exam */
5597: else if(j<0){
5598: nberr++;
5599: 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]);
5600: j=1; /* Temporary Dangerous patch */
5601: 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);
5602: 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]);
5603: 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);
5604: }
5605: k=k+1;
5606: if (j >= jmax){
5607: jmax=j;
5608: ijmax=i;
5609: }
5610: if (j <= jmin){
5611: jmin=j;
5612: ijmin=i;
5613: }
5614: sum=sum+j;
5615: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5616: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5617: }
5618: }
5619: else{
5620: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5621: /* 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 5622:
1.227 brouard 5623: k=k+1;
5624: if (j >= jmax) {
5625: jmax=j;
5626: ijmax=i;
5627: }
5628: else if (j <= jmin){
5629: jmin=j;
5630: ijmin=i;
5631: }
5632: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5633: /*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]);*/
5634: if(j<0){
5635: nberr++;
5636: 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]);
5637: 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]);
5638: }
5639: sum=sum+j;
5640: }
5641: jk= j/stepm;
5642: jl= j -jk*stepm;
5643: ju= j -(jk+1)*stepm;
5644: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5645: if(jl==0){
5646: dh[mi][i]=jk;
5647: bh[mi][i]=0;
5648: }else{ /* We want a negative bias in order to only have interpolation ie
5649: * to avoid the price of an extra matrix product in likelihood */
5650: dh[mi][i]=jk+1;
5651: bh[mi][i]=ju;
5652: }
5653: }else{
5654: if(jl <= -ju){
5655: dh[mi][i]=jk;
5656: bh[mi][i]=jl; /* bias is positive if real duration
5657: * is higher than the multiple of stepm and negative otherwise.
5658: */
5659: }
5660: else{
5661: dh[mi][i]=jk+1;
5662: bh[mi][i]=ju;
5663: }
5664: if(dh[mi][i]==0){
5665: dh[mi][i]=1; /* At least one step */
5666: bh[mi][i]=ju; /* At least one step */
5667: /* 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);*/
5668: }
5669: } /* end if mle */
1.126 brouard 5670: }
5671: } /* end wave */
5672: }
5673: jmean=sum/k;
5674: 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 5675: 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 5676: }
1.126 brouard 5677:
5678: /*********** Tricode ****************************/
1.220 brouard 5679: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5680: {
5681: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5682: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5683: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5684: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5685: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5686: */
1.130 brouard 5687:
1.242 brouard 5688: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5689: int modmaxcovj=0; /* Modality max of covariates j */
5690: int cptcode=0; /* Modality max of covariates j */
5691: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5692:
5693:
1.242 brouard 5694: /* cptcoveff=0; */
5695: /* *cptcov=0; */
1.126 brouard 5696:
1.242 brouard 5697: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5698: for (k=1; k <= maxncov; k++)
5699: for(j=1; j<=2; j++)
5700: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5701:
1.242 brouard 5702: /* Loop on covariates without age and products and no quantitative variable */
5703: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5704: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5705: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5706: switch(Fixed[k]) {
5707: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 5708: modmaxcovj=0;
5709: modmincovj=0;
1.242 brouard 5710: 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*/
5711: ij=(int)(covar[Tvar[k]][i]);
5712: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5713: * If product of Vn*Vm, still boolean *:
5714: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5715: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5716: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5717: modality of the nth covariate of individual i. */
5718: if (ij > modmaxcovj)
5719: modmaxcovj=ij;
5720: else if (ij < modmincovj)
5721: modmincovj=ij;
1.287 brouard 5722: if (ij <0 || ij >1 ){
1.311 brouard 5723: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5724: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5725: fflush(ficlog);
5726: exit(1);
1.287 brouard 5727: }
5728: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5729: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5730: exit(1);
5731: }else
5732: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5733: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5734: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5735: /* getting the maximum value of the modality of the covariate
5736: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5737: female ies 1, then modmaxcovj=1.
5738: */
5739: } /* end for loop on individuals i */
5740: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5741: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5742: cptcode=modmaxcovj;
5743: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5744: /*for (i=0; i<=cptcode; i++) {*/
5745: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5746: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5747: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5748: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5749: if( j != -1){
5750: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5751: covariate for which somebody answered excluding
5752: undefined. Usually 2: 0 and 1. */
5753: }
5754: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5755: covariate for which somebody answered including
5756: undefined. Usually 3: -1, 0 and 1. */
5757: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5758: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5759: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5760:
1.242 brouard 5761: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5762: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5763: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5764: /* modmincovj=3; modmaxcovj = 7; */
5765: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5766: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5767: /* defining two dummy variables: variables V1_1 and V1_2.*/
5768: /* nbcode[Tvar[j]][ij]=k; */
5769: /* nbcode[Tvar[j]][1]=0; */
5770: /* nbcode[Tvar[j]][2]=1; */
5771: /* nbcode[Tvar[j]][3]=2; */
5772: /* To be continued (not working yet). */
5773: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5774:
5775: /* 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*/
5776: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5777: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5778: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5779: /*, could be restored in the future */
5780: 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 5781: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5782: break;
5783: }
5784: ij++;
1.287 brouard 5785: 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 5786: cptcode = ij; /* New max modality for covar j */
5787: } /* end of loop on modality i=-1 to 1 or more */
5788: break;
5789: case 1: /* Testing on varying covariate, could be simple and
5790: * should look at waves or product of fixed *
5791: * varying. No time to test -1, assuming 0 and 1 only */
5792: ij=0;
5793: for(i=0; i<=1;i++){
5794: nbcode[Tvar[k]][++ij]=i;
5795: }
5796: break;
5797: default:
5798: break;
5799: } /* end switch */
5800: } /* end dummy test */
1.311 brouard 5801: if(Dummy[k]==1 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5802: 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*/
5803: if(isnan(covar[Tvar[k]][i])){
5804: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5805: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5806: fflush(ficlog);
5807: exit(1);
5808: }
5809: }
5810: }
1.287 brouard 5811: } /* 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 5812:
5813: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5814: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5815: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5816: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5817: 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 */
5818: 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 */
5819: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5820: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5821:
5822: ij=0;
5823: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5824: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5825: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5826: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5827: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5828: /* If product not in single variable we don't print results */
5829: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5830: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5831: 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*/
5832: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5833: 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 */
5834: if(Fixed[k]!=0)
5835: anyvaryingduminmodel=1;
5836: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5837: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5838: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5839: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5840: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5841: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5842: }
5843: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5844: /* ij--; */
5845: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5846: *cptcov=ij; /*Number of total real effective covariates: effective
5847: * because they can be excluded from the model and real
5848: * if in the model but excluded because missing values, but how to get k from ij?*/
5849: for(j=ij+1; j<= cptcovt; j++){
5850: Tvaraff[j]=0;
5851: Tmodelind[j]=0;
5852: }
5853: for(j=ntveff+1; j<= cptcovt; j++){
5854: TmodelInvind[j]=0;
5855: }
5856: /* To be sorted */
5857: ;
5858: }
1.126 brouard 5859:
1.145 brouard 5860:
1.126 brouard 5861: /*********** Health Expectancies ****************/
5862:
1.235 brouard 5863: 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 5864:
5865: {
5866: /* Health expectancies, no variances */
1.164 brouard 5867: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5868: int nhstepma, nstepma; /* Decreasing with age */
5869: double age, agelim, hf;
5870: double ***p3mat;
5871: double eip;
5872:
1.238 brouard 5873: /* pstamp(ficreseij); */
1.126 brouard 5874: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5875: fprintf(ficreseij,"# Age");
5876: for(i=1; i<=nlstate;i++){
5877: for(j=1; j<=nlstate;j++){
5878: fprintf(ficreseij," e%1d%1d ",i,j);
5879: }
5880: fprintf(ficreseij," e%1d. ",i);
5881: }
5882: fprintf(ficreseij,"\n");
5883:
5884:
5885: if(estepm < stepm){
5886: printf ("Problem %d lower than %d\n",estepm, stepm);
5887: }
5888: else hstepm=estepm;
5889: /* We compute the life expectancy from trapezoids spaced every estepm months
5890: * This is mainly to measure the difference between two models: for example
5891: * if stepm=24 months pijx are given only every 2 years and by summing them
5892: * we are calculating an estimate of the Life Expectancy assuming a linear
5893: * progression in between and thus overestimating or underestimating according
5894: * to the curvature of the survival function. If, for the same date, we
5895: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5896: * to compare the new estimate of Life expectancy with the same linear
5897: * hypothesis. A more precise result, taking into account a more precise
5898: * curvature will be obtained if estepm is as small as stepm. */
5899:
5900: /* For example we decided to compute the life expectancy with the smallest unit */
5901: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5902: nhstepm is the number of hstepm from age to agelim
5903: nstepm is the number of stepm from age to agelin.
1.270 brouard 5904: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5905: and note for a fixed period like estepm months */
5906: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5907: survival function given by stepm (the optimization length). Unfortunately it
5908: means that if the survival funtion is printed only each two years of age and if
5909: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5910: results. So we changed our mind and took the option of the best precision.
5911: */
5912: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5913:
5914: agelim=AGESUP;
5915: /* If stepm=6 months */
5916: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5917: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5918:
5919: /* nhstepm age range expressed in number of stepm */
5920: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5921: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5922: /* if (stepm >= YEARM) hstepm=1;*/
5923: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5924: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5925:
5926: for (age=bage; age<=fage; age ++){
5927: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5928: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5929: /* if (stepm >= YEARM) hstepm=1;*/
5930: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5931:
5932: /* If stepm=6 months */
5933: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5934: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5935:
1.235 brouard 5936: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5937:
5938: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5939:
5940: printf("%d|",(int)age);fflush(stdout);
5941: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5942:
5943: /* Computing expectancies */
5944: for(i=1; i<=nlstate;i++)
5945: for(j=1; j<=nlstate;j++)
5946: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5947: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5948:
5949: /* 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]);*/
5950:
5951: }
5952:
5953: fprintf(ficreseij,"%3.0f",age );
5954: for(i=1; i<=nlstate;i++){
5955: eip=0;
5956: for(j=1; j<=nlstate;j++){
5957: eip +=eij[i][j][(int)age];
5958: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5959: }
5960: fprintf(ficreseij,"%9.4f", eip );
5961: }
5962: fprintf(ficreseij,"\n");
5963:
5964: }
5965: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5966: printf("\n");
5967: fprintf(ficlog,"\n");
5968:
5969: }
5970:
1.235 brouard 5971: 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 5972:
5973: {
5974: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5975: to initial status i, ei. .
1.126 brouard 5976: */
5977: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5978: int nhstepma, nstepma; /* Decreasing with age */
5979: double age, agelim, hf;
5980: double ***p3matp, ***p3matm, ***varhe;
5981: double **dnewm,**doldm;
5982: double *xp, *xm;
5983: double **gp, **gm;
5984: double ***gradg, ***trgradg;
5985: int theta;
5986:
5987: double eip, vip;
5988:
5989: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5990: xp=vector(1,npar);
5991: xm=vector(1,npar);
5992: dnewm=matrix(1,nlstate*nlstate,1,npar);
5993: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5994:
5995: pstamp(ficresstdeij);
5996: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5997: fprintf(ficresstdeij,"# Age");
5998: for(i=1; i<=nlstate;i++){
5999: for(j=1; j<=nlstate;j++)
6000: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6001: fprintf(ficresstdeij," e%1d. ",i);
6002: }
6003: fprintf(ficresstdeij,"\n");
6004:
6005: pstamp(ficrescveij);
6006: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6007: fprintf(ficrescveij,"# Age");
6008: for(i=1; i<=nlstate;i++)
6009: for(j=1; j<=nlstate;j++){
6010: cptj= (j-1)*nlstate+i;
6011: for(i2=1; i2<=nlstate;i2++)
6012: for(j2=1; j2<=nlstate;j2++){
6013: cptj2= (j2-1)*nlstate+i2;
6014: if(cptj2 <= cptj)
6015: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6016: }
6017: }
6018: fprintf(ficrescveij,"\n");
6019:
6020: if(estepm < stepm){
6021: printf ("Problem %d lower than %d\n",estepm, stepm);
6022: }
6023: else hstepm=estepm;
6024: /* We compute the life expectancy from trapezoids spaced every estepm months
6025: * This is mainly to measure the difference between two models: for example
6026: * if stepm=24 months pijx are given only every 2 years and by summing them
6027: * we are calculating an estimate of the Life Expectancy assuming a linear
6028: * progression in between and thus overestimating or underestimating according
6029: * to the curvature of the survival function. If, for the same date, we
6030: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6031: * to compare the new estimate of Life expectancy with the same linear
6032: * hypothesis. A more precise result, taking into account a more precise
6033: * curvature will be obtained if estepm is as small as stepm. */
6034:
6035: /* For example we decided to compute the life expectancy with the smallest unit */
6036: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6037: nhstepm is the number of hstepm from age to agelim
6038: nstepm is the number of stepm from age to agelin.
6039: Look at hpijx to understand the reason of that which relies in memory size
6040: and note for a fixed period like estepm months */
6041: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6042: survival function given by stepm (the optimization length). Unfortunately it
6043: means that if the survival funtion is printed only each two years of age and if
6044: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6045: results. So we changed our mind and took the option of the best precision.
6046: */
6047: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6048:
6049: /* If stepm=6 months */
6050: /* nhstepm age range expressed in number of stepm */
6051: agelim=AGESUP;
6052: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6053: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6054: /* if (stepm >= YEARM) hstepm=1;*/
6055: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6056:
6057: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6058: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6059: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6060: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6061: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6062: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6063:
6064: for (age=bage; age<=fage; age ++){
6065: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6066: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6067: /* if (stepm >= YEARM) hstepm=1;*/
6068: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6069:
1.126 brouard 6070: /* If stepm=6 months */
6071: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6072: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6073:
6074: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6075:
1.126 brouard 6076: /* Computing Variances of health expectancies */
6077: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6078: decrease memory allocation */
6079: for(theta=1; theta <=npar; theta++){
6080: for(i=1; i<=npar; i++){
1.222 brouard 6081: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6082: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6083: }
1.235 brouard 6084: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6085: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6086:
1.126 brouard 6087: for(j=1; j<= nlstate; j++){
1.222 brouard 6088: for(i=1; i<=nlstate; i++){
6089: for(h=0; h<=nhstepm-1; h++){
6090: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6091: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6092: }
6093: }
1.126 brouard 6094: }
1.218 brouard 6095:
1.126 brouard 6096: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6097: for(h=0; h<=nhstepm-1; h++){
6098: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6099: }
1.126 brouard 6100: }/* End theta */
6101:
6102:
6103: for(h=0; h<=nhstepm-1; h++)
6104: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6105: for(theta=1; theta <=npar; theta++)
6106: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6107:
1.218 brouard 6108:
1.222 brouard 6109: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6110: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6111: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6112:
1.222 brouard 6113: printf("%d|",(int)age);fflush(stdout);
6114: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6115: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6116: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6117: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6118: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6119: for(ij=1;ij<=nlstate*nlstate;ij++)
6120: for(ji=1;ji<=nlstate*nlstate;ji++)
6121: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6122: }
6123: }
1.320 brouard 6124: /* if((int)age ==50){ */
6125: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6126: /* } */
1.126 brouard 6127: /* Computing expectancies */
1.235 brouard 6128: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6129: for(i=1; i<=nlstate;i++)
6130: for(j=1; j<=nlstate;j++)
1.222 brouard 6131: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6132: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6133:
1.222 brouard 6134: /* 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 6135:
1.222 brouard 6136: }
1.269 brouard 6137:
6138: /* Standard deviation of expectancies ij */
1.126 brouard 6139: fprintf(ficresstdeij,"%3.0f",age );
6140: for(i=1; i<=nlstate;i++){
6141: eip=0.;
6142: vip=0.;
6143: for(j=1; j<=nlstate;j++){
1.222 brouard 6144: eip += eij[i][j][(int)age];
6145: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6146: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6147: 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 6148: }
6149: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6150: }
6151: fprintf(ficresstdeij,"\n");
1.218 brouard 6152:
1.269 brouard 6153: /* Variance of expectancies ij */
1.126 brouard 6154: fprintf(ficrescveij,"%3.0f",age );
6155: for(i=1; i<=nlstate;i++)
6156: for(j=1; j<=nlstate;j++){
1.222 brouard 6157: cptj= (j-1)*nlstate+i;
6158: for(i2=1; i2<=nlstate;i2++)
6159: for(j2=1; j2<=nlstate;j2++){
6160: cptj2= (j2-1)*nlstate+i2;
6161: if(cptj2 <= cptj)
6162: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6163: }
1.126 brouard 6164: }
6165: fprintf(ficrescveij,"\n");
1.218 brouard 6166:
1.126 brouard 6167: }
6168: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6169: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6170: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6171: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6172: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6173: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6174: printf("\n");
6175: fprintf(ficlog,"\n");
1.218 brouard 6176:
1.126 brouard 6177: free_vector(xm,1,npar);
6178: free_vector(xp,1,npar);
6179: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6180: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6181: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6182: }
1.218 brouard 6183:
1.126 brouard 6184: /************ Variance ******************/
1.235 brouard 6185: 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 6186: {
1.279 brouard 6187: /** Variance of health expectancies
6188: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
6189: * double **newm;
6190: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
6191: */
1.218 brouard 6192:
6193: /* int movingaverage(); */
6194: double **dnewm,**doldm;
6195: double **dnewmp,**doldmp;
6196: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6197: int first=0;
1.218 brouard 6198: int k;
6199: double *xp;
1.279 brouard 6200: double **gp, **gm; /**< for var eij */
6201: double ***gradg, ***trgradg; /**< for var eij */
6202: double **gradgp, **trgradgp; /**< for var p point j */
6203: double *gpp, *gmp; /**< for var p point j */
6204: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6205: double ***p3mat;
6206: double age,agelim, hf;
6207: /* double ***mobaverage; */
6208: int theta;
6209: char digit[4];
6210: char digitp[25];
6211:
6212: char fileresprobmorprev[FILENAMELENGTH];
6213:
6214: if(popbased==1){
6215: if(mobilav!=0)
6216: strcpy(digitp,"-POPULBASED-MOBILAV_");
6217: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6218: }
6219: else
6220: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6221:
1.218 brouard 6222: /* if (mobilav!=0) { */
6223: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6224: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
6225: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
6226: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
6227: /* } */
6228: /* } */
6229:
6230: strcpy(fileresprobmorprev,"PRMORPREV-");
6231: sprintf(digit,"%-d",ij);
6232: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
6233: strcat(fileresprobmorprev,digit); /* Tvar to be done */
6234: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
6235: strcat(fileresprobmorprev,fileresu);
6236: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
6237: printf("Problem with resultfile: %s\n", fileresprobmorprev);
6238: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
6239: }
6240: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6241: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6242: pstamp(ficresprobmorprev);
6243: 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 6244: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
6245: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
6246: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
6247: }
6248: for(j=1;j<=cptcoveff;j++)
6249: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
6250: fprintf(ficresprobmorprev,"\n");
6251:
1.218 brouard 6252: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
6253: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6254: fprintf(ficresprobmorprev," p.%-d SE",j);
6255: for(i=1; i<=nlstate;i++)
6256: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
6257: }
6258: fprintf(ficresprobmorprev,"\n");
6259:
6260: fprintf(ficgp,"\n# Routine varevsij");
6261: fprintf(ficgp,"\nunset title \n");
6262: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
6263: 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");
6264: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 6265:
1.218 brouard 6266: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6267: pstamp(ficresvij);
6268: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
6269: if(popbased==1)
6270: 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);
6271: else
6272: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6273: fprintf(ficresvij,"# Age");
6274: for(i=1; i<=nlstate;i++)
6275: for(j=1; j<=nlstate;j++)
6276: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6277: fprintf(ficresvij,"\n");
6278:
6279: xp=vector(1,npar);
6280: dnewm=matrix(1,nlstate,1,npar);
6281: doldm=matrix(1,nlstate,1,nlstate);
6282: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6283: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6284:
6285: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6286: gpp=vector(nlstate+1,nlstate+ndeath);
6287: gmp=vector(nlstate+1,nlstate+ndeath);
6288: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6289:
1.218 brouard 6290: if(estepm < stepm){
6291: printf ("Problem %d lower than %d\n",estepm, stepm);
6292: }
6293: else hstepm=estepm;
6294: /* For example we decided to compute the life expectancy with the smallest unit */
6295: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6296: nhstepm is the number of hstepm from age to agelim
6297: nstepm is the number of stepm from age to agelim.
6298: Look at function hpijx to understand why because of memory size limitations,
6299: we decided (b) to get a life expectancy respecting the most precise curvature of the
6300: survival function given by stepm (the optimization length). Unfortunately it
6301: means that if the survival funtion is printed every two years of age and if
6302: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6303: results. So we changed our mind and took the option of the best precision.
6304: */
6305: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6306: agelim = AGESUP;
6307: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6308: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6309: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6310: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6311: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6312: gp=matrix(0,nhstepm,1,nlstate);
6313: gm=matrix(0,nhstepm,1,nlstate);
6314:
6315:
6316: for(theta=1; theta <=npar; theta++){
6317: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6318: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6319: }
1.279 brouard 6320: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6321: * returns into prlim .
1.288 brouard 6322: */
1.242 brouard 6323: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6324:
6325: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6326: if (popbased==1) {
6327: if(mobilav ==0){
6328: for(i=1; i<=nlstate;i++)
6329: prlim[i][i]=probs[(int)age][i][ij];
6330: }else{ /* mobilav */
6331: for(i=1; i<=nlstate;i++)
6332: prlim[i][i]=mobaverage[(int)age][i][ij];
6333: }
6334: }
1.295 brouard 6335: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6336: */
6337: 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 6338: /**< 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 6339: * at horizon h in state j including mortality.
6340: */
1.218 brouard 6341: for(j=1; j<= nlstate; j++){
6342: for(h=0; h<=nhstepm; h++){
6343: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6344: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6345: }
6346: }
1.279 brouard 6347: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6348: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6349: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6350: */
6351: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6352: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6353: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6354: }
6355:
6356: /* Again with minus shift */
1.218 brouard 6357:
6358: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6359: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6360:
1.242 brouard 6361: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6362:
6363: if (popbased==1) {
6364: if(mobilav ==0){
6365: for(i=1; i<=nlstate;i++)
6366: prlim[i][i]=probs[(int)age][i][ij];
6367: }else{ /* mobilav */
6368: for(i=1; i<=nlstate;i++)
6369: prlim[i][i]=mobaverage[(int)age][i][ij];
6370: }
6371: }
6372:
1.235 brouard 6373: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6374:
6375: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6376: for(h=0; h<=nhstepm; h++){
6377: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6378: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6379: }
6380: }
6381: /* This for computing probability of death (h=1 means
6382: computed over hstepm matrices product = hstepm*stepm months)
6383: as a weighted average of prlim.
6384: */
6385: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6386: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6387: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6388: }
1.279 brouard 6389: /* end shifting computations */
6390:
6391: /**< Computing gradient matrix at horizon h
6392: */
1.218 brouard 6393: for(j=1; j<= nlstate; j++) /* vareij */
6394: for(h=0; h<=nhstepm; h++){
6395: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6396: }
1.279 brouard 6397: /**< Gradient of overall mortality p.3 (or p.j)
6398: */
6399: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6400: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6401: }
6402:
6403: } /* End theta */
1.279 brouard 6404:
6405: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6406: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6407:
6408: for(h=0; h<=nhstepm; h++) /* veij */
6409: for(j=1; j<=nlstate;j++)
6410: for(theta=1; theta <=npar; theta++)
6411: trgradg[h][j][theta]=gradg[h][theta][j];
6412:
6413: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6414: for(theta=1; theta <=npar; theta++)
6415: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6416: /**< as well as its transposed matrix
6417: */
1.218 brouard 6418:
6419: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6420: for(i=1;i<=nlstate;i++)
6421: for(j=1;j<=nlstate;j++)
6422: vareij[i][j][(int)age] =0.;
1.279 brouard 6423:
6424: /* Computing trgradg by matcov by gradg at age and summing over h
6425: * and k (nhstepm) formula 15 of article
6426: * Lievre-Brouard-Heathcote
6427: */
6428:
1.218 brouard 6429: for(h=0;h<=nhstepm;h++){
6430: for(k=0;k<=nhstepm;k++){
6431: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6432: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6433: for(i=1;i<=nlstate;i++)
6434: for(j=1;j<=nlstate;j++)
6435: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6436: }
6437: }
6438:
1.279 brouard 6439: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6440: * p.j overall mortality formula 49 but computed directly because
6441: * we compute the grad (wix pijx) instead of grad (pijx),even if
6442: * wix is independent of theta.
6443: */
1.218 brouard 6444: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6445: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6446: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6447: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6448: varppt[j][i]=doldmp[j][i];
6449: /* end ppptj */
6450: /* x centered again */
6451:
1.242 brouard 6452: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6453:
6454: if (popbased==1) {
6455: if(mobilav ==0){
6456: for(i=1; i<=nlstate;i++)
6457: prlim[i][i]=probs[(int)age][i][ij];
6458: }else{ /* mobilav */
6459: for(i=1; i<=nlstate;i++)
6460: prlim[i][i]=mobaverage[(int)age][i][ij];
6461: }
6462: }
6463:
6464: /* This for computing probability of death (h=1 means
6465: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6466: as a weighted average of prlim.
6467: */
1.235 brouard 6468: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6469: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6470: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6471: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6472: }
6473: /* end probability of death */
6474:
6475: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6476: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6477: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6478: for(i=1; i<=nlstate;i++){
6479: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6480: }
6481: }
6482: fprintf(ficresprobmorprev,"\n");
6483:
6484: fprintf(ficresvij,"%.0f ",age );
6485: for(i=1; i<=nlstate;i++)
6486: for(j=1; j<=nlstate;j++){
6487: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6488: }
6489: fprintf(ficresvij,"\n");
6490: free_matrix(gp,0,nhstepm,1,nlstate);
6491: free_matrix(gm,0,nhstepm,1,nlstate);
6492: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6493: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6494: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6495: } /* End age */
6496: free_vector(gpp,nlstate+1,nlstate+ndeath);
6497: free_vector(gmp,nlstate+1,nlstate+ndeath);
6498: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6499: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6500: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6501: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6502: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6503: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6504: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6505: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6506: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6507: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6508: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6509: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6510: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6511: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6512: 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);
6513: /* 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 6514: */
1.218 brouard 6515: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6516: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6517:
1.218 brouard 6518: free_vector(xp,1,npar);
6519: free_matrix(doldm,1,nlstate,1,nlstate);
6520: free_matrix(dnewm,1,nlstate,1,npar);
6521: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6522: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6523: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6524: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6525: fclose(ficresprobmorprev);
6526: fflush(ficgp);
6527: fflush(fichtm);
6528: } /* end varevsij */
1.126 brouard 6529:
6530: /************ Variance of prevlim ******************/
1.269 brouard 6531: 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 6532: {
1.205 brouard 6533: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6534: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6535:
1.268 brouard 6536: double **dnewmpar,**doldm;
1.126 brouard 6537: int i, j, nhstepm, hstepm;
6538: double *xp;
6539: double *gp, *gm;
6540: double **gradg, **trgradg;
1.208 brouard 6541: double **mgm, **mgp;
1.126 brouard 6542: double age,agelim;
6543: int theta;
6544:
6545: pstamp(ficresvpl);
1.288 brouard 6546: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6547: fprintf(ficresvpl,"# Age ");
6548: if(nresult >=1)
6549: fprintf(ficresvpl," Result# ");
1.126 brouard 6550: for(i=1; i<=nlstate;i++)
6551: fprintf(ficresvpl," %1d-%1d",i,i);
6552: fprintf(ficresvpl,"\n");
6553:
6554: xp=vector(1,npar);
1.268 brouard 6555: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6556: doldm=matrix(1,nlstate,1,nlstate);
6557:
6558: hstepm=1*YEARM; /* Every year of age */
6559: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6560: agelim = AGESUP;
6561: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6562: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6563: if (stepm >= YEARM) hstepm=1;
6564: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6565: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6566: mgp=matrix(1,npar,1,nlstate);
6567: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6568: gp=vector(1,nlstate);
6569: gm=vector(1,nlstate);
6570:
6571: for(theta=1; theta <=npar; theta++){
6572: for(i=1; i<=npar; i++){ /* Computes gradient */
6573: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6574: }
1.288 brouard 6575: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6576: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6577: /* else */
6578: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6579: for(i=1;i<=nlstate;i++){
1.126 brouard 6580: gp[i] = prlim[i][i];
1.208 brouard 6581: mgp[theta][i] = prlim[i][i];
6582: }
1.126 brouard 6583: for(i=1; i<=npar; i++) /* Computes gradient */
6584: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6585: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6586: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6587: /* else */
6588: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6589: for(i=1;i<=nlstate;i++){
1.126 brouard 6590: gm[i] = prlim[i][i];
1.208 brouard 6591: mgm[theta][i] = prlim[i][i];
6592: }
1.126 brouard 6593: for(i=1;i<=nlstate;i++)
6594: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6595: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6596: } /* End theta */
6597:
6598: trgradg =matrix(1,nlstate,1,npar);
6599:
6600: for(j=1; j<=nlstate;j++)
6601: for(theta=1; theta <=npar; theta++)
6602: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6603: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6604: /* printf("\nmgm mgp %d ",(int)age); */
6605: /* for(j=1; j<=nlstate;j++){ */
6606: /* printf(" %d ",j); */
6607: /* for(theta=1; theta <=npar; theta++) */
6608: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6609: /* printf("\n "); */
6610: /* } */
6611: /* } */
6612: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6613: /* printf("\n gradg %d ",(int)age); */
6614: /* for(j=1; j<=nlstate;j++){ */
6615: /* printf("%d ",j); */
6616: /* for(theta=1; theta <=npar; theta++) */
6617: /* printf("%d %lf ",theta,gradg[theta][j]); */
6618: /* printf("\n "); */
6619: /* } */
6620: /* } */
1.126 brouard 6621:
6622: for(i=1;i<=nlstate;i++)
6623: varpl[i][(int)age] =0.;
1.209 brouard 6624: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6625: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6626: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6627: }else{
1.268 brouard 6628: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6629: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6630: }
1.126 brouard 6631: for(i=1;i<=nlstate;i++)
6632: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6633:
6634: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6635: if(nresult >=1)
6636: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6637: for(i=1; i<=nlstate;i++){
1.126 brouard 6638: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6639: /* for(j=1;j<=nlstate;j++) */
6640: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6641: }
1.126 brouard 6642: fprintf(ficresvpl,"\n");
6643: free_vector(gp,1,nlstate);
6644: free_vector(gm,1,nlstate);
1.208 brouard 6645: free_matrix(mgm,1,npar,1,nlstate);
6646: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6647: free_matrix(gradg,1,npar,1,nlstate);
6648: free_matrix(trgradg,1,nlstate,1,npar);
6649: } /* End age */
6650:
6651: free_vector(xp,1,npar);
6652: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6653: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6654:
6655: }
6656:
6657:
6658: /************ Variance of backprevalence limit ******************/
1.269 brouard 6659: 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 6660: {
6661: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6662: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6663:
6664: double **dnewmpar,**doldm;
6665: int i, j, nhstepm, hstepm;
6666: double *xp;
6667: double *gp, *gm;
6668: double **gradg, **trgradg;
6669: double **mgm, **mgp;
6670: double age,agelim;
6671: int theta;
6672:
6673: pstamp(ficresvbl);
6674: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6675: fprintf(ficresvbl,"# Age ");
6676: if(nresult >=1)
6677: fprintf(ficresvbl," Result# ");
6678: for(i=1; i<=nlstate;i++)
6679: fprintf(ficresvbl," %1d-%1d",i,i);
6680: fprintf(ficresvbl,"\n");
6681:
6682: xp=vector(1,npar);
6683: dnewmpar=matrix(1,nlstate,1,npar);
6684: doldm=matrix(1,nlstate,1,nlstate);
6685:
6686: hstepm=1*YEARM; /* Every year of age */
6687: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6688: agelim = AGEINF;
6689: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6690: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6691: if (stepm >= YEARM) hstepm=1;
6692: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6693: gradg=matrix(1,npar,1,nlstate);
6694: mgp=matrix(1,npar,1,nlstate);
6695: mgm=matrix(1,npar,1,nlstate);
6696: gp=vector(1,nlstate);
6697: gm=vector(1,nlstate);
6698:
6699: for(theta=1; theta <=npar; theta++){
6700: for(i=1; i<=npar; i++){ /* Computes gradient */
6701: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6702: }
6703: if(mobilavproj > 0 )
6704: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6705: else
6706: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6707: for(i=1;i<=nlstate;i++){
6708: gp[i] = bprlim[i][i];
6709: mgp[theta][i] = bprlim[i][i];
6710: }
6711: for(i=1; i<=npar; i++) /* Computes gradient */
6712: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6713: if(mobilavproj > 0 )
6714: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6715: else
6716: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6717: for(i=1;i<=nlstate;i++){
6718: gm[i] = bprlim[i][i];
6719: mgm[theta][i] = bprlim[i][i];
6720: }
6721: for(i=1;i<=nlstate;i++)
6722: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6723: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6724: } /* End theta */
6725:
6726: trgradg =matrix(1,nlstate,1,npar);
6727:
6728: for(j=1; j<=nlstate;j++)
6729: for(theta=1; theta <=npar; theta++)
6730: trgradg[j][theta]=gradg[theta][j];
6731: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6732: /* printf("\nmgm mgp %d ",(int)age); */
6733: /* for(j=1; j<=nlstate;j++){ */
6734: /* printf(" %d ",j); */
6735: /* for(theta=1; theta <=npar; theta++) */
6736: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6737: /* printf("\n "); */
6738: /* } */
6739: /* } */
6740: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6741: /* printf("\n gradg %d ",(int)age); */
6742: /* for(j=1; j<=nlstate;j++){ */
6743: /* printf("%d ",j); */
6744: /* for(theta=1; theta <=npar; theta++) */
6745: /* printf("%d %lf ",theta,gradg[theta][j]); */
6746: /* printf("\n "); */
6747: /* } */
6748: /* } */
6749:
6750: for(i=1;i<=nlstate;i++)
6751: varbpl[i][(int)age] =0.;
6752: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6753: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6754: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6755: }else{
6756: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6757: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6758: }
6759: for(i=1;i<=nlstate;i++)
6760: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6761:
6762: fprintf(ficresvbl,"%.0f ",age );
6763: if(nresult >=1)
6764: fprintf(ficresvbl,"%d ",nres );
6765: for(i=1; i<=nlstate;i++)
6766: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6767: fprintf(ficresvbl,"\n");
6768: free_vector(gp,1,nlstate);
6769: free_vector(gm,1,nlstate);
6770: free_matrix(mgm,1,npar,1,nlstate);
6771: free_matrix(mgp,1,npar,1,nlstate);
6772: free_matrix(gradg,1,npar,1,nlstate);
6773: free_matrix(trgradg,1,nlstate,1,npar);
6774: } /* End age */
6775:
6776: free_vector(xp,1,npar);
6777: free_matrix(doldm,1,nlstate,1,npar);
6778: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6779:
6780: }
6781:
6782: /************ Variance of one-step probabilities ******************/
6783: 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 6784: {
6785: int i, j=0, k1, l1, tj;
6786: int k2, l2, j1, z1;
6787: int k=0, l;
6788: int first=1, first1, first2;
6789: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6790: double **dnewm,**doldm;
6791: double *xp;
6792: double *gp, *gm;
6793: double **gradg, **trgradg;
6794: double **mu;
6795: double age, cov[NCOVMAX+1];
6796: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6797: int theta;
6798: char fileresprob[FILENAMELENGTH];
6799: char fileresprobcov[FILENAMELENGTH];
6800: char fileresprobcor[FILENAMELENGTH];
6801: double ***varpij;
6802:
6803: strcpy(fileresprob,"PROB_");
6804: strcat(fileresprob,fileres);
6805: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6806: printf("Problem with resultfile: %s\n", fileresprob);
6807: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6808: }
6809: strcpy(fileresprobcov,"PROBCOV_");
6810: strcat(fileresprobcov,fileresu);
6811: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6812: printf("Problem with resultfile: %s\n", fileresprobcov);
6813: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6814: }
6815: strcpy(fileresprobcor,"PROBCOR_");
6816: strcat(fileresprobcor,fileresu);
6817: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6818: printf("Problem with resultfile: %s\n", fileresprobcor);
6819: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6820: }
6821: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6822: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6823: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6824: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6825: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6826: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6827: pstamp(ficresprob);
6828: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6829: fprintf(ficresprob,"# Age");
6830: pstamp(ficresprobcov);
6831: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6832: fprintf(ficresprobcov,"# Age");
6833: pstamp(ficresprobcor);
6834: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6835: fprintf(ficresprobcor,"# Age");
1.126 brouard 6836:
6837:
1.222 brouard 6838: for(i=1; i<=nlstate;i++)
6839: for(j=1; j<=(nlstate+ndeath);j++){
6840: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6841: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6842: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6843: }
6844: /* fprintf(ficresprob,"\n");
6845: fprintf(ficresprobcov,"\n");
6846: fprintf(ficresprobcor,"\n");
6847: */
6848: xp=vector(1,npar);
6849: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6850: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6851: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6852: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6853: first=1;
6854: fprintf(ficgp,"\n# Routine varprob");
6855: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6856: fprintf(fichtm,"\n");
6857:
1.288 brouard 6858: 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 6859: 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);
6860: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6861: and drawn. It helps understanding how is the covariance between two incidences.\
6862: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6863: 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 6864: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6865: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6866: standard deviations wide on each axis. <br>\
6867: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6868: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6869: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6870:
1.222 brouard 6871: cov[1]=1;
6872: /* tj=cptcoveff; */
1.225 brouard 6873: tj = (int) pow(2,cptcoveff);
1.222 brouard 6874: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6875: j1=0;
1.224 brouard 6876: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6877: if (cptcovn>0) {
6878: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6879: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6880: fprintf(ficresprob, "**********\n#\n");
6881: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6882: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6883: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6884:
1.222 brouard 6885: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6886: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6887: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6888:
6889:
1.222 brouard 6890: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.319 brouard 6891: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); */
6892: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtmcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6893: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6894:
1.222 brouard 6895: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6896: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6897: fprintf(ficresprobcor, "**********\n#");
6898: if(invalidvarcomb[j1]){
6899: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6900: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6901: continue;
6902: }
6903: }
6904: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6905: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6906: gp=vector(1,(nlstate)*(nlstate+ndeath));
6907: gm=vector(1,(nlstate)*(nlstate+ndeath));
6908: for (age=bage; age<=fage; age ++){
6909: cov[2]=age;
6910: if(nagesqr==1)
6911: cov[3]= age*age;
6912: for (k=1; k<=cptcovn;k++) {
6913: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6914: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6915: * 1 1 1 1 1
6916: * 2 2 1 1 1
6917: * 3 1 2 1 1
6918: */
6919: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6920: }
1.319 brouard 6921: /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 */
6922: /* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] */
6923: /*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6924: for (k=1; k<=cptcovage;k++)
6925: cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
1.222 brouard 6926: for (k=1; k<=cptcovprod;k++)
6927: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6928:
6929:
1.222 brouard 6930: for(theta=1; theta <=npar; theta++){
6931: for(i=1; i<=npar; i++)
6932: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6933:
1.222 brouard 6934: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6935:
1.222 brouard 6936: k=0;
6937: for(i=1; i<= (nlstate); i++){
6938: for(j=1; j<=(nlstate+ndeath);j++){
6939: k=k+1;
6940: gp[k]=pmmij[i][j];
6941: }
6942: }
1.220 brouard 6943:
1.222 brouard 6944: for(i=1; i<=npar; i++)
6945: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6946:
1.222 brouard 6947: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6948: k=0;
6949: for(i=1; i<=(nlstate); i++){
6950: for(j=1; j<=(nlstate+ndeath);j++){
6951: k=k+1;
6952: gm[k]=pmmij[i][j];
6953: }
6954: }
1.220 brouard 6955:
1.222 brouard 6956: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6957: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6958: }
1.126 brouard 6959:
1.222 brouard 6960: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6961: for(theta=1; theta <=npar; theta++)
6962: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6963:
1.222 brouard 6964: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6965: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6966:
1.222 brouard 6967: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6968:
1.222 brouard 6969: k=0;
6970: for(i=1; i<=(nlstate); i++){
6971: for(j=1; j<=(nlstate+ndeath);j++){
6972: k=k+1;
6973: mu[k][(int) age]=pmmij[i][j];
6974: }
6975: }
6976: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6977: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6978: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6979:
1.222 brouard 6980: /*printf("\n%d ",(int)age);
6981: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6982: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6983: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6984: }*/
1.220 brouard 6985:
1.222 brouard 6986: fprintf(ficresprob,"\n%d ",(int)age);
6987: fprintf(ficresprobcov,"\n%d ",(int)age);
6988: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6989:
1.222 brouard 6990: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6991: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6992: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6993: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6994: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6995: }
6996: i=0;
6997: for (k=1; k<=(nlstate);k++){
6998: for (l=1; l<=(nlstate+ndeath);l++){
6999: i++;
7000: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7001: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7002: for (j=1; j<=i;j++){
7003: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7004: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7005: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7006: }
7007: }
7008: }/* end of loop for state */
7009: } /* end of loop for age */
7010: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7011: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7012: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7013: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7014:
7015: /* Confidence intervalle of pij */
7016: /*
7017: fprintf(ficgp,"\nunset parametric;unset label");
7018: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7019: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7020: 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);
7021: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7022: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7023: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7024: */
7025:
7026: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7027: first1=1;first2=2;
7028: for (k2=1; k2<=(nlstate);k2++){
7029: for (l2=1; l2<=(nlstate+ndeath);l2++){
7030: if(l2==k2) continue;
7031: j=(k2-1)*(nlstate+ndeath)+l2;
7032: for (k1=1; k1<=(nlstate);k1++){
7033: for (l1=1; l1<=(nlstate+ndeath);l1++){
7034: if(l1==k1) continue;
7035: i=(k1-1)*(nlstate+ndeath)+l1;
7036: if(i<=j) continue;
7037: for (age=bage; age<=fage; age ++){
7038: if ((int)age %5==0){
7039: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7040: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7041: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7042: mu1=mu[i][(int) age]/stepm*YEARM ;
7043: mu2=mu[j][(int) age]/stepm*YEARM;
7044: c12=cv12/sqrt(v1*v2);
7045: /* Computing eigen value of matrix of covariance */
7046: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7047: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7048: if ((lc2 <0) || (lc1 <0) ){
7049: if(first2==1){
7050: first1=0;
7051: 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);
7052: }
7053: 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);
7054: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7055: /* lc2=fabs(lc2); */
7056: }
1.220 brouard 7057:
1.222 brouard 7058: /* Eigen vectors */
1.280 brouard 7059: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7060: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7061: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7062: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7063: }else
7064: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7065: /*v21=sqrt(1.-v11*v11); *//* error */
7066: v21=(lc1-v1)/cv12*v11;
7067: v12=-v21;
7068: v22=v11;
7069: tnalp=v21/v11;
7070: if(first1==1){
7071: first1=0;
7072: 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);
7073: }
7074: 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);
7075: /*printf(fignu*/
7076: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7077: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7078: if(first==1){
7079: first=0;
7080: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7081: fprintf(ficgp,"\nset parametric;unset label");
7082: 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);
7083: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7084: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7085: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7086: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7087: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7088: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7089: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7090: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7091: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7092: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7093: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7094: 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 7095: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
7096: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 7097: }else{
7098: first=0;
7099: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
7100: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7101: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7102: 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 7103: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
7104: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 7105: }/* if first */
7106: } /* age mod 5 */
7107: } /* end loop age */
7108: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7109: first=1;
7110: } /*l12 */
7111: } /* k12 */
7112: } /*l1 */
7113: }/* k1 */
7114: } /* loop on combination of covariates j1 */
7115: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
7116: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
7117: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7118: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
7119: free_vector(xp,1,npar);
7120: fclose(ficresprob);
7121: fclose(ficresprobcov);
7122: fclose(ficresprobcor);
7123: fflush(ficgp);
7124: fflush(fichtmcov);
7125: }
1.126 brouard 7126:
7127:
7128: /******************* Printing html file ***********/
1.201 brouard 7129: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 7130: int lastpass, int stepm, int weightopt, char model[],\
7131: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 7132: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
7133: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
7134: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 7135: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 7136: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 7137: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
7138: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
7139: </ul>");
1.319 brouard 7140: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
7141: /* </ul>", model); */
1.214 brouard 7142: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
7143: 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",
7144: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
7145: 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 7146: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
7147: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 7148: fprintf(fichtm,"\
7149: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 7150: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 7151: fprintf(fichtm,"\
1.217 brouard 7152: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
7153: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
7154: fprintf(fichtm,"\
1.288 brouard 7155: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7156: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 7157: fprintf(fichtm,"\
1.288 brouard 7158: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 7159: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
7160: fprintf(fichtm,"\
1.211 brouard 7161: - (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 7162: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 7163: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 7164: if(prevfcast==1){
7165: fprintf(fichtm,"\
7166: - Prevalence projections by age and states: \
1.201 brouard 7167: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 7168: }
1.126 brouard 7169:
7170:
1.225 brouard 7171: m=pow(2,cptcoveff);
1.222 brouard 7172: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7173:
1.317 brouard 7174: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 7175:
7176: jj1=0;
7177:
7178: fprintf(fichtm," \n<ul>");
7179: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7180: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7181: if(m != 1 && TKresult[nres]!= k1)
7182: continue;
7183: jj1++;
7184: if (cptcovn > 0) {
7185: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
7186: for (cpt=1; cpt<=cptcoveff;cpt++){
7187: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7188: }
7189: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7190: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7191: }
7192: fprintf(fichtm,"\">");
7193:
7194: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7195: fprintf(fichtm,"************ Results for covariates");
7196: for (cpt=1; cpt<=cptcoveff;cpt++){
7197: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7198: }
7199: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7200: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7201: }
7202: if(invalidvarcomb[k1]){
7203: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7204: continue;
7205: }
7206: fprintf(fichtm,"</a></li>");
7207: } /* cptcovn >0 */
7208: }
1.317 brouard 7209: fprintf(fichtm," \n</ul>");
1.264 brouard 7210:
1.222 brouard 7211: jj1=0;
1.237 brouard 7212:
7213: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 7214: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 7215: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7216: continue;
1.220 brouard 7217:
1.222 brouard 7218: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7219: jj1++;
7220: if (cptcovn > 0) {
1.264 brouard 7221: fprintf(fichtm,"\n<p><a name=\"rescov");
7222: for (cpt=1; cpt<=cptcoveff;cpt++){
7223: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7224: }
7225: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7226: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7227: }
7228: fprintf(fichtm,"\"</a>");
7229:
1.222 brouard 7230: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7231: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 7232: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7233: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
7234: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7235: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 7236: }
1.237 brouard 7237: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7238: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7239: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
7240: }
7241:
1.230 brouard 7242: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.321 ! brouard 7243: fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 7244: if(invalidvarcomb[k1]){
7245: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
7246: printf("\nCombination (%d) ignored because no cases \n",k1);
7247: continue;
7248: }
7249: }
7250: /* aij, bij */
1.259 brouard 7251: 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 7252: <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 7253: /* Pij */
1.241 brouard 7254: 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> \
7255: <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 7256: /* Quasi-incidences */
7257: 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 7258: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 7259: 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 7260: 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> \
7261: <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 7262: /* Survival functions (period) in state j */
7263: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7264: 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> \
1.241 brouard 7265: <img src=\"%s_%d-%d-%d.svg\">", cpt, cpt, nlstate, subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 7266: }
7267: /* State specific survival functions (period) */
7268: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7269: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
7270: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.283 brouard 7271: <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> <img src=\"%s_%d-%d-%d.svg\">", cpt, nlstate, cpt, subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 7272: }
1.288 brouard 7273: /* Period (forward stable) prevalence in each health state */
1.222 brouard 7274: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7275: 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> \
7276: <img src=\"%s_%d-%d-%d.svg\">", cpt, nlstate, cpt, subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 7277: }
1.296 brouard 7278: if(prevbcast==1){
1.288 brouard 7279: /* Backward prevalence in each health state */
1.222 brouard 7280: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7281: 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 7282: <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 7283: }
1.217 brouard 7284: }
1.222 brouard 7285: if(prevfcast==1){
1.288 brouard 7286: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7287: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 7288: 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);
7289: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
7290: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
7291: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 7292: }
7293: }
1.296 brouard 7294: if(prevbcast==1){
1.268 brouard 7295: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
7296: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 7297: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
7298: 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 \
7299: 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 7300: 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);
7301: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
7302: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 7303: }
7304: }
1.220 brouard 7305:
1.222 brouard 7306: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 7307: 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);
7308: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
7309: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 7310: }
7311: /* } /\* end i1 *\/ */
7312: }/* End k1 */
7313: fprintf(fichtm,"</ul>");
1.126 brouard 7314:
1.222 brouard 7315: fprintf(fichtm,"\
1.126 brouard 7316: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 7317: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 7318: - 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 7319: But because parameters are usually highly correlated (a higher incidence of disability \
7320: and a higher incidence of recovery can give very close observed transition) it might \
7321: be very useful to look not only at linear confidence intervals estimated from the \
7322: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
7323: (parameters) of the logistic regression, it might be more meaningful to visualize the \
7324: covariance matrix of the one-step probabilities. \
7325: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7326:
1.222 brouard 7327: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7328: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7329: fprintf(fichtm,"\
1.126 brouard 7330: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7331: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7332:
1.222 brouard 7333: fprintf(fichtm,"\
1.126 brouard 7334: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7335: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7336: fprintf(fichtm,"\
1.126 brouard 7337: - 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): \
7338: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7339: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7340: fprintf(fichtm,"\
1.126 brouard 7341: - (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): \
7342: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7343: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7344: fprintf(fichtm,"\
1.288 brouard 7345: - 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 7346: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7347: fprintf(fichtm,"\
1.128 brouard 7348: - 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 7349: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7350: fprintf(fichtm,"\
1.288 brouard 7351: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7352: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7353:
7354: /* if(popforecast==1) fprintf(fichtm,"\n */
7355: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7356: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7357: /* <br>",fileres,fileres,fileres,fileres); */
7358: /* else */
7359: /* 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 7360: fflush(fichtm);
1.126 brouard 7361:
1.225 brouard 7362: m=pow(2,cptcoveff);
1.222 brouard 7363: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7364:
1.317 brouard 7365: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
7366:
7367: jj1=0;
7368:
7369: fprintf(fichtm," \n<ul>");
7370: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7371: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
7372: if(m != 1 && TKresult[nres]!= k1)
7373: continue;
7374: jj1++;
7375: if (cptcovn > 0) {
7376: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
7377: for (cpt=1; cpt<=cptcoveff;cpt++){
7378: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7379: }
7380: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7381: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7382: }
7383: fprintf(fichtm,"\">");
7384:
7385: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
7386: fprintf(fichtm,"************ Results for covariates");
7387: for (cpt=1; cpt<=cptcoveff;cpt++){
7388: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7389: }
7390: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7391: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7392: }
7393: if(invalidvarcomb[k1]){
7394: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7395: continue;
7396: }
7397: fprintf(fichtm,"</a></li>");
7398: } /* cptcovn >0 */
7399: }
7400: fprintf(fichtm," \n</ul>");
7401:
1.222 brouard 7402: jj1=0;
1.237 brouard 7403:
1.241 brouard 7404: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7405: for(k1=1; k1<=m;k1++){
1.253 brouard 7406: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7407: continue;
1.222 brouard 7408: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7409: jj1++;
1.126 brouard 7410: if (cptcovn > 0) {
1.317 brouard 7411: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
7412: for (cpt=1; cpt<=cptcoveff;cpt++){
7413: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7414: }
7415: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7416: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7417: }
7418: fprintf(fichtm,"\"</a>");
7419:
1.126 brouard 7420: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.317 brouard 7421: for (cpt=1; cpt<=cptcoveff;cpt++){ /**< cptcoveff number of variables */
1.237 brouard 7422: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
1.317 brouard 7423: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
1.237 brouard 7424: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 7425: }
1.237 brouard 7426: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7427: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7428: }
7429:
1.321 ! brouard 7430: fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 7431:
1.222 brouard 7432: if(invalidvarcomb[k1]){
7433: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7434: continue;
7435: }
1.126 brouard 7436: }
7437: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7438: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 7439: 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);
7440: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
7441: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 7442: }
7443: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 7444: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 7445: true period expectancies (those weighted with period prevalences are also\
7446: drawn in addition to the population based expectancies computed using\
1.314 brouard 7447: 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);
7448: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
7449: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7450: /* } /\* end i1 *\/ */
7451: }/* End k1 */
1.241 brouard 7452: }/* End nres */
1.222 brouard 7453: fprintf(fichtm,"</ul>");
7454: fflush(fichtm);
1.126 brouard 7455: }
7456:
7457: /******************* Gnuplot file **************/
1.296 brouard 7458: 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 7459:
7460: char dirfileres[132],optfileres[132];
1.264 brouard 7461: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7462: 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 7463: int lv=0, vlv=0, kl=0;
1.130 brouard 7464: int ng=0;
1.201 brouard 7465: int vpopbased;
1.223 brouard 7466: int ioffset; /* variable offset for columns */
1.270 brouard 7467: int iyearc=1; /* variable column for year of projection */
7468: int iagec=1; /* variable column for age of projection */
1.235 brouard 7469: int nres=0; /* Index of resultline */
1.266 brouard 7470: int istart=1; /* For starting graphs in projections */
1.219 brouard 7471:
1.126 brouard 7472: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7473: /* printf("Problem with file %s",optionfilegnuplot); */
7474: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7475: /* } */
7476:
7477: /*#ifdef windows */
7478: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7479: /*#endif */
1.225 brouard 7480: m=pow(2,cptcoveff);
1.126 brouard 7481:
1.274 brouard 7482: /* diagram of the model */
7483: fprintf(ficgp,"\n#Diagram of the model \n");
7484: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7485: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7486: 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);
7487:
7488: 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);
7489: fprintf(ficgp,"\n#show arrow\nunset label\n");
7490: 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);
7491: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7492: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7493: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7494: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7495:
1.202 brouard 7496: /* Contribution to likelihood */
7497: /* Plot the probability implied in the likelihood */
1.223 brouard 7498: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7499: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7500: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7501: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7502: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7503: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7504: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7505: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7506: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7507: 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));
7508: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7509: 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));
7510: for (i=1; i<= nlstate ; i ++) {
7511: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7512: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7513: 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);
7514: for (j=2; j<= nlstate+ndeath ; j ++) {
7515: 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);
7516: }
7517: fprintf(ficgp,";\nset out; unset ylabel;\n");
7518: }
7519: /* 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 */
7520: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7521: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7522: fprintf(ficgp,"\nset out;unset log\n");
7523: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7524:
1.126 brouard 7525: strcpy(dirfileres,optionfilefiname);
7526: strcpy(optfileres,"vpl");
1.223 brouard 7527: /* 1eme*/
1.238 brouard 7528: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7529: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7530: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7531: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7532: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7533: continue;
7534: /* We are interested in selected combination by the resultline */
1.246 brouard 7535: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7536: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7537: strcpy(gplotlabel,"(");
1.238 brouard 7538: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7539: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7540: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7541: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7542: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7543: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7544: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7545: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7546: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7547: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7548: }
7549: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7550: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7551: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7552: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7553: }
7554: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7555: /* printf("\n#\n"); */
1.238 brouard 7556: fprintf(ficgp,"\n#\n");
7557: if(invalidvarcomb[k1]){
1.260 brouard 7558: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7559: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7560: continue;
7561: }
1.235 brouard 7562:
1.241 brouard 7563: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7564: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7565: /* 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 7566: fprintf(ficgp,"set title \"Alive state %d %s model=%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 7567: 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);
7568: /* 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); */
7569: /* k1-1 error should be nres-1*/
1.238 brouard 7570: for (i=1; i<= nlstate ; i ++) {
7571: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7572: else fprintf(ficgp," %%*lf (%%*lf)");
7573: }
1.288 brouard 7574: 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 7575: for (i=1; i<= nlstate ; i ++) {
7576: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7577: else fprintf(ficgp," %%*lf (%%*lf)");
7578: }
1.260 brouard 7579: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7580: for (i=1; i<= nlstate ; i ++) {
7581: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7582: else fprintf(ficgp," %%*lf (%%*lf)");
7583: }
1.265 brouard 7584: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7585:
7586: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7587: if(cptcoveff ==0){
1.271 brouard 7588: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7589: }else{
7590: kl=0;
7591: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7592: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7593: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7594: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7595: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7596: vlv= nbcode[Tvaraff[k]][lv];
7597: kl++;
7598: /* 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 *\/ */
7599: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7600: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7601: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7602: if(k==cptcoveff){
7603: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7604: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7605: }else{
7606: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7607: kl++;
7608: }
7609: } /* end covariate */
7610: } /* end if no covariate */
7611:
1.296 brouard 7612: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 7613: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7614: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7615: if(cptcoveff ==0){
1.245 brouard 7616: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7617: }else{
7618: kl=0;
7619: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7620: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7621: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7622: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7623: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7624: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7625: kl++;
1.238 brouard 7626: /* 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 *\/ */
7627: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7628: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7629: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7630: if(k==cptcoveff){
1.245 brouard 7631: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7632: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7633: }else{
7634: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7635: kl++;
7636: }
7637: } /* end covariate */
7638: } /* end if no covariate */
1.296 brouard 7639: if(prevbcast == 1){
1.268 brouard 7640: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7641: /* k1-1 error should be nres-1*/
7642: for (i=1; i<= nlstate ; i ++) {
7643: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7644: else fprintf(ficgp," %%*lf (%%*lf)");
7645: }
1.271 brouard 7646: 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 7647: for (i=1; i<= nlstate ; i ++) {
7648: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7649: else fprintf(ficgp," %%*lf (%%*lf)");
7650: }
1.276 brouard 7651: 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 7652: for (i=1; i<= nlstate ; i ++) {
7653: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7654: else fprintf(ficgp," %%*lf (%%*lf)");
7655: }
1.274 brouard 7656: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7657: } /* end if backprojcast */
1.296 brouard 7658: } /* end if prevbcast */
1.276 brouard 7659: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7660: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7661: } /* nres */
1.201 brouard 7662: } /* k1 */
7663: } /* cpt */
1.235 brouard 7664:
7665:
1.126 brouard 7666: /*2 eme*/
1.238 brouard 7667: for (k1=1; k1<= m ; k1 ++){
7668: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7669: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7670: continue;
7671: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7672: strcpy(gplotlabel,"(");
1.238 brouard 7673: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7674: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7675: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7676: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7677: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7678: vlv= nbcode[Tvaraff[k]][lv];
7679: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7680: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7681: }
1.237 brouard 7682: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7683: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7684: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7685: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7686: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7687: }
1.264 brouard 7688: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7689: fprintf(ficgp,"\n#\n");
1.223 brouard 7690: if(invalidvarcomb[k1]){
7691: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7692: continue;
7693: }
1.219 brouard 7694:
1.241 brouard 7695: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7696: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7697: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7698: if(vpopbased==0){
1.238 brouard 7699: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7700: }else
1.238 brouard 7701: fprintf(ficgp,"\nreplot ");
7702: for (i=1; i<= nlstate+1 ; i ++) {
7703: k=2*i;
1.261 brouard 7704: 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 7705: for (j=1; j<= nlstate+1 ; j ++) {
7706: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7707: else fprintf(ficgp," %%*lf (%%*lf)");
7708: }
7709: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7710: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7711: 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 7712: for (j=1; j<= nlstate+1 ; j ++) {
7713: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7714: else fprintf(ficgp," %%*lf (%%*lf)");
7715: }
7716: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7717: 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 7718: for (j=1; j<= nlstate+1 ; j ++) {
7719: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7720: else fprintf(ficgp," %%*lf (%%*lf)");
7721: }
7722: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7723: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7724: } /* state */
7725: } /* vpopbased */
1.264 brouard 7726: 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 7727: } /* end nres */
7728: } /* k1 end 2 eme*/
7729:
7730:
7731: /*3eme*/
7732: for (k1=1; k1<= m ; k1 ++){
7733: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7734: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7735: continue;
7736:
7737: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7738: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7739: strcpy(gplotlabel,"(");
1.238 brouard 7740: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7741: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7742: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7743: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7744: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7745: vlv= nbcode[Tvaraff[k]][lv];
7746: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7747: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7748: }
7749: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7750: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7751: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7752: }
1.264 brouard 7753: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7754: fprintf(ficgp,"\n#\n");
7755: if(invalidvarcomb[k1]){
7756: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7757: continue;
7758: }
7759:
7760: /* k=2+nlstate*(2*cpt-2); */
7761: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7762: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7763: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7764: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7765: 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 7766: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7767: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7768: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7769: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7770: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7771: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7772:
1.238 brouard 7773: */
7774: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7775: 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 7776: /* 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 7777:
1.238 brouard 7778: }
1.261 brouard 7779: 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 7780: }
1.264 brouard 7781: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7782: } /* end nres */
7783: } /* end kl 3eme */
1.126 brouard 7784:
1.223 brouard 7785: /* 4eme */
1.201 brouard 7786: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7787: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7788: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7789: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7790: continue;
1.238 brouard 7791: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7792: strcpy(gplotlabel,"(");
1.238 brouard 7793: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7794: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7795: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7796: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7797: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7798: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7799: vlv= nbcode[Tvaraff[k]][lv];
7800: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7801: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7802: }
7803: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7804: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7805: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7806: }
1.264 brouard 7807: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7808: fprintf(ficgp,"\n#\n");
7809: if(invalidvarcomb[k1]){
7810: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7811: continue;
1.223 brouard 7812: }
1.238 brouard 7813:
1.241 brouard 7814: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7815: 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 7816: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7817: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7818: k=3;
7819: for (i=1; i<= nlstate ; i ++){
7820: if(i==1){
7821: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7822: }else{
7823: fprintf(ficgp,", '' ");
7824: }
7825: l=(nlstate+ndeath)*(i-1)+1;
7826: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7827: for (j=2; j<= nlstate+ndeath ; j ++)
7828: fprintf(ficgp,"+$%d",k+l+j-1);
7829: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7830: } /* nlstate */
1.264 brouard 7831: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7832: } /* end cpt state*/
7833: } /* end nres */
7834: } /* end covariate k1 */
7835:
1.220 brouard 7836: /* 5eme */
1.201 brouard 7837: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7838: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7839: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7840: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7841: continue;
1.238 brouard 7842: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7843: strcpy(gplotlabel,"(");
1.238 brouard 7844: 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);
7845: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7846: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7847: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7848: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7849: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7850: vlv= nbcode[Tvaraff[k]][lv];
7851: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7852: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7853: }
7854: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7855: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7856: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7857: }
1.264 brouard 7858: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7859: fprintf(ficgp,"\n#\n");
7860: if(invalidvarcomb[k1]){
7861: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7862: continue;
7863: }
1.227 brouard 7864:
1.241 brouard 7865: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7866: 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 7867: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7868: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7869: k=3;
7870: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7871: if(j==1)
7872: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7873: else
7874: fprintf(ficgp,", '' ");
7875: l=(nlstate+ndeath)*(cpt-1) +j;
7876: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7877: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7878: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7879: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7880: } /* nlstate */
7881: fprintf(ficgp,", '' ");
7882: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7883: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7884: l=(nlstate+ndeath)*(cpt-1) +j;
7885: if(j < nlstate)
7886: fprintf(ficgp,"$%d +",k+l);
7887: else
7888: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7889: }
1.264 brouard 7890: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7891: } /* end cpt state*/
7892: } /* end covariate */
7893: } /* end nres */
1.227 brouard 7894:
1.220 brouard 7895: /* 6eme */
1.202 brouard 7896: /* CV preval stable (period) for each covariate */
1.237 brouard 7897: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7898: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7899: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7900: continue;
1.255 brouard 7901: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7902: strcpy(gplotlabel,"(");
1.288 brouard 7903: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7904: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7905: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7906: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7907: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7908: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7909: vlv= nbcode[Tvaraff[k]][lv];
7910: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7911: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7912: }
1.237 brouard 7913: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7914: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7915: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7916: }
1.264 brouard 7917: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7918: fprintf(ficgp,"\n#\n");
1.223 brouard 7919: if(invalidvarcomb[k1]){
1.227 brouard 7920: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7921: continue;
1.223 brouard 7922: }
1.227 brouard 7923:
1.241 brouard 7924: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7925: 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 7926: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7927: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7928: k=3; /* Offset */
1.255 brouard 7929: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7930: if(i==1)
7931: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7932: else
7933: fprintf(ficgp,", '' ");
1.255 brouard 7934: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7935: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7936: for (j=2; j<= nlstate ; j ++)
7937: fprintf(ficgp,"+$%d",k+l+j-1);
7938: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7939: } /* nlstate */
1.264 brouard 7940: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7941: } /* end cpt state*/
7942: } /* end covariate */
1.227 brouard 7943:
7944:
1.220 brouard 7945: /* 7eme */
1.296 brouard 7946: if(prevbcast == 1){
1.288 brouard 7947: /* CV backward prevalence for each covariate */
1.237 brouard 7948: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7949: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7950: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7951: continue;
1.268 brouard 7952: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7953: strcpy(gplotlabel,"(");
1.288 brouard 7954: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7955: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7956: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7957: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7958: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7959: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7960: vlv= nbcode[Tvaraff[k]][lv];
7961: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7962: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7963: }
1.237 brouard 7964: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7965: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7966: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7967: }
1.264 brouard 7968: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7969: fprintf(ficgp,"\n#\n");
7970: if(invalidvarcomb[k1]){
7971: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7972: continue;
7973: }
7974:
1.241 brouard 7975: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7976: 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 7977: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7978: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7979: k=3; /* Offset */
1.268 brouard 7980: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7981: if(i==1)
7982: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7983: else
7984: fprintf(ficgp,", '' ");
7985: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7986: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7987: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7988: /* 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 7989: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7990: /* for (j=2; j<= nlstate ; j ++) */
7991: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7992: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7993: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7994: } /* nlstate */
1.264 brouard 7995: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7996: } /* end cpt state*/
7997: } /* end covariate */
1.296 brouard 7998: } /* End if prevbcast */
1.218 brouard 7999:
1.223 brouard 8000: /* 8eme */
1.218 brouard 8001: if(prevfcast==1){
1.288 brouard 8002: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 8003:
1.237 brouard 8004: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8005: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 8006: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8007: continue;
1.211 brouard 8008: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 8009: strcpy(gplotlabel,"(");
1.288 brouard 8010: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 8011: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8012: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8013: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8014: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8015: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8016: vlv= nbcode[Tvaraff[k]][lv];
8017: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 8018: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 8019: }
1.237 brouard 8020: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8021: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8022: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 8023: }
1.264 brouard 8024: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 8025: fprintf(ficgp,"\n#\n");
8026: if(invalidvarcomb[k1]){
8027: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8028: continue;
8029: }
8030:
8031: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 8032: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 8033: 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 8034: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 8035: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 8036:
8037: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8038: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8039: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8040: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 8041: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8042: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8043: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8044: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 8045: if(i==istart){
1.227 brouard 8046: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
8047: }else{
8048: fprintf(ficgp,",\\\n '' ");
8049: }
8050: if(cptcoveff ==0){ /* No covariate */
8051: ioffset=2; /* Age is in 2 */
8052: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8053: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8054: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8055: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8056: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 8057: if(i==nlstate+1){
1.270 brouard 8058: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 8059: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8060: fprintf(ficgp,",\\\n '' ");
8061: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8062: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 8063: offyear, \
1.268 brouard 8064: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 8065: }else
1.227 brouard 8066: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
8067: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8068: }else{ /* more than 2 covariates */
1.270 brouard 8069: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8070: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8071: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8072: iyearc=ioffset-1;
8073: iagec=ioffset;
1.227 brouard 8074: fprintf(ficgp," u %d:(",ioffset);
8075: kl=0;
8076: strcpy(gplotcondition,"(");
8077: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
8078: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
8079: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8080: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8081: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8082: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
8083: kl++;
8084: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8085: kl++;
8086: if(k <cptcoveff && cptcoveff>1)
8087: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8088: }
8089: strcpy(gplotcondition+strlen(gplotcondition),")");
8090: /* 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 *\/ */
8091: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8092: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8093: /* '' 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*/
8094: if(i==nlstate+1){
1.270 brouard 8095: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
8096: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 8097: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8098: fprintf(ficgp," u %d:(",iagec);
8099: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
8100: iyearc, iagec, offyear, \
8101: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 8102: /* '' 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 8103: }else{
8104: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
8105: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
8106: }
8107: } /* end if covariate */
8108: } /* nlstate */
1.264 brouard 8109: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 8110: } /* end cpt state*/
8111: } /* end covariate */
8112: } /* End if prevfcast */
1.227 brouard 8113:
1.296 brouard 8114: if(prevbcast==1){
1.268 brouard 8115: /* Back projection from cross-sectional to stable (mixed) for each covariate */
8116:
8117: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
8118: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8119: if(m != 1 && TKresult[nres]!= k1)
8120: continue;
8121: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
8122: strcpy(gplotlabel,"(");
8123: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
8124: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8125: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8126: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8127: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8128: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8129: vlv= nbcode[Tvaraff[k]][lv];
8130: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8131: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8132: }
8133: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8134: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8135: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8136: }
8137: strcpy(gplotlabel+strlen(gplotlabel),")");
8138: fprintf(ficgp,"\n#\n");
8139: if(invalidvarcomb[k1]){
8140: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8141: continue;
8142: }
8143:
8144: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
8145: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
8146: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
8147: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
8148: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8149:
8150: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
8151: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
8152: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
8153: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
8154: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8155: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8156: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
8157: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
8158: if(i==istart){
8159: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
8160: }else{
8161: fprintf(ficgp,",\\\n '' ");
8162: }
8163: if(cptcoveff ==0){ /* No covariate */
8164: ioffset=2; /* Age is in 2 */
8165: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8166: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8167: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
8168: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
8169: fprintf(ficgp," u %d:(", ioffset);
8170: if(i==nlstate+1){
1.270 brouard 8171: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 8172: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
8173: fprintf(ficgp,",\\\n '' ");
8174: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 8175: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 8176: offbyear, \
8177: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
8178: }else
8179: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
8180: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
8181: }else{ /* more than 2 covariates */
1.270 brouard 8182: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
8183: /*# V1 = 1 V2 = 0 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 */
8185: iyearc=ioffset-1;
8186: iagec=ioffset;
1.268 brouard 8187: fprintf(ficgp," u %d:(",ioffset);
8188: kl=0;
8189: strcpy(gplotcondition,"(");
8190: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
8191: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
8192: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8193: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8194: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8195: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
8196: kl++;
8197: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
8198: kl++;
8199: if(k <cptcoveff && cptcoveff>1)
8200: sprintf(gplotcondition+strlen(gplotcondition)," && ");
8201: }
8202: strcpy(gplotcondition+strlen(gplotcondition),")");
8203: /* 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 *\/ */
8204: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8205: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8206: /* '' 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*/
8207: if(i==nlstate+1){
1.270 brouard 8208: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
8209: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 8210: fprintf(ficgp,",\\\n '' ");
1.270 brouard 8211: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 8212: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 8213: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
8214: iyearc,iagec,offbyear, \
8215: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 8216: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
8217: }else{
8218: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
8219: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
8220: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
8221: }
8222: } /* end if covariate */
8223: } /* nlstate */
8224: fprintf(ficgp,"\nset out; unset label;\n");
8225: } /* end cpt state*/
8226: } /* end covariate */
1.296 brouard 8227: } /* End if prevbcast */
1.268 brouard 8228:
1.227 brouard 8229:
1.238 brouard 8230: /* 9eme writing MLE parameters */
8231: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 8232: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 8233: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 8234: for(k=1; k <=(nlstate+ndeath); k++){
8235: if (k != i) {
1.227 brouard 8236: fprintf(ficgp,"# current state %d\n",k);
8237: for(j=1; j <=ncovmodel; j++){
8238: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
8239: jk++;
8240: }
8241: fprintf(ficgp,"\n");
1.126 brouard 8242: }
8243: }
1.223 brouard 8244: }
1.187 brouard 8245: fprintf(ficgp,"##############\n#\n");
1.227 brouard 8246:
1.145 brouard 8247: /*goto avoid;*/
1.238 brouard 8248: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
8249: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 8250: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
8251: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
8252: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
8253: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
8254: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8255: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8256: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8257: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8258: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
8259: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8260: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
8261: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
8262: fprintf(ficgp,"#\n");
1.223 brouard 8263: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 8264: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 8265: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 8266: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 8267: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
8268: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 8269: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 8270: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8271: continue;
1.264 brouard 8272: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
8273: strcpy(gplotlabel,"(");
1.276 brouard 8274: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 8275: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8276: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8277: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8278: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8279: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8280: vlv= nbcode[Tvaraff[k]][lv];
8281: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8282: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8283: }
1.237 brouard 8284: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8285: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8286: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 8287: }
1.264 brouard 8288: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 8289: fprintf(ficgp,"\n#\n");
1.264 brouard 8290: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 8291: fprintf(ficgp,"\nset key outside ");
8292: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
8293: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 8294: fprintf(ficgp,"\nset ter svg size 640, 480 ");
8295: if (ng==1){
8296: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
8297: fprintf(ficgp,"\nunset log y");
8298: }else if (ng==2){
8299: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
8300: fprintf(ficgp,"\nset log y");
8301: }else if (ng==3){
8302: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
8303: fprintf(ficgp,"\nset log y");
8304: }else
8305: fprintf(ficgp,"\nunset title ");
8306: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
8307: i=1;
8308: for(k2=1; k2<=nlstate; k2++) {
8309: k3=i;
8310: for(k=1; k<=(nlstate+ndeath); k++) {
8311: if (k != k2){
8312: switch( ng) {
8313: case 1:
8314: if(nagesqr==0)
8315: fprintf(ficgp," p%d+p%d*x",i,i+1);
8316: else /* nagesqr =1 */
8317: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8318: break;
8319: case 2: /* ng=2 */
8320: if(nagesqr==0)
8321: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
8322: else /* nagesqr =1 */
8323: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8324: break;
8325: case 3:
8326: if(nagesqr==0)
8327: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
8328: else /* nagesqr =1 */
8329: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
8330: break;
8331: }
8332: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 8333: ijp=1; /* product no age */
8334: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
8335: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 8336: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 8337: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8338: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
8339: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8340: if(DummyV[j]==0){
8341: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
8342: }else{ /* quantitative */
8343: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8344: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8345: }
8346: ij++;
1.237 brouard 8347: }
1.268 brouard 8348: }
8349: }else if(cptcovprod >0){
8350: if(j==Tprod[ijp]) { /* */
8351: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8352: if(ijp <=cptcovprod) { /* Product */
8353: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8354: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8355: /* 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)]); */
8356: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8357: }else{ /* Vn is dummy and Vm is quanti */
8358: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8359: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8360: }
8361: }else{ /* Vn*Vm Vn is quanti */
8362: if(DummyV[Tvard[ijp][2]]==0){
8363: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8364: }else{ /* Both quanti */
8365: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8366: }
1.237 brouard 8367: }
1.268 brouard 8368: ijp++;
1.237 brouard 8369: }
1.268 brouard 8370: } /* end Tprod */
1.237 brouard 8371: } else{ /* simple covariate */
1.264 brouard 8372: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 8373: if(Dummy[j]==0){
8374: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
8375: }else{ /* quantitative */
8376: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 8377: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 8378: }
1.237 brouard 8379: } /* end simple */
8380: } /* end j */
1.223 brouard 8381: }else{
8382: i=i-ncovmodel;
8383: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
8384: fprintf(ficgp," (1.");
8385: }
1.227 brouard 8386:
1.223 brouard 8387: if(ng != 1){
8388: fprintf(ficgp,")/(1");
1.227 brouard 8389:
1.264 brouard 8390: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8391: if(nagesqr==0)
1.264 brouard 8392: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8393: else /* nagesqr =1 */
1.264 brouard 8394: 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 8395:
1.223 brouard 8396: ij=1;
8397: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 8398: if(cptcovage >0){
8399: if((j-2)==Tage[ij]) { /* Bug valgrind */
8400: if(ij <=cptcovage) { /* Bug valgrind */
8401: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
8402: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8403: ij++;
8404: }
8405: }
8406: }else
8407: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/* Valgrind bug nbcode */
1.223 brouard 8408: }
8409: fprintf(ficgp,")");
8410: }
8411: fprintf(ficgp,")");
8412: if(ng ==2)
1.276 brouard 8413: 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 8414: else /* ng= 3 */
1.276 brouard 8415: 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);
1.223 brouard 8416: }else{ /* end ng <> 1 */
8417: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8418: 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 8419: }
8420: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8421: fprintf(ficgp,",");
8422: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8423: fprintf(ficgp,",");
8424: i=i+ncovmodel;
8425: } /* end k */
8426: } /* end k2 */
1.276 brouard 8427: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8428: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8429: } /* end k1 */
1.223 brouard 8430: } /* end ng */
8431: /* avoid: */
8432: fflush(ficgp);
1.126 brouard 8433: } /* end gnuplot */
8434:
8435:
8436: /*************** Moving average **************/
1.219 brouard 8437: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8438: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8439:
1.222 brouard 8440: int i, cpt, cptcod;
8441: int modcovmax =1;
8442: int mobilavrange, mob;
8443: int iage=0;
1.288 brouard 8444: int firstA1=0, firstA2=0;
1.222 brouard 8445:
1.266 brouard 8446: double sum=0., sumr=0.;
1.222 brouard 8447: double age;
1.266 brouard 8448: double *sumnewp, *sumnewm, *sumnewmr;
8449: double *agemingood, *agemaxgood;
8450: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8451:
8452:
1.278 brouard 8453: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8454: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8455:
8456: sumnewp = vector(1,ncovcombmax);
8457: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8458: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8459: agemingood = vector(1,ncovcombmax);
1.266 brouard 8460: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8461: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8462: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8463:
8464: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8465: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8466: sumnewp[cptcod]=0.;
1.266 brouard 8467: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8468: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8469: }
8470: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8471:
1.266 brouard 8472: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8473: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8474: else mobilavrange=mobilav;
8475: for (age=bage; age<=fage; age++)
8476: for (i=1; i<=nlstate;i++)
8477: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8478: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8479: /* We keep the original values on the extreme ages bage, fage and for
8480: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8481: we use a 5 terms etc. until the borders are no more concerned.
8482: */
8483: for (mob=3;mob <=mobilavrange;mob=mob+2){
8484: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8485: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8486: sumnewm[cptcod]=0.;
8487: for (i=1; i<=nlstate;i++){
1.222 brouard 8488: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8489: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8490: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8491: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8492: }
8493: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8494: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8495: } /* end i */
8496: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8497: } /* end cptcod */
1.222 brouard 8498: }/* end age */
8499: }/* end mob */
1.266 brouard 8500: }else{
8501: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8502: return -1;
1.266 brouard 8503: }
8504:
8505: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8506: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8507: if(invalidvarcomb[cptcod]){
8508: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8509: continue;
8510: }
1.219 brouard 8511:
1.266 brouard 8512: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8513: sumnewm[cptcod]=0.;
8514: sumnewmr[cptcod]=0.;
8515: for (i=1; i<=nlstate;i++){
8516: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8517: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8518: }
8519: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8520: agemingoodr[cptcod]=age;
8521: }
8522: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8523: agemingood[cptcod]=age;
8524: }
8525: } /* age */
8526: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8527: sumnewm[cptcod]=0.;
1.266 brouard 8528: sumnewmr[cptcod]=0.;
1.222 brouard 8529: for (i=1; i<=nlstate;i++){
8530: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8531: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8532: }
8533: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8534: agemaxgoodr[cptcod]=age;
1.222 brouard 8535: }
8536: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8537: agemaxgood[cptcod]=age;
8538: }
8539: } /* age */
8540: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8541: /* but they will change */
1.288 brouard 8542: firstA1=0;firstA2=0;
1.266 brouard 8543: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8544: sumnewm[cptcod]=0.;
8545: sumnewmr[cptcod]=0.;
8546: for (i=1; i<=nlstate;i++){
8547: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8548: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8549: }
8550: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8551: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8552: agemaxgoodr[cptcod]=age; /* age min */
8553: for (i=1; i<=nlstate;i++)
8554: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8555: }else{ /* bad we change the value with the values of good ages */
8556: for (i=1; i<=nlstate;i++){
8557: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8558: } /* i */
8559: } /* end bad */
8560: }else{
8561: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8562: agemaxgood[cptcod]=age;
8563: }else{ /* bad we change the value with the values of good ages */
8564: for (i=1; i<=nlstate;i++){
8565: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8566: } /* i */
8567: } /* end bad */
8568: }/* end else */
8569: sum=0.;sumr=0.;
8570: for (i=1; i<=nlstate;i++){
8571: sum+=mobaverage[(int)age][i][cptcod];
8572: sumr+=probs[(int)age][i][cptcod];
8573: }
8574: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8575: if(!firstA1){
8576: firstA1=1;
8577: 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);
8578: }
8579: 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 8580: } /* end bad */
8581: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8582: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 8583: if(!firstA2){
8584: firstA2=1;
8585: 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);
8586: }
8587: 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 8588: } /* end bad */
8589: }/* age */
1.266 brouard 8590:
8591: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8592: sumnewm[cptcod]=0.;
1.266 brouard 8593: sumnewmr[cptcod]=0.;
1.222 brouard 8594: for (i=1; i<=nlstate;i++){
8595: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8596: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8597: }
8598: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8599: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8600: agemingoodr[cptcod]=age;
8601: for (i=1; i<=nlstate;i++)
8602: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8603: }else{ /* bad we change the value with the values of good ages */
8604: for (i=1; i<=nlstate;i++){
8605: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8606: } /* i */
8607: } /* end bad */
8608: }else{
8609: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8610: agemingood[cptcod]=age;
8611: }else{ /* bad */
8612: for (i=1; i<=nlstate;i++){
8613: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8614: } /* i */
8615: } /* end bad */
8616: }/* end else */
8617: sum=0.;sumr=0.;
8618: for (i=1; i<=nlstate;i++){
8619: sum+=mobaverage[(int)age][i][cptcod];
8620: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8621: }
1.266 brouard 8622: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8623: 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 8624: } /* end bad */
8625: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8626: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8627: 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 8628: } /* end bad */
8629: }/* age */
1.266 brouard 8630:
1.222 brouard 8631:
8632: for (age=bage; age<=fage; age++){
1.235 brouard 8633: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8634: sumnewp[cptcod]=0.;
8635: sumnewm[cptcod]=0.;
8636: for (i=1; i<=nlstate;i++){
8637: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8638: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8639: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8640: }
8641: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8642: }
8643: /* printf("\n"); */
8644: /* } */
1.266 brouard 8645:
1.222 brouard 8646: /* brutal averaging */
1.266 brouard 8647: /* for (i=1; i<=nlstate;i++){ */
8648: /* for (age=1; age<=bage; age++){ */
8649: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8650: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8651: /* } */
8652: /* for (age=fage; age<=AGESUP; age++){ */
8653: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8654: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8655: /* } */
8656: /* } /\* end i status *\/ */
8657: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8658: /* for (age=1; age<=AGESUP; age++){ */
8659: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8660: /* mobaverage[(int)age][i][cptcod]=0.; */
8661: /* } */
8662: /* } */
1.222 brouard 8663: }/* end cptcod */
1.266 brouard 8664: free_vector(agemaxgoodr,1, ncovcombmax);
8665: free_vector(agemaxgood,1, ncovcombmax);
8666: free_vector(agemingood,1, ncovcombmax);
8667: free_vector(agemingoodr,1, ncovcombmax);
8668: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8669: free_vector(sumnewm,1, ncovcombmax);
8670: free_vector(sumnewp,1, ncovcombmax);
8671: return 0;
8672: }/* End movingaverage */
1.218 brouard 8673:
1.126 brouard 8674:
1.296 brouard 8675:
1.126 brouard 8676: /************** Forecasting ******************/
1.296 brouard 8677: /* 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)*/
8678: 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){
8679: /* dateintemean, mean date of interviews
8680: dateprojd, year, month, day of starting projection
8681: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 8682: agemin, agemax range of age
8683: dateprev1 dateprev2 range of dates during which prevalence is computed
8684: */
1.296 brouard 8685: /* double anprojd, mprojd, jprojd; */
8686: /* double anprojf, mprojf, jprojf; */
1.267 brouard 8687: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8688: double agec; /* generic age */
1.296 brouard 8689: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 8690: double *popeffectif,*popcount;
8691: double ***p3mat;
1.218 brouard 8692: /* double ***mobaverage; */
1.126 brouard 8693: char fileresf[FILENAMELENGTH];
8694:
8695: agelim=AGESUP;
1.211 brouard 8696: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8697: in each health status at the date of interview (if between dateprev1 and dateprev2).
8698: We still use firstpass and lastpass as another selection.
8699: */
1.214 brouard 8700: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8701: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8702:
1.201 brouard 8703: strcpy(fileresf,"F_");
8704: strcat(fileresf,fileresu);
1.126 brouard 8705: if((ficresf=fopen(fileresf,"w"))==NULL) {
8706: printf("Problem with forecast resultfile: %s\n", fileresf);
8707: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8708: }
1.235 brouard 8709: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8710: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8711:
1.225 brouard 8712: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8713:
8714:
8715: stepsize=(int) (stepm+YEARM-1)/YEARM;
8716: if (stepm<=12) stepsize=1;
8717: if(estepm < stepm){
8718: printf ("Problem %d lower than %d\n",estepm, stepm);
8719: }
1.270 brouard 8720: else{
8721: hstepm=estepm;
8722: }
8723: if(estepm > stepm){ /* Yes every two year */
8724: stepsize=2;
8725: }
1.296 brouard 8726: hstepm=hstepm/stepm;
1.126 brouard 8727:
1.296 brouard 8728:
8729: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8730: /* fractional in yp1 *\/ */
8731: /* aintmean=yp; */
8732: /* yp2=modf((yp1*12),&yp); */
8733: /* mintmean=yp; */
8734: /* yp1=modf((yp2*30.5),&yp); */
8735: /* jintmean=yp; */
8736: /* if(jintmean==0) jintmean=1; */
8737: /* if(mintmean==0) mintmean=1; */
1.126 brouard 8738:
1.296 brouard 8739:
8740: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
8741: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
8742: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 8743: i1=pow(2,cptcoveff);
1.126 brouard 8744: if (cptcovn < 1){i1=1;}
8745:
1.296 brouard 8746: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 8747:
8748: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8749:
1.126 brouard 8750: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8751: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8752: for(k=1; k<=i1;k++){
1.253 brouard 8753: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8754: continue;
1.227 brouard 8755: if(invalidvarcomb[k]){
8756: printf("\nCombination (%d) projection ignored because no cases \n",k);
8757: continue;
8758: }
8759: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8760: for(j=1;j<=cptcoveff;j++) {
8761: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8762: }
1.235 brouard 8763: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8764: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8765: }
1.227 brouard 8766: fprintf(ficresf," yearproj age");
8767: for(j=1; j<=nlstate+ndeath;j++){
8768: for(i=1; i<=nlstate;i++)
8769: fprintf(ficresf," p%d%d",i,j);
8770: fprintf(ficresf," wp.%d",j);
8771: }
1.296 brouard 8772: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 8773: fprintf(ficresf,"\n");
1.296 brouard 8774: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 8775: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8776: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8777: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8778: nhstepm = nhstepm/hstepm;
8779: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8780: oldm=oldms;savm=savms;
1.268 brouard 8781: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8782: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8783: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8784: for (h=0; h<=nhstepm; h++){
8785: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8786: break;
8787: }
8788: }
8789: fprintf(ficresf,"\n");
8790: for(j=1;j<=cptcoveff;j++)
8791: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 8792: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 8793:
8794: for(j=1; j<=nlstate+ndeath;j++) {
8795: ppij=0.;
8796: for(i=1; i<=nlstate;i++) {
1.278 brouard 8797: if (mobilav>=1)
8798: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8799: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8800: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8801: }
1.268 brouard 8802: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8803: } /* end i */
8804: fprintf(ficresf," %.3f", ppij);
8805: }/* end j */
1.227 brouard 8806: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8807: } /* end agec */
1.266 brouard 8808: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8809: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8810: } /* end yearp */
8811: } /* end k */
1.219 brouard 8812:
1.126 brouard 8813: fclose(ficresf);
1.215 brouard 8814: printf("End of Computing forecasting \n");
8815: fprintf(ficlog,"End of Computing forecasting\n");
8816:
1.126 brouard 8817: }
8818:
1.269 brouard 8819: /************** Back Forecasting ******************/
1.296 brouard 8820: /* 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){ */
8821: 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){
8822: /* back1, year, month, day of starting backprojection
1.267 brouard 8823: agemin, agemax range of age
8824: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8825: anback2 year of end of backprojection (same day and month as back1).
8826: prevacurrent and prev are prevalences.
1.267 brouard 8827: */
8828: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8829: double agec; /* generic age */
1.302 brouard 8830: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 8831: double *popeffectif,*popcount;
8832: double ***p3mat;
8833: /* double ***mobaverage; */
8834: char fileresfb[FILENAMELENGTH];
8835:
1.268 brouard 8836: agelim=AGEINF;
1.267 brouard 8837: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8838: in each health status at the date of interview (if between dateprev1 and dateprev2).
8839: We still use firstpass and lastpass as another selection.
8840: */
8841: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8842: /* firstpass, lastpass, stepm, weightopt, model); */
8843:
8844: /*Do we need to compute prevalence again?*/
8845:
8846: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8847:
8848: strcpy(fileresfb,"FB_");
8849: strcat(fileresfb,fileresu);
8850: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8851: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8852: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8853: }
8854: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8855: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8856:
8857: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8858:
8859:
8860: stepsize=(int) (stepm+YEARM-1)/YEARM;
8861: if (stepm<=12) stepsize=1;
8862: if(estepm < stepm){
8863: printf ("Problem %d lower than %d\n",estepm, stepm);
8864: }
1.270 brouard 8865: else{
8866: hstepm=estepm;
8867: }
8868: if(estepm >= stepm){ /* Yes every two year */
8869: stepsize=2;
8870: }
1.267 brouard 8871:
8872: hstepm=hstepm/stepm;
1.296 brouard 8873: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8874: /* fractional in yp1 *\/ */
8875: /* aintmean=yp; */
8876: /* yp2=modf((yp1*12),&yp); */
8877: /* mintmean=yp; */
8878: /* yp1=modf((yp2*30.5),&yp); */
8879: /* jintmean=yp; */
8880: /* if(jintmean==0) jintmean=1; */
8881: /* if(mintmean==0) jintmean=1; */
1.267 brouard 8882:
8883: i1=pow(2,cptcoveff);
8884: if (cptcovn < 1){i1=1;}
8885:
1.296 brouard 8886: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
8887: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8888:
8889: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8890:
8891: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8892: for(k=1; k<=i1;k++){
8893: if(i1 != 1 && TKresult[nres]!= k)
8894: continue;
8895: if(invalidvarcomb[k]){
8896: printf("\nCombination (%d) projection ignored because no cases \n",k);
8897: continue;
8898: }
1.268 brouard 8899: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8900: for(j=1;j<=cptcoveff;j++) {
8901: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8902: }
8903: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8904: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8905: }
8906: fprintf(ficresfb," yearbproj age");
8907: for(j=1; j<=nlstate+ndeath;j++){
8908: for(i=1; i<=nlstate;i++)
1.268 brouard 8909: fprintf(ficresfb," b%d%d",i,j);
8910: fprintf(ficresfb," b.%d",j);
1.267 brouard 8911: }
1.296 brouard 8912: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 8913: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8914: fprintf(ficresfb,"\n");
1.296 brouard 8915: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 8916: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8917: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8918: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8919: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8920: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8921: nhstepm = nhstepm/hstepm;
8922: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8923: oldm=oldms;savm=savms;
1.268 brouard 8924: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8925: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8926: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8927: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8928: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8929: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8930: for (h=0; h<=nhstepm; h++){
1.268 brouard 8931: if (h*hstepm/YEARM*stepm ==-yearp) {
8932: break;
8933: }
8934: }
8935: fprintf(ficresfb,"\n");
8936: for(j=1;j<=cptcoveff;j++)
8937: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 8938: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 8939: for(i=1; i<=nlstate+ndeath;i++) {
8940: ppij=0.;ppi=0.;
8941: for(j=1; j<=nlstate;j++) {
8942: /* if (mobilav==1) */
1.269 brouard 8943: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8944: ppi=ppi+prevacurrent[(int)agec][j][k];
8945: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8946: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8947: /* else { */
8948: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8949: /* } */
1.268 brouard 8950: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8951: } /* end j */
8952: if(ppi <0.99){
8953: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8954: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8955: }
8956: fprintf(ficresfb," %.3f", ppij);
8957: }/* end j */
1.267 brouard 8958: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8959: } /* end agec */
8960: } /* end yearp */
8961: } /* end k */
1.217 brouard 8962:
1.267 brouard 8963: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8964:
1.267 brouard 8965: fclose(ficresfb);
8966: printf("End of Computing Back forecasting \n");
8967: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8968:
1.267 brouard 8969: }
1.217 brouard 8970:
1.269 brouard 8971: /* Variance of prevalence limit: varprlim */
8972: 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 8973: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 8974:
8975: char fileresvpl[FILENAMELENGTH];
8976: FILE *ficresvpl;
8977: double **oldm, **savm;
8978: double **varpl; /* Variances of prevalence limits by age */
8979: int i1, k, nres, j ;
8980:
8981: strcpy(fileresvpl,"VPL_");
8982: strcat(fileresvpl,fileresu);
8983: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 8984: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 8985: exit(0);
8986: }
1.288 brouard 8987: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8988: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 8989:
8990: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8991: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8992:
8993: i1=pow(2,cptcoveff);
8994: if (cptcovn < 1){i1=1;}
8995:
8996: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8997: for(k=1; k<=i1;k++){
8998: if(i1 != 1 && TKresult[nres]!= k)
8999: continue;
9000: fprintf(ficresvpl,"\n#****** ");
9001: printf("\n#****** ");
9002: fprintf(ficlog,"\n#****** ");
9003: for(j=1;j<=cptcoveff;j++) {
9004: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9005: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9006: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9007: }
9008: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
9009: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9010: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9011: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9012: }
9013: fprintf(ficresvpl,"******\n");
9014: printf("******\n");
9015: fprintf(ficlog,"******\n");
9016:
9017: varpl=matrix(1,nlstate,(int) bage, (int) fage);
9018: oldm=oldms;savm=savms;
9019: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
9020: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
9021: /*}*/
9022: }
9023:
9024: fclose(ficresvpl);
1.288 brouard 9025: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
9026: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 9027:
9028: }
9029: /* Variance of back prevalence: varbprlim */
9030: 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){
9031: /*------- Variance of back (stable) prevalence------*/
9032:
9033: char fileresvbl[FILENAMELENGTH];
9034: FILE *ficresvbl;
9035:
9036: double **oldm, **savm;
9037: double **varbpl; /* Variances of back prevalence limits by age */
9038: int i1, k, nres, j ;
9039:
9040: strcpy(fileresvbl,"VBL_");
9041: strcat(fileresvbl,fileresu);
9042: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
9043: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
9044: exit(0);
9045: }
9046: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
9047: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
9048:
9049:
9050: i1=pow(2,cptcoveff);
9051: if (cptcovn < 1){i1=1;}
9052:
9053: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9054: for(k=1; k<=i1;k++){
9055: if(i1 != 1 && TKresult[nres]!= k)
9056: continue;
9057: fprintf(ficresvbl,"\n#****** ");
9058: printf("\n#****** ");
9059: fprintf(ficlog,"\n#****** ");
9060: for(j=1;j<=cptcoveff;j++) {
9061: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9062: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9063: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9064: }
9065: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
9066: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9067: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9068: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9069: }
9070: fprintf(ficresvbl,"******\n");
9071: printf("******\n");
9072: fprintf(ficlog,"******\n");
9073:
9074: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
9075: oldm=oldms;savm=savms;
9076:
9077: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
9078: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
9079: /*}*/
9080: }
9081:
9082: fclose(ficresvbl);
9083: printf("done variance-covariance of back prevalence\n");fflush(stdout);
9084: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
9085:
9086: } /* End of varbprlim */
9087:
1.126 brouard 9088: /************** Forecasting *****not tested NB*************/
1.227 brouard 9089: /* 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 9090:
1.227 brouard 9091: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
9092: /* int *popage; */
9093: /* double calagedatem, agelim, kk1, kk2; */
9094: /* double *popeffectif,*popcount; */
9095: /* double ***p3mat,***tabpop,***tabpopprev; */
9096: /* /\* double ***mobaverage; *\/ */
9097: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 9098:
1.227 brouard 9099: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9100: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9101: /* agelim=AGESUP; */
9102: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 9103:
1.227 brouard 9104: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 9105:
9106:
1.227 brouard 9107: /* strcpy(filerespop,"POP_"); */
9108: /* strcat(filerespop,fileresu); */
9109: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
9110: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
9111: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
9112: /* } */
9113: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
9114: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 9115:
1.227 brouard 9116: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 9117:
1.227 brouard 9118: /* /\* if (mobilav!=0) { *\/ */
9119: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
9120: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
9121: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9122: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
9123: /* /\* } *\/ */
9124: /* /\* } *\/ */
1.126 brouard 9125:
1.227 brouard 9126: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
9127: /* if (stepm<=12) stepsize=1; */
1.126 brouard 9128:
1.227 brouard 9129: /* agelim=AGESUP; */
1.126 brouard 9130:
1.227 brouard 9131: /* hstepm=1; */
9132: /* hstepm=hstepm/stepm; */
1.218 brouard 9133:
1.227 brouard 9134: /* if (popforecast==1) { */
9135: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
9136: /* printf("Problem with population file : %s\n",popfile);exit(0); */
9137: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
9138: /* } */
9139: /* popage=ivector(0,AGESUP); */
9140: /* popeffectif=vector(0,AGESUP); */
9141: /* popcount=vector(0,AGESUP); */
1.126 brouard 9142:
1.227 brouard 9143: /* i=1; */
9144: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 9145:
1.227 brouard 9146: /* imx=i; */
9147: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
9148: /* } */
1.218 brouard 9149:
1.227 brouard 9150: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
9151: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
9152: /* k=k+1; */
9153: /* fprintf(ficrespop,"\n#******"); */
9154: /* for(j=1;j<=cptcoveff;j++) { */
9155: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
9156: /* } */
9157: /* fprintf(ficrespop,"******\n"); */
9158: /* fprintf(ficrespop,"# Age"); */
9159: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
9160: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 9161:
1.227 brouard 9162: /* for (cpt=0; cpt<=0;cpt++) { */
9163: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 9164:
1.227 brouard 9165: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9166: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9167: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9168:
1.227 brouard 9169: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9170: /* oldm=oldms;savm=savms; */
9171: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 9172:
1.227 brouard 9173: /* for (h=0; h<=nhstepm; h++){ */
9174: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9175: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9176: /* } */
9177: /* for(j=1; j<=nlstate+ndeath;j++) { */
9178: /* kk1=0.;kk2=0; */
9179: /* for(i=1; i<=nlstate;i++) { */
9180: /* if (mobilav==1) */
9181: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
9182: /* else { */
9183: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
9184: /* } */
9185: /* } */
9186: /* if (h==(int)(calagedatem+12*cpt)){ */
9187: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
9188: /* /\*fprintf(ficrespop," %.3f", kk1); */
9189: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
9190: /* } */
9191: /* } */
9192: /* for(i=1; i<=nlstate;i++){ */
9193: /* kk1=0.; */
9194: /* for(j=1; j<=nlstate;j++){ */
9195: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
9196: /* } */
9197: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
9198: /* } */
1.218 brouard 9199:
1.227 brouard 9200: /* if (h==(int)(calagedatem+12*cpt)) */
9201: /* for(j=1; j<=nlstate;j++) */
9202: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
9203: /* } */
9204: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9205: /* } */
9206: /* } */
1.218 brouard 9207:
1.227 brouard 9208: /* /\******\/ */
1.218 brouard 9209:
1.227 brouard 9210: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
9211: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
9212: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
9213: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
9214: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 9215:
1.227 brouard 9216: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9217: /* oldm=oldms;savm=savms; */
9218: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
9219: /* for (h=0; h<=nhstepm; h++){ */
9220: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
9221: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
9222: /* } */
9223: /* for(j=1; j<=nlstate+ndeath;j++) { */
9224: /* kk1=0.;kk2=0; */
9225: /* for(i=1; i<=nlstate;i++) { */
9226: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
9227: /* } */
9228: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
9229: /* } */
9230: /* } */
9231: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
9232: /* } */
9233: /* } */
9234: /* } */
9235: /* } */
1.218 brouard 9236:
1.227 brouard 9237: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 9238:
1.227 brouard 9239: /* if (popforecast==1) { */
9240: /* free_ivector(popage,0,AGESUP); */
9241: /* free_vector(popeffectif,0,AGESUP); */
9242: /* free_vector(popcount,0,AGESUP); */
9243: /* } */
9244: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9245: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
9246: /* fclose(ficrespop); */
9247: /* } /\* End of popforecast *\/ */
1.218 brouard 9248:
1.126 brouard 9249: int fileappend(FILE *fichier, char *optionfich)
9250: {
9251: if((fichier=fopen(optionfich,"a"))==NULL) {
9252: printf("Problem with file: %s\n", optionfich);
9253: fprintf(ficlog,"Problem with file: %s\n", optionfich);
9254: return (0);
9255: }
9256: fflush(fichier);
9257: return (1);
9258: }
9259:
9260:
9261: /**************** function prwizard **********************/
9262: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
9263: {
9264:
9265: /* Wizard to print covariance matrix template */
9266:
1.164 brouard 9267: char ca[32], cb[32];
9268: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 9269: int numlinepar;
9270:
9271: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9272: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9273: for(i=1; i <=nlstate; i++){
9274: jj=0;
9275: for(j=1; j <=nlstate+ndeath; j++){
9276: if(j==i) continue;
9277: jj++;
9278: /*ca[0]= k+'a'-1;ca[1]='\0';*/
9279: printf("%1d%1d",i,j);
9280: fprintf(ficparo,"%1d%1d",i,j);
9281: for(k=1; k<=ncovmodel;k++){
9282: /* printf(" %lf",param[i][j][k]); */
9283: /* fprintf(ficparo," %lf",param[i][j][k]); */
9284: printf(" 0.");
9285: fprintf(ficparo," 0.");
9286: }
9287: printf("\n");
9288: fprintf(ficparo,"\n");
9289: }
9290: }
9291: printf("# Scales (for hessian or gradient estimation)\n");
9292: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
9293: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
9294: for(i=1; i <=nlstate; i++){
9295: jj=0;
9296: for(j=1; j <=nlstate+ndeath; j++){
9297: if(j==i) continue;
9298: jj++;
9299: fprintf(ficparo,"%1d%1d",i,j);
9300: printf("%1d%1d",i,j);
9301: fflush(stdout);
9302: for(k=1; k<=ncovmodel;k++){
9303: /* printf(" %le",delti3[i][j][k]); */
9304: /* fprintf(ficparo," %le",delti3[i][j][k]); */
9305: printf(" 0.");
9306: fprintf(ficparo," 0.");
9307: }
9308: numlinepar++;
9309: printf("\n");
9310: fprintf(ficparo,"\n");
9311: }
9312: }
9313: printf("# Covariance matrix\n");
9314: /* # 121 Var(a12)\n\ */
9315: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9316: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
9317: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
9318: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
9319: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
9320: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
9321: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9322: fflush(stdout);
9323: fprintf(ficparo,"# Covariance matrix\n");
9324: /* # 121 Var(a12)\n\ */
9325: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9326: /* # ...\n\ */
9327: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9328:
9329: for(itimes=1;itimes<=2;itimes++){
9330: jj=0;
9331: for(i=1; i <=nlstate; i++){
9332: for(j=1; j <=nlstate+ndeath; j++){
9333: if(j==i) continue;
9334: for(k=1; k<=ncovmodel;k++){
9335: jj++;
9336: ca[0]= k+'a'-1;ca[1]='\0';
9337: if(itimes==1){
9338: printf("#%1d%1d%d",i,j,k);
9339: fprintf(ficparo,"#%1d%1d%d",i,j,k);
9340: }else{
9341: printf("%1d%1d%d",i,j,k);
9342: fprintf(ficparo,"%1d%1d%d",i,j,k);
9343: /* printf(" %.5le",matcov[i][j]); */
9344: }
9345: ll=0;
9346: for(li=1;li <=nlstate; li++){
9347: for(lj=1;lj <=nlstate+ndeath; lj++){
9348: if(lj==li) continue;
9349: for(lk=1;lk<=ncovmodel;lk++){
9350: ll++;
9351: if(ll<=jj){
9352: cb[0]= lk +'a'-1;cb[1]='\0';
9353: if(ll<jj){
9354: if(itimes==1){
9355: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9356: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9357: }else{
9358: printf(" 0.");
9359: fprintf(ficparo," 0.");
9360: }
9361: }else{
9362: if(itimes==1){
9363: printf(" Var(%s%1d%1d)",ca,i,j);
9364: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
9365: }else{
9366: printf(" 0.");
9367: fprintf(ficparo," 0.");
9368: }
9369: }
9370: }
9371: } /* end lk */
9372: } /* end lj */
9373: } /* end li */
9374: printf("\n");
9375: fprintf(ficparo,"\n");
9376: numlinepar++;
9377: } /* end k*/
9378: } /*end j */
9379: } /* end i */
9380: } /* end itimes */
9381:
9382: } /* end of prwizard */
9383: /******************* Gompertz Likelihood ******************************/
9384: double gompertz(double x[])
9385: {
1.302 brouard 9386: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 9387: int i,n=0; /* n is the size of the sample */
9388:
1.220 brouard 9389: for (i=1;i<=imx ; i++) {
1.126 brouard 9390: sump=sump+weight[i];
9391: /* sump=sump+1;*/
9392: num=num+1;
9393: }
1.302 brouard 9394: L=0.0;
9395: /* agegomp=AGEGOMP; */
1.126 brouard 9396: /* for (i=0; i<=imx; i++)
9397: 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]);*/
9398:
1.302 brouard 9399: for (i=1;i<=imx ; i++) {
9400: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
9401: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
9402: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
9403: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
9404: * +
9405: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
9406: */
9407: if (wav[i] > 1 || agedc[i] < AGESUP) {
9408: if (cens[i] == 1){
9409: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9410: } else if (cens[i] == 0){
1.126 brouard 9411: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 9412: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
9413: } else
9414: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 9415: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 9416: L=L+A*weight[i];
1.126 brouard 9417: /* 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 9418: }
9419: }
1.126 brouard 9420:
1.302 brouard 9421: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 9422:
9423: return -2*L*num/sump;
9424: }
9425:
1.136 brouard 9426: #ifdef GSL
9427: /******************* Gompertz_f Likelihood ******************************/
9428: double gompertz_f(const gsl_vector *v, void *params)
9429: {
1.302 brouard 9430: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 9431: double *x= (double *) v->data;
9432: int i,n=0; /* n is the size of the sample */
9433:
9434: for (i=0;i<=imx-1 ; i++) {
9435: sump=sump+weight[i];
9436: /* sump=sump+1;*/
9437: num=num+1;
9438: }
9439:
9440:
9441: /* for (i=0; i<=imx; i++)
9442: 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]);*/
9443: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9444: for (i=1;i<=imx ; i++)
9445: {
9446: if (cens[i] == 1 && wav[i]>1)
9447: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9448:
9449: if (cens[i] == 0 && wav[i]>1)
9450: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9451: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9452:
9453: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9454: if (wav[i] > 1 ) { /* ??? */
9455: LL=LL+A*weight[i];
9456: /* 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]);*/
9457: }
9458: }
9459:
9460: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9461: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9462:
9463: return -2*LL*num/sump;
9464: }
9465: #endif
9466:
1.126 brouard 9467: /******************* Printing html file ***********/
1.201 brouard 9468: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9469: int lastpass, int stepm, int weightopt, char model[],\
9470: int imx, double p[],double **matcov,double agemortsup){
9471: int i,k;
9472:
9473: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9474: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9475: for (i=1;i<=2;i++)
9476: 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 9477: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9478: fprintf(fichtm,"</ul>");
9479:
9480: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9481:
9482: 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>");
9483:
9484: for (k=agegomp;k<(agemortsup-2);k++)
9485: 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]);
9486:
9487:
9488: fflush(fichtm);
9489: }
9490:
9491: /******************* Gnuplot file **************/
1.201 brouard 9492: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9493:
9494: char dirfileres[132],optfileres[132];
1.164 brouard 9495:
1.126 brouard 9496: int ng;
9497:
9498:
9499: /*#ifdef windows */
9500: fprintf(ficgp,"cd \"%s\" \n",pathc);
9501: /*#endif */
9502:
9503:
9504: strcpy(dirfileres,optionfilefiname);
9505: strcpy(optfileres,"vpl");
1.199 brouard 9506: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9507: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9508: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9509: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9510: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9511:
9512: }
9513:
1.136 brouard 9514: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9515: {
1.126 brouard 9516:
1.136 brouard 9517: /*-------- data file ----------*/
9518: FILE *fic;
9519: char dummy[]=" ";
1.240 brouard 9520: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9521: int lstra;
1.136 brouard 9522: int linei, month, year,iout;
1.302 brouard 9523: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 9524: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9525: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9526: char *stratrunc;
1.223 brouard 9527:
1.240 brouard 9528: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9529: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9530:
1.240 brouard 9531: for(v=1; v <=ncovcol;v++){
9532: DummyV[v]=0;
9533: FixedV[v]=0;
9534: }
9535: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9536: DummyV[v]=1;
9537: FixedV[v]=0;
9538: }
9539: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9540: DummyV[v]=0;
9541: FixedV[v]=1;
9542: }
9543: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9544: DummyV[v]=1;
9545: FixedV[v]=1;
9546: }
9547: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9548: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9549: 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]);
9550: }
1.126 brouard 9551:
1.136 brouard 9552: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9553: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9554: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9555: }
1.126 brouard 9556:
1.302 brouard 9557: /* Is it a BOM UTF-8 Windows file? */
9558: /* First data line */
9559: linei=0;
9560: while(fgets(line, MAXLINE, fic)) {
9561: noffset=0;
9562: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
9563: {
9564: noffset=noffset+3;
9565: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
9566: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
9567: fflush(ficlog); return 1;
9568: }
9569: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
9570: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
9571: {
9572: noffset=noffset+2;
1.304 brouard 9573: 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);
9574: 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 9575: fflush(ficlog); return 1;
9576: }
9577: else if( line[0] == 0 && line[1] == 0)
9578: {
9579: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
9580: noffset=noffset+4;
1.304 brouard 9581: 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);
9582: 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 9583: fflush(ficlog); return 1;
9584: }
9585: } else{
9586: ;/*printf(" Not a BOM file\n");*/
9587: }
9588: /* If line starts with a # it is a comment */
9589: if (line[noffset] == '#') {
9590: linei=linei+1;
9591: break;
9592: }else{
9593: break;
9594: }
9595: }
9596: fclose(fic);
9597: if((fic=fopen(datafile,"r"))==NULL) {
9598: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9599: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
9600: }
9601: /* Not a Bom file */
9602:
1.136 brouard 9603: i=1;
9604: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9605: linei=linei+1;
9606: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9607: if(line[j] == '\t')
9608: line[j] = ' ';
9609: }
9610: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9611: ;
9612: };
9613: line[j+1]=0; /* Trims blanks at end of line */
9614: if(line[0]=='#'){
9615: fprintf(ficlog,"Comment line\n%s\n",line);
9616: printf("Comment line\n%s\n",line);
9617: continue;
9618: }
9619: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9620: strcpy(line, linetmp);
1.223 brouard 9621:
9622: /* Loops on waves */
9623: for (j=maxwav;j>=1;j--){
9624: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9625: cutv(stra, strb, line, ' ');
9626: if(strb[0]=='.') { /* Missing value */
9627: lval=-1;
9628: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9629: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9630: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9631: 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);
9632: 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);
9633: return 1;
9634: }
9635: }else{
9636: errno=0;
9637: /* what_kind_of_number(strb); */
9638: dval=strtod(strb,&endptr);
9639: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9640: /* if(strb != endptr && *endptr == '\0') */
9641: /* dval=dlval; */
9642: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9643: if( strb[0]=='\0' || (*endptr != '\0')){
9644: 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);
9645: 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);
9646: return 1;
9647: }
9648: cotqvar[j][iv][i]=dval;
9649: cotvar[j][ntv+iv][i]=dval;
9650: }
9651: strcpy(line,stra);
1.223 brouard 9652: }/* end loop ntqv */
1.225 brouard 9653:
1.223 brouard 9654: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9655: cutv(stra, strb, line, ' ');
9656: if(strb[0]=='.') { /* Missing value */
9657: lval=-1;
9658: }else{
9659: errno=0;
9660: lval=strtol(strb,&endptr,10);
9661: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9662: if( strb[0]=='\0' || (*endptr != '\0')){
9663: 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);
9664: 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);
9665: return 1;
9666: }
9667: }
9668: if(lval <-1 || lval >1){
9669: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 9670: 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 9671: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9672: For example, for multinomial values like 1, 2 and 3,\n \
9673: build V1=0 V2=0 for the reference value (1),\n \
9674: V1=1 V2=0 for (2) \n \
1.223 brouard 9675: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9676: output of IMaCh is often meaningless.\n \
1.319 brouard 9677: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 9678: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 9679: 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 9680: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9681: For example, for multinomial values like 1, 2 and 3,\n \
9682: build V1=0 V2=0 for the reference value (1),\n \
9683: V1=1 V2=0 for (2) \n \
1.223 brouard 9684: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9685: output of IMaCh is often meaningless.\n \
1.319 brouard 9686: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 9687: return 1;
9688: }
9689: cotvar[j][iv][i]=(double)(lval);
9690: strcpy(line,stra);
1.223 brouard 9691: }/* end loop ntv */
1.225 brouard 9692:
1.223 brouard 9693: /* Statuses at wave */
1.137 brouard 9694: cutv(stra, strb, line, ' ');
1.223 brouard 9695: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9696: lval=-1;
1.136 brouard 9697: }else{
1.238 brouard 9698: errno=0;
9699: lval=strtol(strb,&endptr,10);
9700: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9701: if( strb[0]=='\0' || (*endptr != '\0')){
9702: 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);
9703: 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);
9704: return 1;
9705: }
1.136 brouard 9706: }
1.225 brouard 9707:
1.136 brouard 9708: s[j][i]=lval;
1.225 brouard 9709:
1.223 brouard 9710: /* Date of Interview */
1.136 brouard 9711: strcpy(line,stra);
9712: cutv(stra, strb,line,' ');
1.169 brouard 9713: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9714: }
1.169 brouard 9715: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9716: month=99;
9717: year=9999;
1.136 brouard 9718: }else{
1.225 brouard 9719: 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);
9720: 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);
9721: return 1;
1.136 brouard 9722: }
9723: anint[j][i]= (double) year;
1.302 brouard 9724: mint[j][i]= (double)month;
9725: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
9726: /* 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]); */
9727: /* 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]); */
9728: /* } */
1.136 brouard 9729: strcpy(line,stra);
1.223 brouard 9730: } /* End loop on waves */
1.225 brouard 9731:
1.223 brouard 9732: /* Date of death */
1.136 brouard 9733: cutv(stra, strb,line,' ');
1.169 brouard 9734: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9735: }
1.169 brouard 9736: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9737: month=99;
9738: year=9999;
9739: }else{
1.141 brouard 9740: 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 9741: 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);
9742: return 1;
1.136 brouard 9743: }
9744: andc[i]=(double) year;
9745: moisdc[i]=(double) month;
9746: strcpy(line,stra);
9747:
1.223 brouard 9748: /* Date of birth */
1.136 brouard 9749: cutv(stra, strb,line,' ');
1.169 brouard 9750: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9751: }
1.169 brouard 9752: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9753: month=99;
9754: year=9999;
9755: }else{
1.141 brouard 9756: 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);
9757: 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 9758: return 1;
1.136 brouard 9759: }
9760: if (year==9999) {
1.141 brouard 9761: 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);
9762: 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 9763: return 1;
9764:
1.136 brouard 9765: }
9766: annais[i]=(double)(year);
1.302 brouard 9767: moisnais[i]=(double)(month);
9768: for (j=1;j<=maxwav;j++){
9769: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
9770: 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]);
9771: 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]);
9772: }
9773: }
9774:
1.136 brouard 9775: strcpy(line,stra);
1.225 brouard 9776:
1.223 brouard 9777: /* Sample weight */
1.136 brouard 9778: cutv(stra, strb,line,' ');
9779: errno=0;
9780: dval=strtod(strb,&endptr);
9781: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9782: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9783: 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 9784: fflush(ficlog);
9785: return 1;
9786: }
9787: weight[i]=dval;
9788: strcpy(line,stra);
1.225 brouard 9789:
1.223 brouard 9790: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9791: cutv(stra, strb, line, ' ');
9792: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9793: lval=-1;
1.311 brouard 9794: coqvar[iv][i]=NAN;
9795: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 9796: }else{
1.225 brouard 9797: errno=0;
9798: /* what_kind_of_number(strb); */
9799: dval=strtod(strb,&endptr);
9800: /* if(strb != endptr && *endptr == '\0') */
9801: /* dval=dlval; */
9802: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9803: if( strb[0]=='\0' || (*endptr != '\0')){
9804: 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);
9805: 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);
9806: return 1;
9807: }
9808: coqvar[iv][i]=dval;
1.226 brouard 9809: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9810: }
9811: strcpy(line,stra);
9812: }/* end loop nqv */
1.136 brouard 9813:
1.223 brouard 9814: /* Covariate values */
1.136 brouard 9815: for (j=ncovcol;j>=1;j--){
9816: cutv(stra, strb,line,' ');
1.223 brouard 9817: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9818: lval=-1;
1.136 brouard 9819: }else{
1.225 brouard 9820: errno=0;
9821: lval=strtol(strb,&endptr,10);
9822: if( strb[0]=='\0' || (*endptr != '\0')){
9823: 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);
9824: 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);
9825: return 1;
9826: }
1.136 brouard 9827: }
9828: if(lval <-1 || lval >1){
1.225 brouard 9829: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9830: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9831: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9832: For example, for multinomial values like 1, 2 and 3,\n \
9833: build V1=0 V2=0 for the reference value (1),\n \
9834: V1=1 V2=0 for (2) \n \
1.136 brouard 9835: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9836: output of IMaCh is often meaningless.\n \
1.136 brouard 9837: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9838: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9839: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9840: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9841: For example, for multinomial values like 1, 2 and 3,\n \
9842: build V1=0 V2=0 for the reference value (1),\n \
9843: V1=1 V2=0 for (2) \n \
1.136 brouard 9844: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9845: output of IMaCh is often meaningless.\n \
1.136 brouard 9846: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9847: return 1;
1.136 brouard 9848: }
9849: covar[j][i]=(double)(lval);
9850: strcpy(line,stra);
9851: }
9852: lstra=strlen(stra);
1.225 brouard 9853:
1.136 brouard 9854: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9855: stratrunc = &(stra[lstra-9]);
9856: num[i]=atol(stratrunc);
9857: }
9858: else
9859: num[i]=atol(stra);
9860: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9861: 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;}*/
9862:
9863: i=i+1;
9864: } /* End loop reading data */
1.225 brouard 9865:
1.136 brouard 9866: *imax=i-1; /* Number of individuals */
9867: fclose(fic);
1.225 brouard 9868:
1.136 brouard 9869: return (0);
1.164 brouard 9870: /* endread: */
1.225 brouard 9871: printf("Exiting readdata: ");
9872: fclose(fic);
9873: return (1);
1.223 brouard 9874: }
1.126 brouard 9875:
1.234 brouard 9876: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9877: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9878: while (*p2 == ' ')
1.234 brouard 9879: p2++;
9880: /* while ((*p1++ = *p2++) !=0) */
9881: /* ; */
9882: /* do */
9883: /* while (*p2 == ' ') */
9884: /* p2++; */
9885: /* while (*p1++ == *p2++); */
9886: *stri=p2;
1.145 brouard 9887: }
9888:
1.235 brouard 9889: int decoderesult ( char resultline[], int nres)
1.230 brouard 9890: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9891: {
1.235 brouard 9892: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9893: char resultsav[MAXLINE];
1.234 brouard 9894: int resultmodel[MAXLINE];
9895: int modelresult[MAXLINE];
1.230 brouard 9896: char stra[80], strb[80], strc[80], strd[80],stre[80];
9897:
1.234 brouard 9898: removefirstspace(&resultline);
1.230 brouard 9899:
9900: if (strstr(resultline,"v") !=0){
9901: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9902: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9903: return 1;
9904: }
9905: trimbb(resultsav, resultline);
9906: if (strlen(resultsav) >1){
9907: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9908: }
1.253 brouard 9909: if(j == 0){ /* Resultline but no = */
9910: TKresult[nres]=0; /* Combination for the nresult and the model */
9911: return (0);
9912: }
1.234 brouard 9913: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.318 brouard 9914: 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 9915: 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 9916: }
9917: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9918: if(nbocc(resultsav,'=') >1){
1.318 brouard 9919: 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" */
9920: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.234 brouard 9921: }else
9922: cutl(strc,strd,resultsav,'=');
1.318 brouard 9923: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 9924:
1.230 brouard 9925: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 9926: 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 9927: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9928: /* cptcovsel++; */
9929: if (nbocc(stra,'=') >0)
9930: strcpy(resultsav,stra); /* and analyzes it */
9931: }
1.235 brouard 9932: /* Checking for missing or useless values in comparison of current model needs */
1.318 brouard 9933: for(k1=1; k1<= cptcovt ;k1++){ /* Loop on model. model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9934: 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 9935: match=0;
1.318 brouard 9936: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9937: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9938: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 9939: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 9940: break;
9941: }
9942: }
9943: if(match == 0){
1.310 brouard 9944: printf("Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model);
9945: fprintf(ficlog,"Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model);
9946: return 1;
1.234 brouard 9947: }
9948: }
9949: }
1.235 brouard 9950: /* Checking for missing or useless values in comparison of current model needs */
1.318 brouard 9951: 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 9952: match=0;
1.318 brouard 9953: 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 9954: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9955: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.318 brouard 9956: resultmodel[k1]=k2; /* k2th variable of the model corresponds to k1 variable of the model. resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9957: ++match;
9958: }
9959: }
9960: }
9961: if(match == 0){
9962: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
1.310 brouard 9963: fprintf(ficlog,"Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9964: return 1;
1.234 brouard 9965: }else if(match > 1){
9966: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
1.310 brouard 9967: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9968: return 1;
1.234 brouard 9969: }
9970: }
1.235 brouard 9971:
1.234 brouard 9972: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9973: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9974: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9975: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9976: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9977: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9978: /* 1 0 0 0 */
9979: /* 2 1 0 0 */
9980: /* 3 0 1 0 */
9981: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9982: /* 5 0 0 1 */
9983: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9984: /* 7 0 1 1 */
9985: /* 8 1 1 1 */
1.237 brouard 9986: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9987: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9988: /* V5*age V5 known which value for nres? */
9989: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.318 brouard 9990: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* loop on model line */
1.235 brouard 9991: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9992: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9993: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9994: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9995: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9996: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9997: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9998: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9999: k4++;;
10000: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
1.318 brouard 10001: k3q= resultmodel[k1]; /* resultmodel[1(V5)] = 25.1=k3q */
10002: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.237 brouard 10003: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
10004: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
10005: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 10006: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
10007: k4q++;;
10008: }
10009: }
1.234 brouard 10010:
1.235 brouard 10011: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 10012: return (0);
10013: }
1.235 brouard 10014:
1.230 brouard 10015: int decodemodel( char model[], int lastobs)
10016: /**< This routine decodes the model and returns:
1.224 brouard 10017: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
10018: * - nagesqr = 1 if age*age in the model, otherwise 0.
10019: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
10020: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
10021: * - cptcovage number of covariates with age*products =2
10022: * - cptcovs number of simple covariates
10023: * - 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
10024: * which is a new column after the 9 (ncovcol) variables.
1.319 brouard 10025: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 10026: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
10027: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
10028: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
10029: */
1.319 brouard 10030: /* 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 10031: {
1.238 brouard 10032: int i, j, k, ks, v;
1.227 brouard 10033: int j1, k1, k2, k3, k4;
1.136 brouard 10034: char modelsav[80];
1.145 brouard 10035: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 10036: char *strpt;
1.136 brouard 10037:
1.145 brouard 10038: /*removespace(model);*/
1.136 brouard 10039: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 10040: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 10041: if (strstr(model,"AGE") !=0){
1.192 brouard 10042: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
10043: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 10044: return 1;
10045: }
1.141 brouard 10046: if (strstr(model,"v") !=0){
10047: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
10048: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
10049: return 1;
10050: }
1.187 brouard 10051: strcpy(modelsav,model);
10052: if ((strpt=strstr(model,"age*age")) !=0){
10053: printf(" strpt=%s, model=%s\n",strpt, model);
10054: if(strpt != model){
1.234 brouard 10055: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10056: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10057: corresponding column of parameters.\n",model);
1.234 brouard 10058: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 10059: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 10060: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 10061: return 1;
1.225 brouard 10062: }
1.187 brouard 10063: nagesqr=1;
10064: if (strstr(model,"+age*age") !=0)
1.234 brouard 10065: substrchaine(modelsav, model, "+age*age");
1.187 brouard 10066: else if (strstr(model,"age*age+") !=0)
1.234 brouard 10067: substrchaine(modelsav, model, "age*age+");
1.187 brouard 10068: else
1.234 brouard 10069: substrchaine(modelsav, model, "age*age");
1.187 brouard 10070: }else
10071: nagesqr=0;
10072: if (strlen(modelsav) >1){
10073: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
10074: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 10075: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 10076: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 10077: * cst, age and age*age
10078: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
10079: /* including age products which are counted in cptcovage.
10080: * but the covariates which are products must be treated
10081: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 10082: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
10083: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 10084:
10085:
1.187 brouard 10086: /* Design
10087: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
10088: * < ncovcol=8 >
10089: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
10090: * k= 1 2 3 4 5 6 7 8
10091: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
10092: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 10093: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
10094: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 10095: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
10096: * Tage[++cptcovage]=k
10097: * if products, new covar are created after ncovcol with k1
10098: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
10099: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
10100: * 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
10101: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
10102: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
10103: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
10104: * < ncovcol=8 >
10105: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
10106: * k= 1 2 3 4 5 6 7 8 9 10 11 12
10107: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
1.319 brouard 10108: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
1.187 brouard 10109: * p Tprod[1]@2={ 6, 5}
10110: *p Tvard[1][1]@4= {7, 8, 5, 6}
10111: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
10112: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 10113: *How to reorganize? Tvars(orted)
1.187 brouard 10114: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
10115: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
10116: * {2, 1, 4, 8, 5, 6, 3, 7}
10117: * Struct []
10118: */
1.225 brouard 10119:
1.187 brouard 10120: /* This loop fills the array Tvar from the string 'model'.*/
10121: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
10122: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
10123: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
10124: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
10125: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
10126: /* k=1 Tvar[1]=2 (from V2) */
10127: /* k=5 Tvar[5] */
10128: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 10129: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 10130: /* } */
1.198 brouard 10131: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 10132: /*
10133: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 10134: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
10135: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
10136: }
1.187 brouard 10137: cptcovage=0;
1.319 brouard 10138: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
10139: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
10140: 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" */
10141: if (nbocc(modelsav,'+')==0)
10142: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 10143: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
10144: /*scanf("%d",i);*/
1.319 brouard 10145: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age */
10146: 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 10147: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
10148: /* covar is not filled and then is empty */
10149: cptcovprod--;
10150: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
1.319 brouard 10151: 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 10152: Typevar[k]=1; /* 1 for age product */
1.319 brouard 10153: cptcovage++; /* Counts the number of covariates which include age as a product */
10154: 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 10155: /*printf("stre=%s ", stre);*/
10156: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
10157: cptcovprod--;
10158: cutl(stre,strb,strc,'V');
10159: Tvar[k]=atoi(stre);
10160: Typevar[k]=1; /* 1 for age product */
10161: cptcovage++;
10162: Tage[cptcovage]=k;
10163: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
10164: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
10165: cptcovn++;
10166: cptcovprodnoage++;k1++;
10167: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
10168: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
10169: because this model-covariate is a construction we invent a new column
10170: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
1.319 brouard 10171: If already ncovcol=4 and model=V2 + V1 +V1*V4 +age*V3 +V3*V2
10172: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
10173: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=4 etc */
1.234 brouard 10174: Typevar[k]=2; /* 2 for double fixed dummy covariates */
10175: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
10176: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
1.319 brouard 10177: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
1.234 brouard 10178: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
10179: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
10180: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
10181: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
10182: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 10183: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 10184: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
10185: for (i=1; i<=lastobs;i++){
10186: /* Computes the new covariate which is a product of
10187: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
10188: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
10189: }
10190: } /* End age is not in the model */
10191: } /* End if model includes a product */
1.319 brouard 10192: else { /* not a product */
1.234 brouard 10193: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
10194: /* scanf("%d",i);*/
10195: cutl(strd,strc,strb,'V');
10196: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
10197: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
10198: Tvar[k]=atoi(strd);
10199: Typevar[k]=0; /* 0 for simple covariates */
10200: }
10201: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 10202: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 10203: scanf("%d",i);*/
1.187 brouard 10204: } /* end of loop + on total covariates */
10205: } /* end if strlen(modelsave == 0) age*age might exist */
10206: } /* end if strlen(model == 0) */
1.136 brouard 10207:
10208: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
10209: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 10210:
1.136 brouard 10211: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 10212: printf("cptcovprod=%d ", cptcovprod);
10213: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
10214: scanf("%d ",i);*/
10215:
10216:
1.230 brouard 10217: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
10218: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 10219: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
10220: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
10221: k = 1 2 3 4 5 6 7 8 9
10222: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 10223: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 10224: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
10225: Dummy[k] 1 0 0 0 3 1 1 2 3
10226: Tmodelind[combination of covar]=k;
1.225 brouard 10227: */
10228: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 10229: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 10230: /* 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 10231: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 10232: printf("Model=1+age+%s\n\
1.227 brouard 10233: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10234: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10235: 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 10236: fprintf(ficlog,"Model=1+age+%s\n\
1.227 brouard 10237: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
10238: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
10239: 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 10240: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 10241: 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 */
10242: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 10243: Fixed[k]= 0;
10244: Dummy[k]= 0;
1.225 brouard 10245: ncoveff++;
1.232 brouard 10246: ncovf++;
1.234 brouard 10247: nsd++;
10248: modell[k].maintype= FTYPE;
10249: TvarsD[nsd]=Tvar[k];
10250: TvarsDind[nsd]=k;
10251: TvarF[ncovf]=Tvar[k];
10252: TvarFind[ncovf]=k;
10253: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10254: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10255: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
10256: Fixed[k]= 0;
10257: Dummy[k]= 0;
10258: ncoveff++;
10259: ncovf++;
10260: modell[k].maintype= FTYPE;
10261: TvarF[ncovf]=Tvar[k];
10262: TvarFind[ncovf]=k;
1.230 brouard 10263: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 10264: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 10265: }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 10266: Fixed[k]= 0;
10267: Dummy[k]= 1;
1.230 brouard 10268: nqfveff++;
1.234 brouard 10269: modell[k].maintype= FTYPE;
10270: modell[k].subtype= FQ;
10271: nsq++;
10272: TvarsQ[nsq]=Tvar[k];
10273: TvarsQind[nsq]=k;
1.232 brouard 10274: ncovf++;
1.234 brouard 10275: TvarF[ncovf]=Tvar[k];
10276: TvarFind[ncovf]=k;
1.231 brouard 10277: 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 10278: 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 10279: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 10280: Fixed[k]= 1;
10281: Dummy[k]= 0;
1.225 brouard 10282: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 10283: modell[k].maintype= VTYPE;
10284: modell[k].subtype= VD;
10285: nsd++;
10286: TvarsD[nsd]=Tvar[k];
10287: TvarsDind[nsd]=k;
10288: ncovv++; /* Only simple time varying variables */
10289: TvarV[ncovv]=Tvar[k];
1.242 brouard 10290: 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 10291: 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 */
10292: 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 10293: 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);
10294: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 10295: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 10296: Fixed[k]= 1;
10297: Dummy[k]= 1;
10298: nqtveff++;
10299: modell[k].maintype= VTYPE;
10300: modell[k].subtype= VQ;
10301: ncovv++; /* Only simple time varying variables */
10302: nsq++;
1.319 brouard 10303: TvarsQ[nsq]=Tvar[k]; /* k=1 Tvar=5 nsq=1 TvarsQ[1]=5 */
1.234 brouard 10304: TvarsQind[nsq]=k;
10305: TvarV[ncovv]=Tvar[k];
1.242 brouard 10306: 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 10307: 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 */
10308: 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 10309: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
10310: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
10311: 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 10312: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 10313: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 10314: ncova++;
10315: TvarA[ncova]=Tvar[k];
10316: TvarAind[ncova]=k;
1.231 brouard 10317: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 10318: Fixed[k]= 2;
10319: Dummy[k]= 2;
10320: modell[k].maintype= ATYPE;
10321: modell[k].subtype= APFD;
10322: /* ncoveff++; */
1.227 brouard 10323: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 10324: Fixed[k]= 2;
10325: Dummy[k]= 3;
10326: modell[k].maintype= ATYPE;
10327: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
10328: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 10329: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 10330: Fixed[k]= 3;
10331: Dummy[k]= 2;
10332: modell[k].maintype= ATYPE;
10333: modell[k].subtype= APVD; /* Product age * varying dummy */
10334: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 10335: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10336: Fixed[k]= 3;
10337: Dummy[k]= 3;
10338: modell[k].maintype= ATYPE;
10339: modell[k].subtype= APVQ; /* Product age * varying quantitative */
10340: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 10341: }
10342: }else if (Typevar[k] == 2) { /* product without age */
10343: k1=Tposprod[k];
10344: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 10345: if(Tvard[k1][2] <=ncovcol){
10346: Fixed[k]= 1;
10347: Dummy[k]= 0;
10348: modell[k].maintype= FTYPE;
10349: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
10350: ncovf++; /* Fixed variables without age */
10351: TvarF[ncovf]=Tvar[k];
10352: TvarFind[ncovf]=k;
10353: }else if(Tvard[k1][2] <=ncovcol+nqv){
10354: Fixed[k]= 0; /* or 2 ?*/
10355: Dummy[k]= 1;
10356: modell[k].maintype= FTYPE;
10357: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
10358: ncovf++; /* Varying variables without age */
10359: TvarF[ncovf]=Tvar[k];
10360: TvarFind[ncovf]=k;
10361: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10362: Fixed[k]= 1;
10363: Dummy[k]= 0;
10364: modell[k].maintype= VTYPE;
10365: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
10366: ncovv++; /* Varying variables without age */
10367: TvarV[ncovv]=Tvar[k];
10368: TvarVind[ncovv]=k;
10369: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10370: Fixed[k]= 1;
10371: Dummy[k]= 1;
10372: modell[k].maintype= VTYPE;
10373: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
10374: ncovv++; /* Varying variables without age */
10375: TvarV[ncovv]=Tvar[k];
10376: TvarVind[ncovv]=k;
10377: }
1.227 brouard 10378: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 10379: if(Tvard[k1][2] <=ncovcol){
10380: Fixed[k]= 0; /* or 2 ?*/
10381: Dummy[k]= 1;
10382: modell[k].maintype= FTYPE;
10383: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
10384: ncovf++; /* Fixed variables without age */
10385: TvarF[ncovf]=Tvar[k];
10386: TvarFind[ncovf]=k;
10387: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10388: Fixed[k]= 1;
10389: Dummy[k]= 1;
10390: modell[k].maintype= VTYPE;
10391: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
10392: ncovv++; /* Varying variables without age */
10393: TvarV[ncovv]=Tvar[k];
10394: TvarVind[ncovv]=k;
10395: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10396: Fixed[k]= 1;
10397: Dummy[k]= 1;
10398: modell[k].maintype= VTYPE;
10399: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
10400: ncovv++; /* Varying variables without age */
10401: TvarV[ncovv]=Tvar[k];
10402: TvarVind[ncovv]=k;
10403: ncovv++; /* Varying variables without age */
10404: TvarV[ncovv]=Tvar[k];
10405: TvarVind[ncovv]=k;
10406: }
1.227 brouard 10407: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 10408: if(Tvard[k1][2] <=ncovcol){
10409: Fixed[k]= 1;
10410: Dummy[k]= 1;
10411: modell[k].maintype= VTYPE;
10412: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
10413: ncovv++; /* Varying variables without age */
10414: TvarV[ncovv]=Tvar[k];
10415: TvarVind[ncovv]=k;
10416: }else if(Tvard[k1][2] <=ncovcol+nqv){
10417: Fixed[k]= 1;
10418: Dummy[k]= 1;
10419: modell[k].maintype= VTYPE;
10420: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
10421: ncovv++; /* Varying variables without age */
10422: TvarV[ncovv]=Tvar[k];
10423: TvarVind[ncovv]=k;
10424: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10425: Fixed[k]= 1;
10426: Dummy[k]= 0;
10427: modell[k].maintype= VTYPE;
10428: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
10429: ncovv++; /* Varying variables without age */
10430: TvarV[ncovv]=Tvar[k];
10431: TvarVind[ncovv]=k;
10432: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10433: Fixed[k]= 1;
10434: Dummy[k]= 1;
10435: modell[k].maintype= VTYPE;
10436: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
10437: ncovv++; /* Varying variables without age */
10438: TvarV[ncovv]=Tvar[k];
10439: TvarVind[ncovv]=k;
10440: }
1.227 brouard 10441: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10442: if(Tvard[k1][2] <=ncovcol){
10443: Fixed[k]= 1;
10444: Dummy[k]= 1;
10445: modell[k].maintype= VTYPE;
10446: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
10447: ncovv++; /* Varying variables without age */
10448: TvarV[ncovv]=Tvar[k];
10449: TvarVind[ncovv]=k;
10450: }else if(Tvard[k1][2] <=ncovcol+nqv){
10451: Fixed[k]= 1;
10452: Dummy[k]= 1;
10453: modell[k].maintype= VTYPE;
10454: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
10455: ncovv++; /* Varying variables without age */
10456: TvarV[ncovv]=Tvar[k];
10457: TvarVind[ncovv]=k;
10458: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10459: Fixed[k]= 1;
10460: Dummy[k]= 1;
10461: modell[k].maintype= VTYPE;
10462: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
10463: ncovv++; /* Varying variables without age */
10464: TvarV[ncovv]=Tvar[k];
10465: TvarVind[ncovv]=k;
10466: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10467: Fixed[k]= 1;
10468: Dummy[k]= 1;
10469: modell[k].maintype= VTYPE;
10470: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
10471: ncovv++; /* Varying variables without age */
10472: TvarV[ncovv]=Tvar[k];
10473: TvarVind[ncovv]=k;
10474: }
1.227 brouard 10475: }else{
1.240 brouard 10476: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10477: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10478: } /*end k1*/
1.225 brouard 10479: }else{
1.226 brouard 10480: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10481: 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 10482: }
1.227 brouard 10483: 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 10484: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10485: 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]);
10486: }
10487: /* Searching for doublons in the model */
10488: for(k1=1; k1<= cptcovt;k1++){
10489: for(k2=1; k2 <k1;k2++){
1.285 brouard 10490: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10491: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10492: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10493: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10494: 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]);
10495: 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 10496: return(1);
10497: }
10498: }else if (Typevar[k1] ==2){
10499: k3=Tposprod[k1];
10500: k4=Tposprod[k2];
10501: 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])) ){
10502: 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]]);
10503: 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);
10504: return(1);
10505: }
10506: }
1.227 brouard 10507: }
10508: }
1.225 brouard 10509: }
10510: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10511: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10512: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10513: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10514: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10515: /*endread:*/
1.225 brouard 10516: printf("Exiting decodemodel: ");
10517: return (1);
1.136 brouard 10518: }
10519:
1.169 brouard 10520: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10521: {/* Check ages at death */
1.136 brouard 10522: int i, m;
1.218 brouard 10523: int firstone=0;
10524:
1.136 brouard 10525: for (i=1; i<=imx; i++) {
10526: for(m=2; (m<= maxwav); m++) {
10527: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10528: anint[m][i]=9999;
1.216 brouard 10529: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10530: s[m][i]=-1;
1.136 brouard 10531: }
10532: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10533: *nberr = *nberr + 1;
1.218 brouard 10534: if(firstone == 0){
10535: firstone=1;
1.260 brouard 10536: 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 10537: }
1.262 brouard 10538: 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 10539: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10540: }
10541: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10542: (*nberr)++;
1.259 brouard 10543: 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 10544: 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 10545: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10546: }
10547: }
10548: }
10549:
10550: for (i=1; i<=imx; i++) {
10551: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10552: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10553: 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 10554: if (s[m][i] >= nlstate+1) {
1.169 brouard 10555: if(agedc[i]>0){
10556: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10557: agev[m][i]=agedc[i];
1.214 brouard 10558: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10559: }else {
1.136 brouard 10560: if ((int)andc[i]!=9999){
10561: nbwarn++;
10562: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10563: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10564: agev[m][i]=-1;
10565: }
10566: }
1.169 brouard 10567: } /* agedc > 0 */
1.214 brouard 10568: } /* end if */
1.136 brouard 10569: else if(s[m][i] !=9){ /* Standard case, age in fractional
10570: years but with the precision of a month */
10571: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10572: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10573: agev[m][i]=1;
10574: else if(agev[m][i] < *agemin){
10575: *agemin=agev[m][i];
10576: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10577: }
10578: else if(agev[m][i] >*agemax){
10579: *agemax=agev[m][i];
1.156 brouard 10580: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10581: }
10582: /*agev[m][i]=anint[m][i]-annais[i];*/
10583: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10584: } /* en if 9*/
1.136 brouard 10585: else { /* =9 */
1.214 brouard 10586: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10587: agev[m][i]=1;
10588: s[m][i]=-1;
10589: }
10590: }
1.214 brouard 10591: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10592: agev[m][i]=1;
1.214 brouard 10593: else{
10594: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10595: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10596: agev[m][i]=0;
10597: }
10598: } /* End for lastpass */
10599: }
1.136 brouard 10600:
10601: for (i=1; i<=imx; i++) {
10602: for(m=firstpass; (m<=lastpass); m++){
10603: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10604: (*nberr)++;
1.136 brouard 10605: 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);
10606: 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);
10607: return 1;
10608: }
10609: }
10610: }
10611:
10612: /*for (i=1; i<=imx; i++){
10613: for (m=firstpass; (m<lastpass); m++){
10614: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10615: }
10616:
10617: }*/
10618:
10619:
1.139 brouard 10620: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10621: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10622:
10623: return (0);
1.164 brouard 10624: /* endread:*/
1.136 brouard 10625: printf("Exiting calandcheckages: ");
10626: return (1);
10627: }
10628:
1.172 brouard 10629: #if defined(_MSC_VER)
10630: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10631: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10632: //#include "stdafx.h"
10633: //#include <stdio.h>
10634: //#include <tchar.h>
10635: //#include <windows.h>
10636: //#include <iostream>
10637: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10638:
10639: LPFN_ISWOW64PROCESS fnIsWow64Process;
10640:
10641: BOOL IsWow64()
10642: {
10643: BOOL bIsWow64 = FALSE;
10644:
10645: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10646: // (HANDLE, PBOOL);
10647:
10648: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10649:
10650: HMODULE module = GetModuleHandle(_T("kernel32"));
10651: const char funcName[] = "IsWow64Process";
10652: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10653: GetProcAddress(module, funcName);
10654:
10655: if (NULL != fnIsWow64Process)
10656: {
10657: if (!fnIsWow64Process(GetCurrentProcess(),
10658: &bIsWow64))
10659: //throw std::exception("Unknown error");
10660: printf("Unknown error\n");
10661: }
10662: return bIsWow64 != FALSE;
10663: }
10664: #endif
1.177 brouard 10665:
1.191 brouard 10666: void syscompilerinfo(int logged)
1.292 brouard 10667: {
10668: #include <stdint.h>
10669:
10670: /* #include "syscompilerinfo.h"*/
1.185 brouard 10671: /* command line Intel compiler 32bit windows, XP compatible:*/
10672: /* /GS /W3 /Gy
10673: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10674: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10675: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10676: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10677: */
10678: /* 64 bits */
1.185 brouard 10679: /*
10680: /GS /W3 /Gy
10681: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10682: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10683: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10684: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10685: /* Optimization are useless and O3 is slower than O2 */
10686: /*
10687: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10688: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10689: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10690: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10691: */
1.186 brouard 10692: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10693: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10694: /PDB:"visual studio
10695: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10696: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10697: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10698: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10699: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10700: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10701: uiAccess='false'"
10702: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10703: /NOLOGO /TLBID:1
10704: */
1.292 brouard 10705:
10706:
1.177 brouard 10707: #if defined __INTEL_COMPILER
1.178 brouard 10708: #if defined(__GNUC__)
10709: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10710: #endif
1.177 brouard 10711: #elif defined(__GNUC__)
1.179 brouard 10712: #ifndef __APPLE__
1.174 brouard 10713: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10714: #endif
1.177 brouard 10715: struct utsname sysInfo;
1.178 brouard 10716: int cross = CROSS;
10717: if (cross){
10718: printf("Cross-");
1.191 brouard 10719: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10720: }
1.174 brouard 10721: #endif
10722:
1.191 brouard 10723: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10724: #if defined(__clang__)
1.191 brouard 10725: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10726: #endif
10727: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10728: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10729: #endif
10730: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10731: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10732: #endif
10733: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10734: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10735: #endif
10736: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10737: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10738: #endif
10739: #if defined(_MSC_VER)
1.191 brouard 10740: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10741: #endif
10742: #if defined(__PGI)
1.191 brouard 10743: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10744: #endif
10745: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10746: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10747: #endif
1.191 brouard 10748: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10749:
1.167 brouard 10750: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10751: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10752: // Windows (x64 and x86)
1.191 brouard 10753: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10754: #elif __unix__ // all unices, not all compilers
10755: // Unix
1.191 brouard 10756: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10757: #elif __linux__
10758: // linux
1.191 brouard 10759: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10760: #elif __APPLE__
1.174 brouard 10761: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10762: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10763: #endif
10764:
10765: /* __MINGW32__ */
10766: /* __CYGWIN__ */
10767: /* __MINGW64__ */
10768: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10769: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10770: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10771: /* _WIN64 // Defined for applications for Win64. */
10772: /* _M_X64 // Defined for compilations that target x64 processors. */
10773: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10774:
1.167 brouard 10775: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10776: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10777: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10778: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10779: #else
1.191 brouard 10780: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10781: #endif
10782:
1.169 brouard 10783: #if defined(__GNUC__)
10784: # if defined(__GNUC_PATCHLEVEL__)
10785: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10786: + __GNUC_MINOR__ * 100 \
10787: + __GNUC_PATCHLEVEL__)
10788: # else
10789: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10790: + __GNUC_MINOR__ * 100)
10791: # endif
1.174 brouard 10792: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10793: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10794:
10795: if (uname(&sysInfo) != -1) {
10796: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10797: 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 10798: }
10799: else
10800: perror("uname() error");
1.179 brouard 10801: //#ifndef __INTEL_COMPILER
10802: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10803: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10804: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10805: #endif
1.169 brouard 10806: #endif
1.172 brouard 10807:
1.286 brouard 10808: // void main ()
1.172 brouard 10809: // {
1.169 brouard 10810: #if defined(_MSC_VER)
1.174 brouard 10811: if (IsWow64()){
1.191 brouard 10812: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10813: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10814: }
10815: else{
1.191 brouard 10816: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10817: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10818: }
1.172 brouard 10819: // printf("\nPress Enter to continue...");
10820: // getchar();
10821: // }
10822:
1.169 brouard 10823: #endif
10824:
1.167 brouard 10825:
1.219 brouard 10826: }
1.136 brouard 10827:
1.219 brouard 10828: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 10829: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.235 brouard 10830: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10831: /* double ftolpl = 1.e-10; */
1.180 brouard 10832: double age, agebase, agelim;
1.203 brouard 10833: double tot;
1.180 brouard 10834:
1.202 brouard 10835: strcpy(filerespl,"PL_");
10836: strcat(filerespl,fileresu);
10837: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 10838: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10839: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 10840: }
1.288 brouard 10841: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
10842: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10843: pstamp(ficrespl);
1.288 brouard 10844: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10845: fprintf(ficrespl,"#Age ");
10846: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10847: fprintf(ficrespl,"\n");
1.180 brouard 10848:
1.219 brouard 10849: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10850:
1.219 brouard 10851: agebase=ageminpar;
10852: agelim=agemaxpar;
1.180 brouard 10853:
1.227 brouard 10854: /* i1=pow(2,ncoveff); */
1.234 brouard 10855: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10856: if (cptcovn < 1){i1=1;}
1.180 brouard 10857:
1.238 brouard 10858: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10859: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10860: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10861: continue;
1.235 brouard 10862:
1.238 brouard 10863: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10864: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10865: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10866: /* k=k+1; */
10867: /* to clean */
10868: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10869: fprintf(ficrespl,"#******");
10870: printf("#******");
10871: fprintf(ficlog,"#******");
10872: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10873: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10874: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10875: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10876: }
10877: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10878: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10879: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10880: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10881: }
10882: fprintf(ficrespl,"******\n");
10883: printf("******\n");
10884: fprintf(ficlog,"******\n");
10885: if(invalidvarcomb[k]){
10886: printf("\nCombination (%d) ignored because no case \n",k);
10887: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10888: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10889: continue;
10890: }
1.219 brouard 10891:
1.238 brouard 10892: fprintf(ficrespl,"#Age ");
10893: for(j=1;j<=cptcoveff;j++) {
10894: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10895: }
10896: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10897: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10898:
1.238 brouard 10899: for (age=agebase; age<=agelim; age++){
10900: /* for (age=agebase; age<=agebase; age++){ */
10901: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10902: fprintf(ficrespl,"%.0f ",age );
10903: for(j=1;j<=cptcoveff;j++)
10904: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10905: tot=0.;
10906: for(i=1; i<=nlstate;i++){
10907: tot += prlim[i][i];
10908: fprintf(ficrespl," %.5f", prlim[i][i]);
10909: }
10910: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10911: } /* Age */
10912: /* was end of cptcod */
10913: } /* cptcov */
10914: } /* nres */
1.219 brouard 10915: return 0;
1.180 brouard 10916: }
10917:
1.218 brouard 10918: 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 10919: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 10920:
10921: /* Computes the back prevalence limit for any combination of covariate values
10922: * at any age between ageminpar and agemaxpar
10923: */
1.235 brouard 10924: int i, j, k, i1, nres=0 ;
1.217 brouard 10925: /* double ftolpl = 1.e-10; */
10926: double age, agebase, agelim;
10927: double tot;
1.218 brouard 10928: /* double ***mobaverage; */
10929: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10930:
10931: strcpy(fileresplb,"PLB_");
10932: strcat(fileresplb,fileresu);
10933: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 10934: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
10935: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 10936: }
1.288 brouard 10937: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
10938: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 10939: pstamp(ficresplb);
1.288 brouard 10940: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 10941: fprintf(ficresplb,"#Age ");
10942: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10943: fprintf(ficresplb,"\n");
10944:
1.218 brouard 10945:
10946: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10947:
10948: agebase=ageminpar;
10949: agelim=agemaxpar;
10950:
10951:
1.227 brouard 10952: i1=pow(2,cptcoveff);
1.218 brouard 10953: if (cptcovn < 1){i1=1;}
1.227 brouard 10954:
1.238 brouard 10955: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10956: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10957: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10958: continue;
10959: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10960: fprintf(ficresplb,"#******");
10961: printf("#******");
10962: fprintf(ficlog,"#******");
10963: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10964: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10965: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10966: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10967: }
10968: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10969: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10970: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10971: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10972: }
10973: fprintf(ficresplb,"******\n");
10974: printf("******\n");
10975: fprintf(ficlog,"******\n");
10976: if(invalidvarcomb[k]){
10977: printf("\nCombination (%d) ignored because no cases \n",k);
10978: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10979: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10980: continue;
10981: }
1.218 brouard 10982:
1.238 brouard 10983: fprintf(ficresplb,"#Age ");
10984: for(j=1;j<=cptcoveff;j++) {
10985: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10986: }
10987: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10988: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10989:
10990:
1.238 brouard 10991: for (age=agebase; age<=agelim; age++){
10992: /* for (age=agebase; age<=agebase; age++){ */
10993: if(mobilavproj > 0){
10994: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10995: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10996: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10997: }else if (mobilavproj == 0){
10998: 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);
10999: 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);
11000: exit(1);
11001: }else{
11002: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 11003: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 11004: /* printf("TOTOT\n"); */
11005: /* exit(1); */
1.238 brouard 11006: }
11007: fprintf(ficresplb,"%.0f ",age );
11008: for(j=1;j<=cptcoveff;j++)
11009: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11010: tot=0.;
11011: for(i=1; i<=nlstate;i++){
11012: tot += bprlim[i][i];
11013: fprintf(ficresplb," %.5f", bprlim[i][i]);
11014: }
11015: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
11016: } /* Age */
11017: /* was end of cptcod */
1.255 brouard 11018: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 11019: } /* end of any combination */
11020: } /* end of nres */
1.218 brouard 11021: /* hBijx(p, bage, fage); */
11022: /* fclose(ficrespijb); */
11023:
11024: return 0;
1.217 brouard 11025: }
1.218 brouard 11026:
1.180 brouard 11027: int hPijx(double *p, int bage, int fage){
11028: /*------------- h Pij x at various ages ------------*/
11029:
11030: int stepsize;
11031: int agelim;
11032: int hstepm;
11033: int nhstepm;
1.235 brouard 11034: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 11035:
11036: double agedeb;
11037: double ***p3mat;
11038:
1.201 brouard 11039: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 11040: if((ficrespij=fopen(filerespij,"w"))==NULL) {
11041: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
11042: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
11043: }
11044: printf("Computing pij: result on file '%s' \n", filerespij);
11045: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
11046:
11047: stepsize=(int) (stepm+YEARM-1)/YEARM;
11048: /*if (stepm<=24) stepsize=2;*/
11049:
11050: agelim=AGESUP;
11051: hstepm=stepsize*YEARM; /* Every year of age */
11052: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 11053:
1.180 brouard 11054: /* hstepm=1; aff par mois*/
11055: pstamp(ficrespij);
11056: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 11057: i1= pow(2,cptcoveff);
1.218 brouard 11058: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11059: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11060: /* k=k+1; */
1.235 brouard 11061: for(nres=1; nres <= nresult; nres++) /* For each resultline */
11062: for(k=1; k<=i1;k++){
1.253 brouard 11063: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 11064: continue;
1.183 brouard 11065: fprintf(ficrespij,"\n#****** ");
1.227 brouard 11066: for(j=1;j<=cptcoveff;j++)
1.198 brouard 11067: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 11068: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
11069: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11070: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
11071: }
1.183 brouard 11072: fprintf(ficrespij,"******\n");
11073:
11074: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
11075: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
11076: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
11077:
11078: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 11079:
1.183 brouard 11080: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11081: oldm=oldms;savm=savms;
1.235 brouard 11082: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 11083: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
11084: for(i=1; i<=nlstate;i++)
11085: for(j=1; j<=nlstate+ndeath;j++)
11086: fprintf(ficrespij," %1d-%1d",i,j);
11087: fprintf(ficrespij,"\n");
11088: for (h=0; h<=nhstepm; h++){
11089: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11090: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 11091: for(i=1; i<=nlstate;i++)
11092: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 11093: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 11094: fprintf(ficrespij,"\n");
11095: }
1.183 brouard 11096: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11097: fprintf(ficrespij,"\n");
11098: }
1.180 brouard 11099: /*}*/
11100: }
1.218 brouard 11101: return 0;
1.180 brouard 11102: }
1.218 brouard 11103:
11104: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 11105: /*------------- h Bij x at various ages ------------*/
11106:
11107: int stepsize;
1.218 brouard 11108: /* int agelim; */
11109: int ageminl;
1.217 brouard 11110: int hstepm;
11111: int nhstepm;
1.238 brouard 11112: int h, i, i1, j, k, nres;
1.218 brouard 11113:
1.217 brouard 11114: double agedeb;
11115: double ***p3mat;
1.218 brouard 11116:
11117: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
11118: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
11119: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11120: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
11121: }
11122: printf("Computing pij back: result on file '%s' \n", filerespijb);
11123: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
11124:
11125: stepsize=(int) (stepm+YEARM-1)/YEARM;
11126: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 11127:
1.218 brouard 11128: /* agelim=AGESUP; */
1.289 brouard 11129: ageminl=AGEINF; /* was 30 */
1.218 brouard 11130: hstepm=stepsize*YEARM; /* Every year of age */
11131: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
11132:
11133: /* hstepm=1; aff par mois*/
11134: pstamp(ficrespijb);
1.255 brouard 11135: 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 11136: i1= pow(2,cptcoveff);
1.218 brouard 11137: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
11138: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
11139: /* k=k+1; */
1.238 brouard 11140: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
11141: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 11142: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 11143: continue;
11144: fprintf(ficrespijb,"\n#****** ");
11145: for(j=1;j<=cptcoveff;j++)
11146: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11147: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11148: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11149: }
11150: fprintf(ficrespijb,"******\n");
1.264 brouard 11151: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 11152: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
11153: continue;
11154: }
11155:
11156: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
11157: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
11158: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
1.297 brouard 11159: 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 */
11160: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
1.238 brouard 11161:
11162: /* nhstepm=nhstepm*YEARM; aff par mois*/
11163:
1.266 brouard 11164: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
11165: /* and memory limitations if stepm is small */
11166:
1.238 brouard 11167: /* oldm=oldms;savm=savms; */
11168: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 11169: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 11170: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 11171: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 11172: for(i=1; i<=nlstate;i++)
11173: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 11174: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 11175: fprintf(ficrespijb,"\n");
1.238 brouard 11176: for (h=0; h<=nhstepm; h++){
11177: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
11178: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
11179: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
11180: for(i=1; i<=nlstate;i++)
11181: for(j=1; j<=nlstate+ndeath;j++)
11182: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
11183: fprintf(ficrespijb,"\n");
11184: }
11185: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
11186: fprintf(ficrespijb,"\n");
11187: } /* end age deb */
11188: } /* end combination */
11189: } /* end nres */
1.218 brouard 11190: return 0;
11191: } /* hBijx */
1.217 brouard 11192:
1.180 brouard 11193:
1.136 brouard 11194: /***********************************************/
11195: /**************** Main Program *****************/
11196: /***********************************************/
11197:
11198: int main(int argc, char *argv[])
11199: {
11200: #ifdef GSL
11201: const gsl_multimin_fminimizer_type *T;
11202: size_t iteri = 0, it;
11203: int rval = GSL_CONTINUE;
11204: int status = GSL_SUCCESS;
11205: double ssval;
11206: #endif
11207: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 11208: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
11209: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 11210: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 11211: int jj, ll, li, lj, lk;
1.136 brouard 11212: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 11213: int num_filled;
1.136 brouard 11214: int itimes;
11215: int NDIM=2;
11216: int vpopbased=0;
1.235 brouard 11217: int nres=0;
1.258 brouard 11218: int endishere=0;
1.277 brouard 11219: int noffset=0;
1.274 brouard 11220: int ncurrv=0; /* Temporary variable */
11221:
1.164 brouard 11222: char ca[32], cb[32];
1.136 brouard 11223: /* FILE *fichtm; *//* Html File */
11224: /* FILE *ficgp;*/ /*Gnuplot File */
11225: struct stat info;
1.191 brouard 11226: double agedeb=0.;
1.194 brouard 11227:
11228: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 11229: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 11230:
1.165 brouard 11231: double fret;
1.191 brouard 11232: double dum=0.; /* Dummy variable */
1.136 brouard 11233: double ***p3mat;
1.218 brouard 11234: /* double ***mobaverage; */
1.319 brouard 11235: double wald;
1.164 brouard 11236:
11237: char line[MAXLINE];
1.197 brouard 11238: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
11239:
1.234 brouard 11240: char modeltemp[MAXLINE];
1.230 brouard 11241: char resultline[MAXLINE];
11242:
1.136 brouard 11243: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 11244: char *tok, *val; /* pathtot */
1.290 brouard 11245: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs declared globally ;*/
1.195 brouard 11246: int c, h , cpt, c2;
1.191 brouard 11247: int jl=0;
11248: int i1, j1, jk, stepsize=0;
1.194 brouard 11249: int count=0;
11250:
1.164 brouard 11251: int *tab;
1.136 brouard 11252: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 11253: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
11254: /* double anprojf, mprojf, jprojf; */
11255: /* double jintmean,mintmean,aintmean; */
11256: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11257: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11258: double yrfproj= 10.0; /* Number of years of forward projections */
11259: double yrbproj= 10.0; /* Number of years of backward projections */
11260: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 11261: int mobilav=0,popforecast=0;
1.191 brouard 11262: int hstepm=0, nhstepm=0;
1.136 brouard 11263: int agemortsup;
11264: float sumlpop=0.;
11265: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
11266: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
11267:
1.191 brouard 11268: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 11269: double ftolpl=FTOL;
11270: double **prlim;
1.217 brouard 11271: double **bprlim;
1.317 brouard 11272: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
11273: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 11274: double ***paramstart; /* Matrix of starting parameter values */
11275: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 11276: double **matcov; /* Matrix of covariance */
1.203 brouard 11277: double **hess; /* Hessian matrix */
1.136 brouard 11278: double ***delti3; /* Scale */
11279: double *delti; /* Scale */
11280: double ***eij, ***vareij;
11281: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 11282:
1.136 brouard 11283: double *epj, vepp;
1.164 brouard 11284:
1.273 brouard 11285: double dateprev1, dateprev2;
1.296 brouard 11286: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
11287: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
11288:
1.217 brouard 11289:
1.136 brouard 11290: double **ximort;
1.145 brouard 11291: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 11292: int *dcwave;
11293:
1.164 brouard 11294: char z[1]="c";
1.136 brouard 11295:
11296: /*char *strt;*/
11297: char strtend[80];
1.126 brouard 11298:
1.164 brouard 11299:
1.126 brouard 11300: /* setlocale (LC_ALL, ""); */
11301: /* bindtextdomain (PACKAGE, LOCALEDIR); */
11302: /* textdomain (PACKAGE); */
11303: /* setlocale (LC_CTYPE, ""); */
11304: /* setlocale (LC_MESSAGES, ""); */
11305:
11306: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 11307: rstart_time = time(NULL);
11308: /* (void) gettimeofday(&start_time,&tzp);*/
11309: start_time = *localtime(&rstart_time);
1.126 brouard 11310: curr_time=start_time;
1.157 brouard 11311: /*tml = *localtime(&start_time.tm_sec);*/
11312: /* strcpy(strstart,asctime(&tml)); */
11313: strcpy(strstart,asctime(&start_time));
1.126 brouard 11314:
11315: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 11316: /* tp.tm_sec = tp.tm_sec +86400; */
11317: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 11318: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
11319: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
11320: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 11321: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 11322: /* strt=asctime(&tmg); */
11323: /* printf("Time(after) =%s",strstart); */
11324: /* (void) time (&time_value);
11325: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
11326: * tm = *localtime(&time_value);
11327: * strstart=asctime(&tm);
11328: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
11329: */
11330:
11331: nberr=0; /* Number of errors and warnings */
11332: nbwarn=0;
1.184 brouard 11333: #ifdef WIN32
11334: _getcwd(pathcd, size);
11335: #else
1.126 brouard 11336: getcwd(pathcd, size);
1.184 brouard 11337: #endif
1.191 brouard 11338: syscompilerinfo(0);
1.196 brouard 11339: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 11340: if(argc <=1){
11341: printf("\nEnter the parameter file name: ");
1.205 brouard 11342: if(!fgets(pathr,FILENAMELENGTH,stdin)){
11343: printf("ERROR Empty parameter file name\n");
11344: goto end;
11345: }
1.126 brouard 11346: i=strlen(pathr);
11347: if(pathr[i-1]=='\n')
11348: pathr[i-1]='\0';
1.156 brouard 11349: i=strlen(pathr);
1.205 brouard 11350: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 11351: pathr[i-1]='\0';
1.205 brouard 11352: }
11353: i=strlen(pathr);
11354: if( i==0 ){
11355: printf("ERROR Empty parameter file name\n");
11356: goto end;
11357: }
11358: for (tok = pathr; tok != NULL; ){
1.126 brouard 11359: printf("Pathr |%s|\n",pathr);
11360: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
11361: printf("val= |%s| pathr=%s\n",val,pathr);
11362: strcpy (pathtot, val);
11363: if(pathr[0] == '\0') break; /* Dirty */
11364: }
11365: }
1.281 brouard 11366: else if (argc<=2){
11367: strcpy(pathtot,argv[1]);
11368: }
1.126 brouard 11369: else{
11370: strcpy(pathtot,argv[1]);
1.281 brouard 11371: strcpy(z,argv[2]);
11372: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 11373: }
11374: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
11375: /*cygwin_split_path(pathtot,path,optionfile);
11376: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
11377: /* cutv(path,optionfile,pathtot,'\\');*/
11378:
11379: /* Split argv[0], imach program to get pathimach */
11380: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
11381: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11382: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11383: /* strcpy(pathimach,argv[0]); */
11384: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
11385: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
11386: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 11387: #ifdef WIN32
11388: _chdir(path); /* Can be a relative path */
11389: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
11390: #else
1.126 brouard 11391: chdir(path); /* Can be a relative path */
1.184 brouard 11392: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
11393: #endif
11394: printf("Current directory %s!\n",pathcd);
1.126 brouard 11395: strcpy(command,"mkdir ");
11396: strcat(command,optionfilefiname);
11397: if((outcmd=system(command)) != 0){
1.169 brouard 11398: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 11399: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
11400: /* fclose(ficlog); */
11401: /* exit(1); */
11402: }
11403: /* if((imk=mkdir(optionfilefiname))<0){ */
11404: /* perror("mkdir"); */
11405: /* } */
11406:
11407: /*-------- arguments in the command line --------*/
11408:
1.186 brouard 11409: /* Main Log file */
1.126 brouard 11410: strcat(filelog, optionfilefiname);
11411: strcat(filelog,".log"); /* */
11412: if((ficlog=fopen(filelog,"w"))==NULL) {
11413: printf("Problem with logfile %s\n",filelog);
11414: goto end;
11415: }
11416: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 11417: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 11418: fprintf(ficlog,"\nEnter the parameter file name: \n");
11419: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
11420: path=%s \n\
11421: optionfile=%s\n\
11422: optionfilext=%s\n\
1.156 brouard 11423: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 11424:
1.197 brouard 11425: syscompilerinfo(1);
1.167 brouard 11426:
1.126 brouard 11427: printf("Local time (at start):%s",strstart);
11428: fprintf(ficlog,"Local time (at start): %s",strstart);
11429: fflush(ficlog);
11430: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 11431: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 11432:
11433: /* */
11434: strcpy(fileres,"r");
11435: strcat(fileres, optionfilefiname);
1.201 brouard 11436: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 11437: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 11438: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 11439:
1.186 brouard 11440: /* Main ---------arguments file --------*/
1.126 brouard 11441:
11442: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 11443: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
11444: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 11445: fflush(ficlog);
1.149 brouard 11446: /* goto end; */
11447: exit(70);
1.126 brouard 11448: }
11449:
11450: strcpy(filereso,"o");
1.201 brouard 11451: strcat(filereso,fileresu);
1.126 brouard 11452: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
11453: printf("Problem with Output resultfile: %s\n", filereso);
11454: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
11455: fflush(ficlog);
11456: goto end;
11457: }
1.278 brouard 11458: /*-------- Rewriting parameter file ----------*/
11459: strcpy(rfileres,"r"); /* "Rparameterfile */
11460: strcat(rfileres,optionfilefiname); /* Parameter file first name */
11461: strcat(rfileres,"."); /* */
11462: strcat(rfileres,optionfilext); /* Other files have txt extension */
11463: if((ficres =fopen(rfileres,"w"))==NULL) {
11464: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
11465: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
11466: fflush(ficlog);
11467: goto end;
11468: }
11469: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 11470:
1.278 brouard 11471:
1.126 brouard 11472: /* Reads comments: lines beginning with '#' */
11473: numlinepar=0;
1.277 brouard 11474: /* Is it a BOM UTF-8 Windows file? */
11475: /* First parameter line */
1.197 brouard 11476: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 11477: noffset=0;
11478: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
11479: {
11480: noffset=noffset+3;
11481: printf("# File is an UTF8 Bom.\n"); // 0xBF
11482: }
1.302 brouard 11483: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
11484: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 11485: {
11486: noffset=noffset+2;
11487: printf("# File is an UTF16BE BOM file\n");
11488: }
11489: else if( line[0] == 0 && line[1] == 0)
11490: {
11491: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
11492: noffset=noffset+4;
11493: printf("# File is an UTF16BE BOM file\n");
11494: }
11495: } else{
11496: ;/*printf(" Not a BOM file\n");*/
11497: }
11498:
1.197 brouard 11499: /* If line starts with a # it is a comment */
1.277 brouard 11500: if (line[noffset] == '#') {
1.197 brouard 11501: numlinepar++;
11502: fputs(line,stdout);
11503: fputs(line,ficparo);
1.278 brouard 11504: fputs(line,ficres);
1.197 brouard 11505: fputs(line,ficlog);
11506: continue;
11507: }else
11508: break;
11509: }
11510: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11511: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11512: if (num_filled != 5) {
11513: printf("Should be 5 parameters\n");
1.283 brouard 11514: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11515: }
1.126 brouard 11516: numlinepar++;
1.197 brouard 11517: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11518: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11519: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11520: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11521: }
11522: /* Second parameter line */
11523: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11524: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11525: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11526: if (line[0] == '#') {
11527: numlinepar++;
1.283 brouard 11528: printf("%s",line);
11529: fprintf(ficres,"%s",line);
11530: fprintf(ficparo,"%s",line);
11531: fprintf(ficlog,"%s",line);
1.197 brouard 11532: continue;
11533: }else
11534: break;
11535: }
1.223 brouard 11536: 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", \
11537: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11538: if (num_filled != 11) {
11539: 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 11540: printf("but line=%s\n",line);
1.283 brouard 11541: 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");
11542: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11543: }
1.286 brouard 11544: if( lastpass > maxwav){
11545: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11546: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11547: fflush(ficlog);
11548: goto end;
11549: }
11550: 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 11551: 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 11552: 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 11553: 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 11554: }
1.203 brouard 11555: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11556: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11557: /* Third parameter line */
11558: while(fgets(line, MAXLINE, ficpar)) {
11559: /* If line starts with a # it is a comment */
11560: if (line[0] == '#') {
11561: numlinepar++;
1.283 brouard 11562: printf("%s",line);
11563: fprintf(ficres,"%s",line);
11564: fprintf(ficparo,"%s",line);
11565: fprintf(ficlog,"%s",line);
1.197 brouard 11566: continue;
11567: }else
11568: break;
11569: }
1.201 brouard 11570: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11571: if (num_filled != 1){
1.302 brouard 11572: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
11573: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 11574: model[0]='\0';
11575: goto end;
11576: }
11577: else{
11578: if (model[0]=='+'){
11579: for(i=1; i<=strlen(model);i++)
11580: modeltemp[i-1]=model[i];
1.201 brouard 11581: strcpy(model,modeltemp);
1.197 brouard 11582: }
11583: }
1.199 brouard 11584: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11585: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11586: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11587: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11588: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11589: }
11590: /* 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); */
11591: /* numlinepar=numlinepar+3; /\* In general *\/ */
11592: /* 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 11593: /* 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); */
11594: /* 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 11595: fflush(ficlog);
1.190 brouard 11596: /* if(model[0]=='#'|| model[0]== '\0'){ */
11597: if(model[0]=='#'){
1.279 brouard 11598: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11599: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11600: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11601: if(mle != -1){
1.279 brouard 11602: 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 11603: exit(1);
11604: }
11605: }
1.126 brouard 11606: while((c=getc(ficpar))=='#' && c!= EOF){
11607: ungetc(c,ficpar);
11608: fgets(line, MAXLINE, ficpar);
11609: numlinepar++;
1.195 brouard 11610: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11611: z[0]=line[1];
11612: }
11613: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11614: fputs(line, stdout);
11615: //puts(line);
1.126 brouard 11616: fputs(line,ficparo);
11617: fputs(line,ficlog);
11618: }
11619: ungetc(c,ficpar);
11620:
11621:
1.290 brouard 11622: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
11623: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
11624: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
11625: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11626: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11627: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11628: v1+v2*age+v2*v3 makes cptcovn = 3
11629: */
11630: if (strlen(model)>1)
1.187 brouard 11631: 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 11632: else
1.187 brouard 11633: ncovmodel=2; /* Constant and age */
1.133 brouard 11634: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11635: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11636: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11637: 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);
11638: 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);
11639: fflush(stdout);
11640: fclose (ficlog);
11641: goto end;
11642: }
1.126 brouard 11643: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11644: delti=delti3[1][1];
11645: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11646: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11647: /* We could also provide initial parameters values giving by simple logistic regression
11648: * only one way, that is without matrix product. We will have nlstate maximizations */
11649: /* for(i=1;i<nlstate;i++){ */
11650: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11651: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11652: /* } */
1.126 brouard 11653: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11654: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11655: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11656: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11657: fclose (ficparo);
11658: fclose (ficlog);
11659: goto end;
11660: exit(0);
1.220 brouard 11661: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11662: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11663: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11664: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11665: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11666: matcov=matrix(1,npar,1,npar);
1.203 brouard 11667: hess=matrix(1,npar,1,npar);
1.220 brouard 11668: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11669: /* Read guessed parameters */
1.126 brouard 11670: /* Reads comments: lines beginning with '#' */
11671: while((c=getc(ficpar))=='#' && c!= EOF){
11672: ungetc(c,ficpar);
11673: fgets(line, MAXLINE, ficpar);
11674: numlinepar++;
1.141 brouard 11675: fputs(line,stdout);
1.126 brouard 11676: fputs(line,ficparo);
11677: fputs(line,ficlog);
11678: }
11679: ungetc(c,ficpar);
11680:
11681: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11682: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11683: for(i=1; i <=nlstate; i++){
1.234 brouard 11684: j=0;
1.126 brouard 11685: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11686: if(jj==i) continue;
11687: j++;
1.292 brouard 11688: while((c=getc(ficpar))=='#' && c!= EOF){
11689: ungetc(c,ficpar);
11690: fgets(line, MAXLINE, ficpar);
11691: numlinepar++;
11692: fputs(line,stdout);
11693: fputs(line,ficparo);
11694: fputs(line,ficlog);
11695: }
11696: ungetc(c,ficpar);
1.234 brouard 11697: fscanf(ficpar,"%1d%1d",&i1,&j1);
11698: if ((i1 != i) || (j1 != jj)){
11699: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11700: It might be a problem of design; if ncovcol and the model are correct\n \
11701: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11702: exit(1);
11703: }
11704: fprintf(ficparo,"%1d%1d",i1,j1);
11705: if(mle==1)
11706: printf("%1d%1d",i,jj);
11707: fprintf(ficlog,"%1d%1d",i,jj);
11708: for(k=1; k<=ncovmodel;k++){
11709: fscanf(ficpar," %lf",¶m[i][j][k]);
11710: if(mle==1){
11711: printf(" %lf",param[i][j][k]);
11712: fprintf(ficlog," %lf",param[i][j][k]);
11713: }
11714: else
11715: fprintf(ficlog," %lf",param[i][j][k]);
11716: fprintf(ficparo," %lf",param[i][j][k]);
11717: }
11718: fscanf(ficpar,"\n");
11719: numlinepar++;
11720: if(mle==1)
11721: printf("\n");
11722: fprintf(ficlog,"\n");
11723: fprintf(ficparo,"\n");
1.126 brouard 11724: }
11725: }
11726: fflush(ficlog);
1.234 brouard 11727:
1.251 brouard 11728: /* Reads parameters values */
1.126 brouard 11729: p=param[1][1];
1.251 brouard 11730: pstart=paramstart[1][1];
1.126 brouard 11731:
11732: /* Reads comments: lines beginning with '#' */
11733: while((c=getc(ficpar))=='#' && c!= EOF){
11734: ungetc(c,ficpar);
11735: fgets(line, MAXLINE, ficpar);
11736: numlinepar++;
1.141 brouard 11737: fputs(line,stdout);
1.126 brouard 11738: fputs(line,ficparo);
11739: fputs(line,ficlog);
11740: }
11741: ungetc(c,ficpar);
11742:
11743: for(i=1; i <=nlstate; i++){
11744: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11745: fscanf(ficpar,"%1d%1d",&i1,&j1);
11746: if ( (i1-i) * (j1-j) != 0){
11747: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11748: exit(1);
11749: }
11750: printf("%1d%1d",i,j);
11751: fprintf(ficparo,"%1d%1d",i1,j1);
11752: fprintf(ficlog,"%1d%1d",i1,j1);
11753: for(k=1; k<=ncovmodel;k++){
11754: fscanf(ficpar,"%le",&delti3[i][j][k]);
11755: printf(" %le",delti3[i][j][k]);
11756: fprintf(ficparo," %le",delti3[i][j][k]);
11757: fprintf(ficlog," %le",delti3[i][j][k]);
11758: }
11759: fscanf(ficpar,"\n");
11760: numlinepar++;
11761: printf("\n");
11762: fprintf(ficparo,"\n");
11763: fprintf(ficlog,"\n");
1.126 brouard 11764: }
11765: }
11766: fflush(ficlog);
1.234 brouard 11767:
1.145 brouard 11768: /* Reads covariance matrix */
1.126 brouard 11769: delti=delti3[1][1];
1.220 brouard 11770:
11771:
1.126 brouard 11772: /* 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 11773:
1.126 brouard 11774: /* Reads comments: lines beginning with '#' */
11775: while((c=getc(ficpar))=='#' && c!= EOF){
11776: ungetc(c,ficpar);
11777: fgets(line, MAXLINE, ficpar);
11778: numlinepar++;
1.141 brouard 11779: fputs(line,stdout);
1.126 brouard 11780: fputs(line,ficparo);
11781: fputs(line,ficlog);
11782: }
11783: ungetc(c,ficpar);
1.220 brouard 11784:
1.126 brouard 11785: matcov=matrix(1,npar,1,npar);
1.203 brouard 11786: hess=matrix(1,npar,1,npar);
1.131 brouard 11787: for(i=1; i <=npar; i++)
11788: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11789:
1.194 brouard 11790: /* Scans npar lines */
1.126 brouard 11791: for(i=1; i <=npar; i++){
1.226 brouard 11792: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11793: if(count != 3){
1.226 brouard 11794: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11795: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11796: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11797: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11798: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11799: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11800: exit(1);
1.220 brouard 11801: }else{
1.226 brouard 11802: if(mle==1)
11803: printf("%1d%1d%d",i1,j1,jk);
11804: }
11805: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11806: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11807: for(j=1; j <=i; j++){
1.226 brouard 11808: fscanf(ficpar," %le",&matcov[i][j]);
11809: if(mle==1){
11810: printf(" %.5le",matcov[i][j]);
11811: }
11812: fprintf(ficlog," %.5le",matcov[i][j]);
11813: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11814: }
11815: fscanf(ficpar,"\n");
11816: numlinepar++;
11817: if(mle==1)
1.220 brouard 11818: printf("\n");
1.126 brouard 11819: fprintf(ficlog,"\n");
11820: fprintf(ficparo,"\n");
11821: }
1.194 brouard 11822: /* End of read covariance matrix npar lines */
1.126 brouard 11823: for(i=1; i <=npar; i++)
11824: for(j=i+1;j<=npar;j++)
1.226 brouard 11825: matcov[i][j]=matcov[j][i];
1.126 brouard 11826:
11827: if(mle==1)
11828: printf("\n");
11829: fprintf(ficlog,"\n");
11830:
11831: fflush(ficlog);
11832:
11833: } /* End of mle != -3 */
1.218 brouard 11834:
1.186 brouard 11835: /* Main data
11836: */
1.290 brouard 11837: nobs=lastobs-firstobs+1; /* was = lastobs;*/
11838: /* num=lvector(1,n); */
11839: /* moisnais=vector(1,n); */
11840: /* annais=vector(1,n); */
11841: /* moisdc=vector(1,n); */
11842: /* andc=vector(1,n); */
11843: /* weight=vector(1,n); */
11844: /* agedc=vector(1,n); */
11845: /* cod=ivector(1,n); */
11846: /* for(i=1;i<=n;i++){ */
11847: num=lvector(firstobs,lastobs);
11848: moisnais=vector(firstobs,lastobs);
11849: annais=vector(firstobs,lastobs);
11850: moisdc=vector(firstobs,lastobs);
11851: andc=vector(firstobs,lastobs);
11852: weight=vector(firstobs,lastobs);
11853: agedc=vector(firstobs,lastobs);
11854: cod=ivector(firstobs,lastobs);
11855: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 11856: num[i]=0;
11857: moisnais[i]=0;
11858: annais[i]=0;
11859: moisdc[i]=0;
11860: andc[i]=0;
11861: agedc[i]=0;
11862: cod[i]=0;
11863: weight[i]=1.0; /* Equal weights, 1 by default */
11864: }
1.290 brouard 11865: mint=matrix(1,maxwav,firstobs,lastobs);
11866: anint=matrix(1,maxwav,firstobs,lastobs);
11867: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11868: tab=ivector(1,NCOVMAX);
1.144 brouard 11869: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11870: 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 11871:
1.136 brouard 11872: /* Reads data from file datafile */
11873: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11874: goto end;
11875:
11876: /* Calculation of the number of parameters from char model */
1.234 brouard 11877: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11878: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11879: k=3 V4 Tvar[k=3]= 4 (from V4)
11880: k=2 V1 Tvar[k=2]= 1 (from V1)
11881: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11882: */
11883:
11884: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11885: TvarsDind=ivector(1,NCOVMAX); /* */
11886: TvarsD=ivector(1,NCOVMAX); /* */
11887: TvarsQind=ivector(1,NCOVMAX); /* */
11888: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11889: TvarF=ivector(1,NCOVMAX); /* */
11890: TvarFind=ivector(1,NCOVMAX); /* */
11891: TvarV=ivector(1,NCOVMAX); /* */
11892: TvarVind=ivector(1,NCOVMAX); /* */
11893: TvarA=ivector(1,NCOVMAX); /* */
11894: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11895: TvarFD=ivector(1,NCOVMAX); /* */
11896: TvarFDind=ivector(1,NCOVMAX); /* */
11897: TvarFQ=ivector(1,NCOVMAX); /* */
11898: TvarFQind=ivector(1,NCOVMAX); /* */
11899: TvarVD=ivector(1,NCOVMAX); /* */
11900: TvarVDind=ivector(1,NCOVMAX); /* */
11901: TvarVQ=ivector(1,NCOVMAX); /* */
11902: TvarVQind=ivector(1,NCOVMAX); /* */
11903:
1.230 brouard 11904: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11905: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11906: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11907: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11908: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11909: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11910: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11911: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11912: */
11913: /* For model-covariate k tells which data-covariate to use but
11914: because this model-covariate is a construction we invent a new column
11915: ncovcol + k1
11916: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11917: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11918: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11919: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11920: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11921: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11922: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11923: */
1.145 brouard 11924: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11925: 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 11926: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11927: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11928: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11929: 4 covariates (3 plus signs)
11930: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11931: */
1.230 brouard 11932: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11933: * individual dummy, fixed or varying:
11934: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11935: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11936: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11937: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11938: * Tmodelind[1]@9={9,0,3,2,}*/
11939: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11940: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11941: * individual quantitative, fixed or varying:
11942: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11943: * 3, 1, 0, 0, 0, 0, 0, 0},
11944: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11945: /* Main decodemodel */
11946:
1.187 brouard 11947:
1.223 brouard 11948: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11949: goto end;
11950:
1.137 brouard 11951: if((double)(lastobs-imx)/(double)imx > 1.10){
11952: nbwarn++;
11953: 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);
11954: 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);
11955: }
1.136 brouard 11956: /* if(mle==1){*/
1.137 brouard 11957: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11958: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11959: }
11960:
11961: /*-calculation of age at interview from date of interview and age at death -*/
11962: agev=matrix(1,maxwav,1,imx);
11963:
11964: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11965: goto end;
11966:
1.126 brouard 11967:
1.136 brouard 11968: agegomp=(int)agemin;
1.290 brouard 11969: free_vector(moisnais,firstobs,lastobs);
11970: free_vector(annais,firstobs,lastobs);
1.126 brouard 11971: /* free_matrix(mint,1,maxwav,1,n);
11972: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11973: /* free_vector(moisdc,1,n); */
11974: /* free_vector(andc,1,n); */
1.145 brouard 11975: /* */
11976:
1.126 brouard 11977: wav=ivector(1,imx);
1.214 brouard 11978: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11979: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11980: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11981: 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.*/
11982: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11983: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11984:
11985: /* Concatenates waves */
1.214 brouard 11986: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11987: Death is a valid wave (if date is known).
11988: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11989: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11990: and mw[mi+1][i]. dh depends on stepm.
11991: */
11992:
1.126 brouard 11993: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11994: /* Concatenates waves */
1.145 brouard 11995:
1.290 brouard 11996: free_vector(moisdc,firstobs,lastobs);
11997: free_vector(andc,firstobs,lastobs);
1.215 brouard 11998:
1.126 brouard 11999: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
12000: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
12001: ncodemax[1]=1;
1.145 brouard 12002: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 12003: cptcoveff=0;
1.220 brouard 12004: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
12005: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 12006: }
12007:
12008: ncovcombmax=pow(2,cptcoveff);
12009: invalidvarcomb=ivector(1, ncovcombmax);
12010: for(i=1;i<ncovcombmax;i++)
12011: invalidvarcomb[i]=0;
12012:
1.211 brouard 12013: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 12014: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 12015: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 12016:
1.200 brouard 12017: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 12018: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 12019: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 12020: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
12021: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
12022: * (currently 0 or 1) in the data.
12023: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
12024: * corresponding modality (h,j).
12025: */
12026:
1.145 brouard 12027: h=0;
12028: /*if (cptcovn > 0) */
1.126 brouard 12029: m=pow(2,cptcoveff);
12030:
1.144 brouard 12031: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 12032: * For k=4 covariates, h goes from 1 to m=2**k
12033: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
12034: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 12035: * h\k 1 2 3 4
1.143 brouard 12036: *______________________________
12037: * 1 i=1 1 i=1 1 i=1 1 i=1 1
12038: * 2 2 1 1 1
12039: * 3 i=2 1 2 1 1
12040: * 4 2 2 1 1
12041: * 5 i=3 1 i=2 1 2 1
12042: * 6 2 1 2 1
12043: * 7 i=4 1 2 2 1
12044: * 8 2 2 2 1
1.197 brouard 12045: * 9 i=5 1 i=3 1 i=2 1 2
12046: * 10 2 1 1 2
12047: * 11 i=6 1 2 1 2
12048: * 12 2 2 1 2
12049: * 13 i=7 1 i=4 1 2 2
12050: * 14 2 1 2 2
12051: * 15 i=8 1 2 2 2
12052: * 16 2 2 2 2
1.143 brouard 12053: */
1.212 brouard 12054: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 12055: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
12056: * and the value of each covariate?
12057: * V1=1, V2=1, V3=2, V4=1 ?
12058: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
12059: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
12060: * In order to get the real value in the data, we use nbcode
12061: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
12062: * We are keeping this crazy system in order to be able (in the future?)
12063: * to have more than 2 values (0 or 1) for a covariate.
12064: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
12065: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
12066: * bbbbbbbb
12067: * 76543210
12068: * h-1 00000101 (6-1=5)
1.219 brouard 12069: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 12070: * &
12071: * 1 00000001 (1)
1.219 brouard 12072: * 00000000 = 1 & ((h-1) >> (k-1))
12073: * +1= 00000001 =1
1.211 brouard 12074: *
12075: * h=14, k=3 => h'=h-1=13, k'=k-1=2
12076: * h' 1101 =2^3+2^2+0x2^1+2^0
12077: * >>k' 11
12078: * & 00000001
12079: * = 00000001
12080: * +1 = 00000010=2 = codtabm(14,3)
12081: * Reverse h=6 and m=16?
12082: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
12083: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
12084: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
12085: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
12086: * V3=decodtabm(14,3,2**4)=2
12087: * h'=13 1101 =2^3+2^2+0x2^1+2^0
12088: *(h-1) >> (j-1) 0011 =13 >> 2
12089: * &1 000000001
12090: * = 000000001
12091: * +1= 000000010 =2
12092: * 2211
12093: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
12094: * V3=2
1.220 brouard 12095: * codtabm and decodtabm are identical
1.211 brouard 12096: */
12097:
1.145 brouard 12098:
12099: free_ivector(Ndum,-1,NCOVMAX);
12100:
12101:
1.126 brouard 12102:
1.186 brouard 12103: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 12104: strcpy(optionfilegnuplot,optionfilefiname);
12105: if(mle==-3)
1.201 brouard 12106: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 12107: strcat(optionfilegnuplot,".gp");
12108:
12109: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
12110: printf("Problem with file %s",optionfilegnuplot);
12111: }
12112: else{
1.204 brouard 12113: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 12114: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 12115: //fprintf(ficgp,"set missing 'NaNq'\n");
12116: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 12117: }
12118: /* fclose(ficgp);*/
1.186 brouard 12119:
12120:
12121: /* Initialisation of --------- index.htm --------*/
1.126 brouard 12122:
12123: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
12124: if(mle==-3)
1.201 brouard 12125: strcat(optionfilehtm,"-MORT_");
1.126 brouard 12126: strcat(optionfilehtm,".htm");
12127: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 12128: printf("Problem with %s \n",optionfilehtm);
12129: exit(0);
1.126 brouard 12130: }
12131:
12132: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
12133: strcat(optionfilehtmcov,"-cov.htm");
12134: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
12135: printf("Problem with %s \n",optionfilehtmcov), exit(0);
12136: }
12137: else{
12138: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
12139: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12140: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 12141: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
12142: }
12143:
1.213 brouard 12144: 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å¦è¡“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 12145: <hr size=\"2\" color=\"#EC5E5E\"> \n\
12146: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 12147: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 12148: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 12149: \n\
12150: <hr size=\"2\" color=\"#EC5E5E\">\
12151: <ul><li><h4>Parameter files</h4>\n\
12152: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
12153: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
12154: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
12155: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
12156: - Date and time at start: %s</ul>\n",\
12157: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
12158: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
12159: fileres,fileres,\
12160: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
12161: fflush(fichtm);
12162:
12163: strcpy(pathr,path);
12164: strcat(pathr,optionfilefiname);
1.184 brouard 12165: #ifdef WIN32
12166: _chdir(optionfilefiname); /* Move to directory named optionfile */
12167: #else
1.126 brouard 12168: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 12169: #endif
12170:
1.126 brouard 12171:
1.220 brouard 12172: /* Calculates basic frequencies. Computes observed prevalence at single age
12173: and for any valid combination of covariates
1.126 brouard 12174: and prints on file fileres'p'. */
1.251 brouard 12175: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 12176: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 12177:
12178: fprintf(fichtm,"\n");
1.286 brouard 12179: 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 12180: ftol, stepm);
12181: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
12182: ncurrv=1;
12183: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
12184: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
12185: ncurrv=i;
12186: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12187: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 12188: ncurrv=i;
12189: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 12190: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 12191: ncurrv=i;
12192: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
12193: 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", \
12194: nlstate, ndeath, maxwav, mle, weightopt);
12195:
12196: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
12197: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
12198:
12199:
1.317 brouard 12200: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 12201: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
12202: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 12203: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 12204: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 12205: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12206: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12207: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
12208: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 12209:
1.126 brouard 12210: /* For Powell, parameters are in a vector p[] starting at p[1]
12211: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
12212: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
12213:
12214: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 12215: /* For mortality only */
1.126 brouard 12216: if (mle==-3){
1.136 brouard 12217: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 12218: for(i=1;i<=NDIM;i++)
12219: for(j=1;j<=NDIM;j++)
12220: ximort[i][j]=0.;
1.186 brouard 12221: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 12222: cens=ivector(firstobs,lastobs);
12223: ageexmed=vector(firstobs,lastobs);
12224: agecens=vector(firstobs,lastobs);
12225: dcwave=ivector(firstobs,lastobs);
1.223 brouard 12226:
1.126 brouard 12227: for (i=1; i<=imx; i++){
12228: dcwave[i]=-1;
12229: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 12230: if (s[m][i]>nlstate) {
12231: dcwave[i]=m;
12232: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
12233: break;
12234: }
1.126 brouard 12235: }
1.226 brouard 12236:
1.126 brouard 12237: for (i=1; i<=imx; i++) {
12238: if (wav[i]>0){
1.226 brouard 12239: ageexmed[i]=agev[mw[1][i]][i];
12240: j=wav[i];
12241: agecens[i]=1.;
12242:
12243: if (ageexmed[i]> 1 && wav[i] > 0){
12244: agecens[i]=agev[mw[j][i]][i];
12245: cens[i]= 1;
12246: }else if (ageexmed[i]< 1)
12247: cens[i]= -1;
12248: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
12249: cens[i]=0 ;
1.126 brouard 12250: }
12251: else cens[i]=-1;
12252: }
12253:
12254: for (i=1;i<=NDIM;i++) {
12255: for (j=1;j<=NDIM;j++)
1.226 brouard 12256: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 12257: }
12258:
1.302 brouard 12259: p[1]=0.0268; p[NDIM]=0.083;
12260: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 12261:
12262:
1.136 brouard 12263: #ifdef GSL
12264: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 12265: #else
1.126 brouard 12266: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 12267: #endif
1.201 brouard 12268: strcpy(filerespow,"POW-MORT_");
12269: strcat(filerespow,fileresu);
1.126 brouard 12270: if((ficrespow=fopen(filerespow,"w"))==NULL) {
12271: printf("Problem with resultfile: %s\n", filerespow);
12272: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
12273: }
1.136 brouard 12274: #ifdef GSL
12275: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 12276: #else
1.126 brouard 12277: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 12278: #endif
1.126 brouard 12279: /* for (i=1;i<=nlstate;i++)
12280: for(j=1;j<=nlstate+ndeath;j++)
12281: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
12282: */
12283: fprintf(ficrespow,"\n");
1.136 brouard 12284: #ifdef GSL
12285: /* gsl starts here */
12286: T = gsl_multimin_fminimizer_nmsimplex;
12287: gsl_multimin_fminimizer *sfm = NULL;
12288: gsl_vector *ss, *x;
12289: gsl_multimin_function minex_func;
12290:
12291: /* Initial vertex size vector */
12292: ss = gsl_vector_alloc (NDIM);
12293:
12294: if (ss == NULL){
12295: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
12296: }
12297: /* Set all step sizes to 1 */
12298: gsl_vector_set_all (ss, 0.001);
12299:
12300: /* Starting point */
1.126 brouard 12301:
1.136 brouard 12302: x = gsl_vector_alloc (NDIM);
12303:
12304: if (x == NULL){
12305: gsl_vector_free(ss);
12306: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
12307: }
12308:
12309: /* Initialize method and iterate */
12310: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 12311: /* gsl_vector_set(x, 0, 0.0268); */
12312: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 12313: gsl_vector_set(x, 0, p[1]);
12314: gsl_vector_set(x, 1, p[2]);
12315:
12316: minex_func.f = &gompertz_f;
12317: minex_func.n = NDIM;
12318: minex_func.params = (void *)&p; /* ??? */
12319:
12320: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
12321: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
12322:
12323: printf("Iterations beginning .....\n\n");
12324: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
12325:
12326: iteri=0;
12327: while (rval == GSL_CONTINUE){
12328: iteri++;
12329: status = gsl_multimin_fminimizer_iterate(sfm);
12330:
12331: if (status) printf("error: %s\n", gsl_strerror (status));
12332: fflush(0);
12333:
12334: if (status)
12335: break;
12336:
12337: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
12338: ssval = gsl_multimin_fminimizer_size (sfm);
12339:
12340: if (rval == GSL_SUCCESS)
12341: printf ("converged to a local maximum at\n");
12342:
12343: printf("%5d ", iteri);
12344: for (it = 0; it < NDIM; it++){
12345: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
12346: }
12347: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
12348: }
12349:
12350: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
12351:
12352: gsl_vector_free(x); /* initial values */
12353: gsl_vector_free(ss); /* inital step size */
12354: for (it=0; it<NDIM; it++){
12355: p[it+1]=gsl_vector_get(sfm->x,it);
12356: fprintf(ficrespow," %.12lf", p[it]);
12357: }
12358: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
12359: #endif
12360: #ifdef POWELL
12361: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
12362: #endif
1.126 brouard 12363: fclose(ficrespow);
12364:
1.203 brouard 12365: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 12366:
12367: for(i=1; i <=NDIM; i++)
12368: for(j=i+1;j<=NDIM;j++)
1.220 brouard 12369: matcov[i][j]=matcov[j][i];
1.126 brouard 12370:
12371: printf("\nCovariance matrix\n ");
1.203 brouard 12372: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 12373: for(i=1; i <=NDIM; i++) {
12374: for(j=1;j<=NDIM;j++){
1.220 brouard 12375: printf("%f ",matcov[i][j]);
12376: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 12377: }
1.203 brouard 12378: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 12379: }
12380:
12381: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 12382: for (i=1;i<=NDIM;i++) {
1.126 brouard 12383: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 12384: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
12385: }
1.302 brouard 12386: lsurv=vector(agegomp,AGESUP);
12387: lpop=vector(agegomp,AGESUP);
12388: tpop=vector(agegomp,AGESUP);
1.126 brouard 12389: lsurv[agegomp]=100000;
12390:
12391: for (k=agegomp;k<=AGESUP;k++) {
12392: agemortsup=k;
12393: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
12394: }
12395:
12396: for (k=agegomp;k<agemortsup;k++)
12397: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
12398:
12399: for (k=agegomp;k<agemortsup;k++){
12400: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
12401: sumlpop=sumlpop+lpop[k];
12402: }
12403:
12404: tpop[agegomp]=sumlpop;
12405: for (k=agegomp;k<(agemortsup-3);k++){
12406: /* tpop[k+1]=2;*/
12407: tpop[k+1]=tpop[k]-lpop[k];
12408: }
12409:
12410:
12411: printf("\nAge lx qx dx Lx Tx e(x)\n");
12412: for (k=agegomp;k<(agemortsup-2);k++)
12413: 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]);
12414:
12415:
12416: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 12417: ageminpar=50;
12418: agemaxpar=100;
1.194 brouard 12419: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
12420: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12421: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12422: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
12423: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12424: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12425: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12426: }else{
12427: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
12428: 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 12429: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 12430: }
1.201 brouard 12431: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 12432: stepm, weightopt,\
12433: model,imx,p,matcov,agemortsup);
12434:
1.302 brouard 12435: free_vector(lsurv,agegomp,AGESUP);
12436: free_vector(lpop,agegomp,AGESUP);
12437: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 12438: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 12439: free_ivector(dcwave,firstobs,lastobs);
12440: free_vector(agecens,firstobs,lastobs);
12441: free_vector(ageexmed,firstobs,lastobs);
12442: free_ivector(cens,firstobs,lastobs);
1.220 brouard 12443: #ifdef GSL
1.136 brouard 12444: #endif
1.186 brouard 12445: } /* Endof if mle==-3 mortality only */
1.205 brouard 12446: /* Standard */
12447: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
12448: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12449: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 12450: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 12451: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12452: for (k=1; k<=npar;k++)
12453: printf(" %d %8.5f",k,p[k]);
12454: printf("\n");
1.205 brouard 12455: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
12456: /* mlikeli uses func not funcone */
1.247 brouard 12457: /* for(i=1;i<nlstate;i++){ */
12458: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12459: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12460: /* } */
1.205 brouard 12461: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
12462: }
12463: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
12464: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12465: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
12466: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12467: }
12468: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 12469: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12470: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12471: for (k=1; k<=npar;k++)
12472: printf(" %d %8.5f",k,p[k]);
12473: printf("\n");
12474:
12475: /*--------- results files --------------*/
1.283 brouard 12476: /* 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 12477:
12478:
12479: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 12480: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 12481: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 12482:
12483: printf("#model= 1 + age ");
12484: fprintf(ficres,"#model= 1 + age ");
12485: fprintf(ficlog,"#model= 1 + age ");
12486: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
12487: </ul>", model);
12488:
12489: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
12490: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
12491: if(nagesqr==1){
12492: printf(" + age*age ");
12493: fprintf(ficres," + age*age ");
12494: fprintf(ficlog," + age*age ");
12495: fprintf(fichtm, "<th>+ age*age</th>");
12496: }
12497: for(j=1;j <=ncovmodel-2;j++){
12498: if(Typevar[j]==0) {
12499: printf(" + V%d ",Tvar[j]);
12500: fprintf(ficres," + V%d ",Tvar[j]);
12501: fprintf(ficlog," + V%d ",Tvar[j]);
12502: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
12503: }else if(Typevar[j]==1) {
12504: printf(" + V%d*age ",Tvar[j]);
12505: fprintf(ficres," + V%d*age ",Tvar[j]);
12506: fprintf(ficlog," + V%d*age ",Tvar[j]);
12507: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
12508: }else if(Typevar[j]==2) {
12509: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12510: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12511: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12512: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12513: }
12514: }
12515: printf("\n");
12516: fprintf(ficres,"\n");
12517: fprintf(ficlog,"\n");
12518: fprintf(fichtm, "</tr>");
12519: fprintf(fichtm, "\n");
12520:
12521:
1.126 brouard 12522: for(i=1,jk=1; i <=nlstate; i++){
12523: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 12524: if (k != i) {
1.319 brouard 12525: fprintf(fichtm, "<tr>");
1.225 brouard 12526: printf("%d%d ",i,k);
12527: fprintf(ficlog,"%d%d ",i,k);
12528: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 12529: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 12530: for(j=1; j <=ncovmodel; j++){
12531: printf("%12.7f ",p[jk]);
12532: fprintf(ficlog,"%12.7f ",p[jk]);
12533: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 12534: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 12535: jk++;
12536: }
12537: printf("\n");
12538: fprintf(ficlog,"\n");
12539: fprintf(ficres,"\n");
1.319 brouard 12540: fprintf(fichtm, "</tr>\n");
1.225 brouard 12541: }
1.126 brouard 12542: }
12543: }
1.319 brouard 12544: /* fprintf(fichtm,"</tr>\n"); */
12545: fprintf(fichtm,"</table>\n");
12546: fprintf(fichtm, "\n");
12547:
1.203 brouard 12548: if(mle != 0){
12549: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 12550: ftolhess=ftol; /* Usually correct */
1.203 brouard 12551: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
12552: 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");
12553: 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");
1.321 ! brouard 12554: fprintf(fichtm, "\n<p>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 'Matrix of variance-covariance of one-step probabilities' and its graphs.\n</br>");
1.319 brouard 12555: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
12556: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
12557: if(nagesqr==1){
12558: printf(" + age*age ");
12559: fprintf(ficres," + age*age ");
12560: fprintf(ficlog," + age*age ");
12561: fprintf(fichtm, "<th>+ age*age</th>");
12562: }
12563: for(j=1;j <=ncovmodel-2;j++){
12564: if(Typevar[j]==0) {
12565: printf(" + V%d ",Tvar[j]);
12566: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
12567: }else if(Typevar[j]==1) {
12568: printf(" + V%d*age ",Tvar[j]);
12569: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
12570: }else if(Typevar[j]==2) {
12571: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
12572: }
12573: }
12574: fprintf(fichtm, "</tr>\n");
12575:
1.203 brouard 12576: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 12577: for(k=1; k <=(nlstate+ndeath); k++){
12578: if (k != i) {
1.319 brouard 12579: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 12580: printf("%d%d ",i,k);
12581: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 12582: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 12583: for(j=1; j <=ncovmodel; j++){
1.319 brouard 12584: wald=p[jk]/sqrt(matcov[jk][jk]);
1.321 ! brouard 12585: printf("%12.7f(%12.7f) sqrt(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]));
! 12586: fprintf(ficlog,"%12.7f(%12.7f) sqrt(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 12587: if(fabs(wald) > 1.96){
1.321 ! brouard 12588: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 12589: }else{
12590: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
12591: }
1.321 ! brouard 12592: fprintf(fichtm,"sqrt(W)=%8.3f</br>",wald);
1.319 brouard 12593: 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 12594: jk++;
12595: }
12596: printf("\n");
12597: fprintf(ficlog,"\n");
1.319 brouard 12598: fprintf(fichtm, "</tr>\n");
1.225 brouard 12599: }
12600: }
1.193 brouard 12601: }
1.203 brouard 12602: } /* end of hesscov and Wald tests */
1.319 brouard 12603: fprintf(fichtm,"</table>\n");
1.225 brouard 12604:
1.203 brouard 12605: /* */
1.126 brouard 12606: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
12607: printf("# Scales (for hessian or gradient estimation)\n");
12608: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
12609: for(i=1,jk=1; i <=nlstate; i++){
12610: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 12611: if (j!=i) {
12612: fprintf(ficres,"%1d%1d",i,j);
12613: printf("%1d%1d",i,j);
12614: fprintf(ficlog,"%1d%1d",i,j);
12615: for(k=1; k<=ncovmodel;k++){
12616: printf(" %.5e",delti[jk]);
12617: fprintf(ficlog," %.5e",delti[jk]);
12618: fprintf(ficres," %.5e",delti[jk]);
12619: jk++;
12620: }
12621: printf("\n");
12622: fprintf(ficlog,"\n");
12623: fprintf(ficres,"\n");
12624: }
1.126 brouard 12625: }
12626: }
12627:
12628: 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 12629: if(mle >= 1) /* To big for the screen */
1.126 brouard 12630: 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");
12631: 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");
12632: /* # 121 Var(a12)\n\ */
12633: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12634: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12635: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12636: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12637: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12638: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12639: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12640:
12641:
12642: /* Just to have a covariance matrix which will be more understandable
12643: even is we still don't want to manage dictionary of variables
12644: */
12645: for(itimes=1;itimes<=2;itimes++){
12646: jj=0;
12647: for(i=1; i <=nlstate; i++){
1.225 brouard 12648: for(j=1; j <=nlstate+ndeath; j++){
12649: if(j==i) continue;
12650: for(k=1; k<=ncovmodel;k++){
12651: jj++;
12652: ca[0]= k+'a'-1;ca[1]='\0';
12653: if(itimes==1){
12654: if(mle>=1)
12655: printf("#%1d%1d%d",i,j,k);
12656: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12657: fprintf(ficres,"#%1d%1d%d",i,j,k);
12658: }else{
12659: if(mle>=1)
12660: printf("%1d%1d%d",i,j,k);
12661: fprintf(ficlog,"%1d%1d%d",i,j,k);
12662: fprintf(ficres,"%1d%1d%d",i,j,k);
12663: }
12664: ll=0;
12665: for(li=1;li <=nlstate; li++){
12666: for(lj=1;lj <=nlstate+ndeath; lj++){
12667: if(lj==li) continue;
12668: for(lk=1;lk<=ncovmodel;lk++){
12669: ll++;
12670: if(ll<=jj){
12671: cb[0]= lk +'a'-1;cb[1]='\0';
12672: if(ll<jj){
12673: if(itimes==1){
12674: if(mle>=1)
12675: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12676: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12677: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12678: }else{
12679: if(mle>=1)
12680: printf(" %.5e",matcov[jj][ll]);
12681: fprintf(ficlog," %.5e",matcov[jj][ll]);
12682: fprintf(ficres," %.5e",matcov[jj][ll]);
12683: }
12684: }else{
12685: if(itimes==1){
12686: if(mle>=1)
12687: printf(" Var(%s%1d%1d)",ca,i,j);
12688: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12689: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12690: }else{
12691: if(mle>=1)
12692: printf(" %.7e",matcov[jj][ll]);
12693: fprintf(ficlog," %.7e",matcov[jj][ll]);
12694: fprintf(ficres," %.7e",matcov[jj][ll]);
12695: }
12696: }
12697: }
12698: } /* end lk */
12699: } /* end lj */
12700: } /* end li */
12701: if(mle>=1)
12702: printf("\n");
12703: fprintf(ficlog,"\n");
12704: fprintf(ficres,"\n");
12705: numlinepar++;
12706: } /* end k*/
12707: } /*end j */
1.126 brouard 12708: } /* end i */
12709: } /* end itimes */
12710:
12711: fflush(ficlog);
12712: fflush(ficres);
1.225 brouard 12713: while(fgets(line, MAXLINE, ficpar)) {
12714: /* If line starts with a # it is a comment */
12715: if (line[0] == '#') {
12716: numlinepar++;
12717: fputs(line,stdout);
12718: fputs(line,ficparo);
12719: fputs(line,ficlog);
1.299 brouard 12720: fputs(line,ficres);
1.225 brouard 12721: continue;
12722: }else
12723: break;
12724: }
12725:
1.209 brouard 12726: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12727: /* ungetc(c,ficpar); */
12728: /* fgets(line, MAXLINE, ficpar); */
12729: /* fputs(line,stdout); */
12730: /* fputs(line,ficparo); */
12731: /* } */
12732: /* ungetc(c,ficpar); */
1.126 brouard 12733:
12734: estepm=0;
1.209 brouard 12735: 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 12736:
12737: if (num_filled != 6) {
12738: 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);
12739: 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);
12740: goto end;
12741: }
12742: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12743: }
12744: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12745: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12746:
1.209 brouard 12747: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12748: if (estepm==0 || estepm < stepm) estepm=stepm;
12749: if (fage <= 2) {
12750: bage = ageminpar;
12751: fage = agemaxpar;
12752: }
12753:
12754: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12755: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12756: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12757:
1.186 brouard 12758: /* Other stuffs, more or less useful */
1.254 brouard 12759: while(fgets(line, MAXLINE, ficpar)) {
12760: /* If line starts with a # it is a comment */
12761: if (line[0] == '#') {
12762: numlinepar++;
12763: fputs(line,stdout);
12764: fputs(line,ficparo);
12765: fputs(line,ficlog);
1.299 brouard 12766: fputs(line,ficres);
1.254 brouard 12767: continue;
12768: }else
12769: break;
12770: }
12771:
12772: 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){
12773:
12774: if (num_filled != 7) {
12775: 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);
12776: 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);
12777: goto end;
12778: }
12779: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12780: 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);
12781: 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);
12782: 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 12783: }
1.254 brouard 12784:
12785: while(fgets(line, MAXLINE, ficpar)) {
12786: /* If line starts with a # it is a comment */
12787: if (line[0] == '#') {
12788: numlinepar++;
12789: fputs(line,stdout);
12790: fputs(line,ficparo);
12791: fputs(line,ficlog);
1.299 brouard 12792: fputs(line,ficres);
1.254 brouard 12793: continue;
12794: }else
12795: break;
1.126 brouard 12796: }
12797:
12798:
12799: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12800: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12801:
1.254 brouard 12802: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12803: if (num_filled != 1) {
12804: 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);
12805: 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);
12806: goto end;
12807: }
12808: printf("pop_based=%d\n",popbased);
12809: fprintf(ficlog,"pop_based=%d\n",popbased);
12810: fprintf(ficparo,"pop_based=%d\n",popbased);
12811: fprintf(ficres,"pop_based=%d\n",popbased);
12812: }
12813:
1.258 brouard 12814: /* Results */
1.307 brouard 12815: endishere=0;
1.258 brouard 12816: nresult=0;
1.308 brouard 12817: parameterline=0;
1.258 brouard 12818: do{
12819: if(!fgets(line, MAXLINE, ficpar)){
12820: endishere=1;
1.308 brouard 12821: parameterline=15;
1.258 brouard 12822: }else if (line[0] == '#') {
12823: /* If line starts with a # it is a comment */
1.254 brouard 12824: numlinepar++;
12825: fputs(line,stdout);
12826: fputs(line,ficparo);
12827: fputs(line,ficlog);
1.299 brouard 12828: fputs(line,ficres);
1.254 brouard 12829: continue;
1.258 brouard 12830: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12831: parameterline=11;
1.296 brouard 12832: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 12833: parameterline=12;
1.307 brouard 12834: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 12835: parameterline=13;
1.307 brouard 12836: }
1.258 brouard 12837: else{
12838: parameterline=14;
1.254 brouard 12839: }
1.308 brouard 12840: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 12841: case 11:
1.296 brouard 12842: 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)){
12843: 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 12844: 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);
12845: 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);
12846: 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);
12847: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12848: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12849: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 12850: prvforecast = 1;
12851: }
12852: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 12853: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
12854: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
12855: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 12856: prvforecast = 2;
12857: }
12858: else {
12859: 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);
12860: 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);
12861: goto end;
1.258 brouard 12862: }
1.254 brouard 12863: break;
1.258 brouard 12864: case 12:
1.296 brouard 12865: 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)){
12866: 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);
12867: 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);
12868: 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);
12869: 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);
12870: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 12871: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12872: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 12873: prvbackcast = 1;
12874: }
12875: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 12876: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
12877: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
12878: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 12879: prvbackcast = 2;
12880: }
12881: else {
12882: 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);
12883: 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);
12884: goto end;
1.258 brouard 12885: }
1.230 brouard 12886: break;
1.258 brouard 12887: case 13:
1.307 brouard 12888: num_filled=sscanf(line,"result:%[^\n]\n",resultline);
12889: nresult++; /* Sum of resultlines */
12890: printf("Result %d: result:%s\n",nresult, resultline);
1.318 brouard 12891: if(nresult > MAXRESULTLINESPONE-1){
12892: 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);
12893: 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 12894: goto end;
12895: }
1.310 brouard 12896: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 12897: fprintf(ficparo,"result: %s\n",resultline);
12898: fprintf(ficres,"result: %s\n",resultline);
12899: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 12900: } else
12901: goto end;
1.307 brouard 12902: break;
12903: case 14:
12904: printf("Error: Unknown command '%s'\n",line);
12905: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 12906: if(line[0] == ' ' || line[0] == '\n'){
12907: printf("It should not be an empty line '%s'\n",line);
12908: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
12909: }
1.307 brouard 12910: if(ncovmodel >=2 && nresult==0 ){
12911: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
12912: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12913: }
1.307 brouard 12914: /* goto end; */
12915: break;
1.308 brouard 12916: case 15:
12917: printf("End of resultlines.\n");
12918: fprintf(ficlog,"End of resultlines.\n");
12919: break;
12920: default: /* parameterline =0 */
1.307 brouard 12921: nresult=1;
12922: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 12923: } /* End switch parameterline */
12924: }while(endishere==0); /* End do */
1.126 brouard 12925:
1.230 brouard 12926: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12927: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12928:
12929: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12930: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12931: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12932: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12933: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12934: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12935: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12936: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12937: }else{
1.270 brouard 12938: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 12939: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
12940: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
12941: if(prvforecast==1){
12942: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
12943: jprojd=jproj1;
12944: mprojd=mproj1;
12945: anprojd=anproj1;
12946: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
12947: jprojf=jproj2;
12948: mprojf=mproj2;
12949: anprojf=anproj2;
12950: } else if(prvforecast == 2){
12951: dateprojd=dateintmean;
12952: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
12953: dateprojf=dateintmean+yrfproj;
12954: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
12955: }
12956: if(prvbackcast==1){
12957: datebackd=(jback1+12*mback1+365*anback1)/365;
12958: jbackd=jback1;
12959: mbackd=mback1;
12960: anbackd=anback1;
12961: datebackf=(jback2+12*mback2+365*anback2)/365;
12962: jbackf=jback2;
12963: mbackf=mback2;
12964: anbackf=anback2;
12965: } else if(prvbackcast == 2){
12966: datebackd=dateintmean;
12967: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
12968: datebackf=dateintmean-yrbproj;
12969: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
12970: }
12971:
12972: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 12973: }
12974: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 12975: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
12976: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 12977:
1.225 brouard 12978: /*------------ free_vector -------------*/
12979: /* chdir(path); */
1.220 brouard 12980:
1.215 brouard 12981: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12982: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12983: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12984: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 12985: free_lvector(num,firstobs,lastobs);
12986: free_vector(agedc,firstobs,lastobs);
1.126 brouard 12987: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12988: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12989: fclose(ficparo);
12990: fclose(ficres);
1.220 brouard 12991:
12992:
1.186 brouard 12993: /* Other results (useful)*/
1.220 brouard 12994:
12995:
1.126 brouard 12996: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12997: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12998: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12999: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 13000: fclose(ficrespl);
13001:
13002: /*------------- h Pij x at various ages ------------*/
1.180 brouard 13003: /*#include "hpijx.h"*/
13004: hPijx(p, bage, fage);
1.145 brouard 13005: fclose(ficrespij);
1.227 brouard 13006:
1.220 brouard 13007: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 13008: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 13009: k=1;
1.126 brouard 13010: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 13011:
1.269 brouard 13012: /* Prevalence for each covariate combination in probs[age][status][cov] */
13013: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13014: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 13015: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 13016: for(k=1;k<=ncovcombmax;k++)
13017: probs[i][j][k]=0.;
1.269 brouard 13018: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
13019: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 13020: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 13021: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
13022: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 13023: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 13024: for(k=1;k<=ncovcombmax;k++)
13025: mobaverages[i][j][k]=0.;
1.219 brouard 13026: mobaverage=mobaverages;
13027: if (mobilav!=0) {
1.235 brouard 13028: printf("Movingaveraging observed prevalence\n");
1.258 brouard 13029: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 13030: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
13031: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
13032: printf(" Error in movingaverage mobilav=%d\n",mobilav);
13033: }
1.269 brouard 13034: } else if (mobilavproj !=0) {
1.235 brouard 13035: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 13036: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 13037: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
13038: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
13039: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
13040: }
1.269 brouard 13041: }else{
13042: printf("Internal error moving average\n");
13043: fflush(stdout);
13044: exit(1);
1.219 brouard 13045: }
13046: }/* end if moving average */
1.227 brouard 13047:
1.126 brouard 13048: /*---------- Forecasting ------------------*/
1.296 brouard 13049: if(prevfcast==1){
13050: /* /\* if(stepm ==1){*\/ */
13051: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13052: /*This done previously after freqsummary.*/
13053: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
13054: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
13055:
13056: /* } else if (prvforecast==2){ */
13057: /* /\* if(stepm ==1){*\/ */
13058: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
13059: /* } */
13060: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
13061: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 13062: }
1.269 brouard 13063:
1.296 brouard 13064: /* Prevbcasting */
13065: if(prevbcast==1){
1.219 brouard 13066: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13067: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13068: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
13069:
13070: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
13071:
13072: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 13073:
1.219 brouard 13074: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
13075: fclose(ficresplb);
13076:
1.222 brouard 13077: hBijx(p, bage, fage, mobaverage);
13078: fclose(ficrespijb);
1.219 brouard 13079:
1.296 brouard 13080: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
13081: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
13082: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
13083: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
13084: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
13085: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
13086:
13087:
1.269 brouard 13088: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13089:
13090:
1.269 brouard 13091: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 13092: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13093: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
13094: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 13095: } /* end Prevbcasting */
1.268 brouard 13096:
1.186 brouard 13097:
13098: /* ------ Other prevalence ratios------------ */
1.126 brouard 13099:
1.215 brouard 13100: free_ivector(wav,1,imx);
13101: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
13102: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
13103: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 13104:
13105:
1.127 brouard 13106: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 13107:
1.201 brouard 13108: strcpy(filerese,"E_");
13109: strcat(filerese,fileresu);
1.126 brouard 13110: if((ficreseij=fopen(filerese,"w"))==NULL) {
13111: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13112: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
13113: }
1.208 brouard 13114: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
13115: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 13116:
13117: pstamp(ficreseij);
1.219 brouard 13118:
1.235 brouard 13119: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13120: if (cptcovn < 1){i1=1;}
13121:
13122: for(nres=1; nres <= nresult; nres++) /* For each resultline */
13123: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 13124: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 13125: continue;
1.219 brouard 13126: fprintf(ficreseij,"\n#****** ");
1.235 brouard 13127: printf("\n#****** ");
1.225 brouard 13128: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 13129: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 13130: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13131: }
13132: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13133: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13134: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 13135: }
13136: fprintf(ficreseij,"******\n");
1.235 brouard 13137: printf("******\n");
1.219 brouard 13138:
13139: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13140: oldm=oldms;savm=savms;
1.235 brouard 13141: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 13142:
1.219 brouard 13143: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 13144: }
13145: fclose(ficreseij);
1.208 brouard 13146: printf("done evsij\n");fflush(stdout);
13147: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 13148:
1.218 brouard 13149:
1.227 brouard 13150: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 13151:
1.201 brouard 13152: strcpy(filerest,"T_");
13153: strcat(filerest,fileresu);
1.127 brouard 13154: if((ficrest=fopen(filerest,"w"))==NULL) {
13155: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
13156: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
13157: }
1.208 brouard 13158: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
13159: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 13160: strcpy(fileresstde,"STDE_");
13161: strcat(fileresstde,fileresu);
1.126 brouard 13162: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 13163: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
13164: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 13165: }
1.227 brouard 13166: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
13167: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 13168:
1.201 brouard 13169: strcpy(filerescve,"CVE_");
13170: strcat(filerescve,fileresu);
1.126 brouard 13171: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 13172: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
13173: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 13174: }
1.227 brouard 13175: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
13176: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 13177:
1.201 brouard 13178: strcpy(fileresv,"V_");
13179: strcat(fileresv,fileresu);
1.126 brouard 13180: if((ficresvij=fopen(fileresv,"w"))==NULL) {
13181: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
13182: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
13183: }
1.227 brouard 13184: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
13185: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 13186:
1.235 brouard 13187: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
13188: if (cptcovn < 1){i1=1;}
13189:
13190: for(nres=1; nres <= nresult; nres++) /* For each resultline */
13191: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 13192: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 13193: continue;
1.321 ! brouard 13194: printf("\n# model %s \n#****** Result for:", model);
! 13195: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
! 13196: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.227 brouard 13197: for(j=1;j<=cptcoveff;j++){
13198: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13199: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13200: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13201: }
1.235 brouard 13202: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13203: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13204: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13205: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13206: }
1.208 brouard 13207: fprintf(ficrest,"******\n");
1.227 brouard 13208: fprintf(ficlog,"******\n");
13209: printf("******\n");
1.208 brouard 13210:
13211: fprintf(ficresstdeij,"\n#****** ");
13212: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 13213: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 13214: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
13215: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 13216: }
1.235 brouard 13217: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13218: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13219: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13220: }
1.208 brouard 13221: fprintf(ficresstdeij,"******\n");
13222: fprintf(ficrescveij,"******\n");
13223:
13224: fprintf(ficresvij,"\n#****** ");
1.238 brouard 13225: /* pstamp(ficresvij); */
1.225 brouard 13226: for(j=1;j<=cptcoveff;j++)
1.227 brouard 13227: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 13228: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
13229: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
13230: }
1.208 brouard 13231: fprintf(ficresvij,"******\n");
13232:
13233: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13234: oldm=oldms;savm=savms;
1.235 brouard 13235: printf(" cvevsij ");
13236: fprintf(ficlog, " cvevsij ");
13237: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 13238: printf(" end cvevsij \n ");
13239: fprintf(ficlog, " end cvevsij \n ");
13240:
13241: /*
13242: */
13243: /* goto endfree; */
13244:
13245: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
13246: pstamp(ficrest);
13247:
1.269 brouard 13248: epj=vector(1,nlstate+1);
1.208 brouard 13249: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 13250: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
13251: cptcod= 0; /* To be deleted */
13252: printf("varevsij vpopbased=%d \n",vpopbased);
13253: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 13254: 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 13255: 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 ");
13256: if(vpopbased==1)
13257: 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);
13258: else
1.288 brouard 13259: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13260: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
13261: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
13262: fprintf(ficrest,"\n");
13263: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 13264: printf("Computing age specific forward period (stable) prevalences in each health state \n");
13265: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 13266: for(age=bage; age <=fage ;age++){
1.235 brouard 13267: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 13268: if (vpopbased==1) {
13269: if(mobilav ==0){
13270: for(i=1; i<=nlstate;i++)
13271: prlim[i][i]=probs[(int)age][i][k];
13272: }else{ /* mobilav */
13273: for(i=1; i<=nlstate;i++)
13274: prlim[i][i]=mobaverage[(int)age][i][k];
13275: }
13276: }
1.219 brouard 13277:
1.227 brouard 13278: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
13279: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
13280: /* printf(" age %4.0f ",age); */
13281: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
13282: for(i=1, epj[j]=0.;i <=nlstate;i++) {
13283: epj[j] += prlim[i][i]*eij[i][j][(int)age];
13284: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
13285: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
13286: }
13287: epj[nlstate+1] +=epj[j];
13288: }
13289: /* printf(" age %4.0f \n",age); */
1.219 brouard 13290:
1.227 brouard 13291: for(i=1, vepp=0.;i <=nlstate;i++)
13292: for(j=1;j <=nlstate;j++)
13293: vepp += vareij[i][j][(int)age];
13294: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
13295: for(j=1;j <=nlstate;j++){
13296: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
13297: }
13298: fprintf(ficrest,"\n");
13299: }
1.208 brouard 13300: } /* End vpopbased */
1.269 brouard 13301: free_vector(epj,1,nlstate+1);
1.208 brouard 13302: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
13303: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 13304: printf("done selection\n");fflush(stdout);
13305: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 13306:
1.235 brouard 13307: } /* End k selection */
1.227 brouard 13308:
13309: printf("done State-specific expectancies\n");fflush(stdout);
13310: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
13311:
1.288 brouard 13312: /* variance-covariance of forward period prevalence*/
1.269 brouard 13313: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 13314:
1.227 brouard 13315:
1.290 brouard 13316: free_vector(weight,firstobs,lastobs);
1.227 brouard 13317: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 13318: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
13319: free_matrix(anint,1,maxwav,firstobs,lastobs);
13320: free_matrix(mint,1,maxwav,firstobs,lastobs);
13321: free_ivector(cod,firstobs,lastobs);
1.227 brouard 13322: free_ivector(tab,1,NCOVMAX);
13323: fclose(ficresstdeij);
13324: fclose(ficrescveij);
13325: fclose(ficresvij);
13326: fclose(ficrest);
13327: fclose(ficpar);
13328:
13329:
1.126 brouard 13330: /*---------- End : free ----------------*/
1.219 brouard 13331: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 13332: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
13333: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 13334: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
13335: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 13336: } /* mle==-3 arrives here for freeing */
1.227 brouard 13337: /* endfree:*/
13338: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
13339: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
13340: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 13341: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
13342: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
13343: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
13344: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 13345: free_matrix(matcov,1,npar,1,npar);
13346: free_matrix(hess,1,npar,1,npar);
13347: /*free_vector(delti,1,npar);*/
13348: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13349: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 13350: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 13351: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13352:
13353: free_ivector(ncodemax,1,NCOVMAX);
13354: free_ivector(ncodemaxwundef,1,NCOVMAX);
13355: free_ivector(Dummy,-1,NCOVMAX);
13356: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 13357: free_ivector(DummyV,1,NCOVMAX);
13358: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 13359: free_ivector(Typevar,-1,NCOVMAX);
13360: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 13361: free_ivector(TvarsQ,1,NCOVMAX);
13362: free_ivector(TvarsQind,1,NCOVMAX);
13363: free_ivector(TvarsD,1,NCOVMAX);
13364: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 13365: free_ivector(TvarFD,1,NCOVMAX);
13366: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 13367: free_ivector(TvarF,1,NCOVMAX);
13368: free_ivector(TvarFind,1,NCOVMAX);
13369: free_ivector(TvarV,1,NCOVMAX);
13370: free_ivector(TvarVind,1,NCOVMAX);
13371: free_ivector(TvarA,1,NCOVMAX);
13372: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 13373: free_ivector(TvarFQ,1,NCOVMAX);
13374: free_ivector(TvarFQind,1,NCOVMAX);
13375: free_ivector(TvarVD,1,NCOVMAX);
13376: free_ivector(TvarVDind,1,NCOVMAX);
13377: free_ivector(TvarVQ,1,NCOVMAX);
13378: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 13379: free_ivector(Tvarsel,1,NCOVMAX);
13380: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 13381: free_ivector(Tposprod,1,NCOVMAX);
13382: free_ivector(Tprod,1,NCOVMAX);
13383: free_ivector(Tvaraff,1,NCOVMAX);
13384: free_ivector(invalidvarcomb,1,ncovcombmax);
13385: free_ivector(Tage,1,NCOVMAX);
13386: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 13387: free_ivector(TmodelInvind,1,NCOVMAX);
13388: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 13389:
13390: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
13391: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 13392: fflush(fichtm);
13393: fflush(ficgp);
13394:
1.227 brouard 13395:
1.126 brouard 13396: if((nberr >0) || (nbwarn>0)){
1.216 brouard 13397: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
13398: 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 13399: }else{
13400: printf("End of Imach\n");
13401: fprintf(ficlog,"End of Imach\n");
13402: }
13403: printf("See log file on %s\n",filelog);
13404: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 13405: /*(void) gettimeofday(&end_time,&tzp);*/
13406: rend_time = time(NULL);
13407: end_time = *localtime(&rend_time);
13408: /* tml = *localtime(&end_time.tm_sec); */
13409: strcpy(strtend,asctime(&end_time));
1.126 brouard 13410: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
13411: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 13412: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 13413:
1.157 brouard 13414: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
13415: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
13416: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 13417: /* printf("Total time was %d uSec.\n", total_usecs);*/
13418: /* if(fileappend(fichtm,optionfilehtm)){ */
13419: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13420: fclose(fichtm);
13421: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13422: fclose(fichtmcov);
13423: fclose(ficgp);
13424: fclose(ficlog);
13425: /*------ End -----------*/
1.227 brouard 13426:
1.281 brouard 13427:
13428: /* Executes gnuplot */
1.227 brouard 13429:
13430: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 13431: #ifdef WIN32
1.227 brouard 13432: if (_chdir(pathcd) != 0)
13433: printf("Can't move to directory %s!\n",path);
13434: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 13435: #else
1.227 brouard 13436: if(chdir(pathcd) != 0)
13437: printf("Can't move to directory %s!\n", path);
13438: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 13439: #endif
1.126 brouard 13440: printf("Current directory %s!\n",pathcd);
13441: /*strcat(plotcmd,CHARSEPARATOR);*/
13442: sprintf(plotcmd,"gnuplot");
1.157 brouard 13443: #ifdef _WIN32
1.126 brouard 13444: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
13445: #endif
13446: if(!stat(plotcmd,&info)){
1.158 brouard 13447: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13448: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 13449: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 13450: }else
13451: strcpy(pplotcmd,plotcmd);
1.157 brouard 13452: #ifdef __unix
1.126 brouard 13453: strcpy(plotcmd,GNUPLOTPROGRAM);
13454: if(!stat(plotcmd,&info)){
1.158 brouard 13455: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13456: }else
13457: strcpy(pplotcmd,plotcmd);
13458: #endif
13459: }else
13460: strcpy(pplotcmd,plotcmd);
13461:
13462: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 13463: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 13464: strcpy(pplotcmd,plotcmd);
1.227 brouard 13465:
1.126 brouard 13466: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 13467: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 13468: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 13469: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 13470: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 13471: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 13472: strcpy(plotcmd,pplotcmd);
13473: }
1.126 brouard 13474: }
1.158 brouard 13475: printf(" Successful, please wait...");
1.126 brouard 13476: while (z[0] != 'q') {
13477: /* chdir(path); */
1.154 brouard 13478: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 13479: scanf("%s",z);
13480: /* if (z[0] == 'c') system("./imach"); */
13481: if (z[0] == 'e') {
1.158 brouard 13482: #ifdef __APPLE__
1.152 brouard 13483: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 13484: #elif __linux
13485: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 13486: #else
1.152 brouard 13487: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 13488: #endif
13489: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
13490: system(pplotcmd);
1.126 brouard 13491: }
13492: else if (z[0] == 'g') system(plotcmd);
13493: else if (z[0] == 'q') exit(0);
13494: }
1.227 brouard 13495: end:
1.126 brouard 13496: while (z[0] != 'q') {
1.195 brouard 13497: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 13498: scanf("%s",z);
13499: }
1.283 brouard 13500: printf("End\n");
1.282 brouard 13501: exit(0);
1.126 brouard 13502: }
FreeBSD-CVSweb <freebsd-cvsweb@FreeBSD.org>
![[BACK]](/icons/small/back.gif){kind=icon}
Return to imach.c CVS log ![[TXT]](/icons/small/text.gif){kind=icon}
![[DIR]](/icons/small/dir.gif){kind=icon}
Up to [Local Repository] / imach / src