Annotation of imach/src/imach.c, revision 1.313
1.313 ! brouard 1: /* $Id: imach.c,v 1.312 2022/04/05 21:24:39 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.313 ! brouard 4: Revision 1.312 2022/04/05 21:24:39 brouard
! 5: *** empty log message ***
! 6:
1.312 brouard 7: Revision 1.311 2022/04/05 21:03:51 brouard
8: Summary: Fixed quantitative covariates
9:
10: Fixed covariates (dummy or quantitative)
11: with missing values have never been allowed but are ERRORS and
12: program quits. Standard deviations of fixed covariates were
13: wrongly computed. Mean and standard deviations of time varying
14: covariates are still not computed.
15:
1.311 brouard 16: Revision 1.310 2022/03/17 08:45:53 brouard
17: Summary: 99r25
18:
19: Improving detection of errors: result lines should be compatible with
20: the model.
21:
1.310 brouard 22: Revision 1.309 2021/05/20 12:39:14 brouard
23: Summary: Version 0.99r24
24:
1.309 brouard 25: Revision 1.308 2021/03/31 13:11:57 brouard
26: Summary: Version 0.99r23
27:
28:
29: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
30:
1.308 brouard 31: Revision 1.307 2021/03/08 18:11:32 brouard
32: Summary: 0.99r22 fixed bug on result:
33:
1.307 brouard 34: Revision 1.306 2021/02/20 15:44:02 brouard
35: Summary: Version 0.99r21
36:
37: * imach.c (Module): Fix bug on quitting after result lines!
38: (Module): Version 0.99r21
39:
1.306 brouard 40: Revision 1.305 2021/02/20 15:28:30 brouard
41: * imach.c (Module): Fix bug on quitting after result lines!
42:
1.305 brouard 43: Revision 1.304 2021/02/12 11:34:20 brouard
44: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
45:
1.304 brouard 46: Revision 1.303 2021/02/11 19:50:15 brouard
47: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
48:
1.303 brouard 49: Revision 1.302 2020/02/22 21:00:05 brouard
50: * (Module): imach.c Update mle=-3 (for computing Life expectancy
51: and life table from the data without any state)
52:
1.302 brouard 53: Revision 1.301 2019/06/04 13:51:20 brouard
54: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
55:
1.301 brouard 56: Revision 1.300 2019/05/22 19:09:45 brouard
57: Summary: version 0.99r19 of May 2019
58:
1.300 brouard 59: Revision 1.299 2019/05/22 18:37:08 brouard
60: Summary: Cleaned 0.99r19
61:
1.299 brouard 62: Revision 1.298 2019/05/22 18:19:56 brouard
63: *** empty log message ***
64:
1.298 brouard 65: Revision 1.297 2019/05/22 17:56:10 brouard
66: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
67:
1.297 brouard 68: Revision 1.296 2019/05/20 13:03:18 brouard
69: Summary: Projection syntax simplified
70:
71:
72: We can now start projections, forward or backward, from the mean date
73: of inteviews up to or down to a number of years of projection:
74: prevforecast=1 yearsfproj=15.3 mobil_average=0
75: or
76: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
77: or
78: prevbackcast=1 yearsbproj=12.3 mobil_average=1
79: or
80: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
81:
1.296 brouard 82: Revision 1.295 2019/05/18 09:52:50 brouard
83: Summary: doxygen tex bug
84:
1.295 brouard 85: Revision 1.294 2019/05/16 14:54:33 brouard
86: Summary: There was some wrong lines added
87:
1.294 brouard 88: Revision 1.293 2019/05/09 15:17:34 brouard
89: *** empty log message ***
90:
1.293 brouard 91: Revision 1.292 2019/05/09 14:17:20 brouard
92: Summary: Some updates
93:
1.292 brouard 94: Revision 1.291 2019/05/09 13:44:18 brouard
95: Summary: Before ncovmax
96:
1.291 brouard 97: Revision 1.290 2019/05/09 13:39:37 brouard
98: Summary: 0.99r18 unlimited number of individuals
99:
100: 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.
101:
1.290 brouard 102: Revision 1.289 2018/12/13 09:16:26 brouard
103: Summary: Bug for young ages (<-30) will be in r17
104:
1.289 brouard 105: Revision 1.288 2018/05/02 20:58:27 brouard
106: Summary: Some bugs fixed
107:
1.288 brouard 108: Revision 1.287 2018/05/01 17:57:25 brouard
109: Summary: Bug fixed by providing frequencies only for non missing covariates
110:
1.287 brouard 111: Revision 1.286 2018/04/27 14:27:04 brouard
112: Summary: some minor bugs
113:
1.286 brouard 114: Revision 1.285 2018/04/21 21:02:16 brouard
115: Summary: Some bugs fixed, valgrind tested
116:
1.285 brouard 117: Revision 1.284 2018/04/20 05:22:13 brouard
118: Summary: Computing mean and stdeviation of fixed quantitative variables
119:
1.284 brouard 120: Revision 1.283 2018/04/19 14:49:16 brouard
121: Summary: Some minor bugs fixed
122:
1.283 brouard 123: Revision 1.282 2018/02/27 22:50:02 brouard
124: *** empty log message ***
125:
1.282 brouard 126: Revision 1.281 2018/02/27 19:25:23 brouard
127: Summary: Adding second argument for quitting
128:
1.281 brouard 129: Revision 1.280 2018/02/21 07:58:13 brouard
130: Summary: 0.99r15
131:
132: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
133:
1.280 brouard 134: Revision 1.279 2017/07/20 13:35:01 brouard
135: Summary: temporary working
136:
1.279 brouard 137: Revision 1.278 2017/07/19 14:09:02 brouard
138: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
139:
1.278 brouard 140: Revision 1.277 2017/07/17 08:53:49 brouard
141: Summary: BOM files can be read now
142:
1.277 brouard 143: Revision 1.276 2017/06/30 15:48:31 brouard
144: Summary: Graphs improvements
145:
1.276 brouard 146: Revision 1.275 2017/06/30 13:39:33 brouard
147: Summary: Saito's color
148:
1.275 brouard 149: Revision 1.274 2017/06/29 09:47:08 brouard
150: Summary: Version 0.99r14
151:
1.274 brouard 152: Revision 1.273 2017/06/27 11:06:02 brouard
153: Summary: More documentation on projections
154:
1.273 brouard 155: Revision 1.272 2017/06/27 10:22:40 brouard
156: Summary: Color of backprojection changed from 6 to 5(yellow)
157:
1.272 brouard 158: Revision 1.271 2017/06/27 10:17:50 brouard
159: Summary: Some bug with rint
160:
1.271 brouard 161: Revision 1.270 2017/05/24 05:45:29 brouard
162: *** empty log message ***
163:
1.270 brouard 164: Revision 1.269 2017/05/23 08:39:25 brouard
165: Summary: Code into subroutine, cleanings
166:
1.269 brouard 167: Revision 1.268 2017/05/18 20:09:32 brouard
168: Summary: backprojection and confidence intervals of backprevalence
169:
1.268 brouard 170: Revision 1.267 2017/05/13 10:25:05 brouard
171: Summary: temporary save for backprojection
172:
1.267 brouard 173: Revision 1.266 2017/05/13 07:26:12 brouard
174: Summary: Version 0.99r13 (improvements and bugs fixed)
175:
1.266 brouard 176: Revision 1.265 2017/04/26 16:22:11 brouard
177: Summary: imach 0.99r13 Some bugs fixed
178:
1.265 brouard 179: Revision 1.264 2017/04/26 06:01:29 brouard
180: Summary: Labels in graphs
181:
1.264 brouard 182: Revision 1.263 2017/04/24 15:23:15 brouard
183: Summary: to save
184:
1.263 brouard 185: Revision 1.262 2017/04/18 16:48:12 brouard
186: *** empty log message ***
187:
1.262 brouard 188: Revision 1.261 2017/04/05 10:14:09 brouard
189: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
190:
1.261 brouard 191: Revision 1.260 2017/04/04 17:46:59 brouard
192: Summary: Gnuplot indexations fixed (humm)
193:
1.260 brouard 194: Revision 1.259 2017/04/04 13:01:16 brouard
195: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
196:
1.259 brouard 197: Revision 1.258 2017/04/03 10:17:47 brouard
198: Summary: Version 0.99r12
199:
200: Some cleanings, conformed with updated documentation.
201:
1.258 brouard 202: Revision 1.257 2017/03/29 16:53:30 brouard
203: Summary: Temp
204:
1.257 brouard 205: Revision 1.256 2017/03/27 05:50:23 brouard
206: Summary: Temporary
207:
1.256 brouard 208: Revision 1.255 2017/03/08 16:02:28 brouard
209: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
210:
1.255 brouard 211: Revision 1.254 2017/03/08 07:13:00 brouard
212: Summary: Fixing data parameter line
213:
1.254 brouard 214: Revision 1.253 2016/12/15 11:59:41 brouard
215: Summary: 0.99 in progress
216:
1.253 brouard 217: Revision 1.252 2016/09/15 21:15:37 brouard
218: *** empty log message ***
219:
1.252 brouard 220: Revision 1.251 2016/09/15 15:01:13 brouard
221: Summary: not working
222:
1.251 brouard 223: Revision 1.250 2016/09/08 16:07:27 brouard
224: Summary: continue
225:
1.250 brouard 226: Revision 1.249 2016/09/07 17:14:18 brouard
227: Summary: Starting values from frequencies
228:
1.249 brouard 229: Revision 1.248 2016/09/07 14:10:18 brouard
230: *** empty log message ***
231:
1.248 brouard 232: Revision 1.247 2016/09/02 11:11:21 brouard
233: *** empty log message ***
234:
1.247 brouard 235: Revision 1.246 2016/09/02 08:49:22 brouard
236: *** empty log message ***
237:
1.246 brouard 238: Revision 1.245 2016/09/02 07:25:01 brouard
239: *** empty log message ***
240:
1.245 brouard 241: Revision 1.244 2016/09/02 07:17:34 brouard
242: *** empty log message ***
243:
1.244 brouard 244: Revision 1.243 2016/09/02 06:45:35 brouard
245: *** empty log message ***
246:
1.243 brouard 247: Revision 1.242 2016/08/30 15:01:20 brouard
248: Summary: Fixing a lots
249:
1.242 brouard 250: Revision 1.241 2016/08/29 17:17:25 brouard
251: Summary: gnuplot problem in Back projection to fix
252:
1.241 brouard 253: Revision 1.240 2016/08/29 07:53:18 brouard
254: Summary: Better
255:
1.240 brouard 256: Revision 1.239 2016/08/26 15:51:03 brouard
257: Summary: Improvement in Powell output in order to copy and paste
258:
259: Author:
260:
1.239 brouard 261: Revision 1.238 2016/08/26 14:23:35 brouard
262: Summary: Starting tests of 0.99
263:
1.238 brouard 264: Revision 1.237 2016/08/26 09:20:19 brouard
265: Summary: to valgrind
266:
1.237 brouard 267: Revision 1.236 2016/08/25 10:50:18 brouard
268: *** empty log message ***
269:
1.236 brouard 270: Revision 1.235 2016/08/25 06:59:23 brouard
271: *** empty log message ***
272:
1.235 brouard 273: Revision 1.234 2016/08/23 16:51:20 brouard
274: *** empty log message ***
275:
1.234 brouard 276: Revision 1.233 2016/08/23 07:40:50 brouard
277: Summary: not working
278:
1.233 brouard 279: Revision 1.232 2016/08/22 14:20:21 brouard
280: Summary: not working
281:
1.232 brouard 282: Revision 1.231 2016/08/22 07:17:15 brouard
283: Summary: not working
284:
1.231 brouard 285: Revision 1.230 2016/08/22 06:55:53 brouard
286: Summary: Not working
287:
1.230 brouard 288: Revision 1.229 2016/07/23 09:45:53 brouard
289: Summary: Completing for func too
290:
1.229 brouard 291: Revision 1.228 2016/07/22 17:45:30 brouard
292: Summary: Fixing some arrays, still debugging
293:
1.227 brouard 294: Revision 1.226 2016/07/12 18:42:34 brouard
295: Summary: temp
296:
1.226 brouard 297: Revision 1.225 2016/07/12 08:40:03 brouard
298: Summary: saving but not running
299:
1.225 brouard 300: Revision 1.224 2016/07/01 13:16:01 brouard
301: Summary: Fixes
302:
1.224 brouard 303: Revision 1.223 2016/02/19 09:23:35 brouard
304: Summary: temporary
305:
1.223 brouard 306: Revision 1.222 2016/02/17 08:14:50 brouard
307: Summary: Probably last 0.98 stable version 0.98r6
308:
1.222 brouard 309: Revision 1.221 2016/02/15 23:35:36 brouard
310: Summary: minor bug
311:
1.220 brouard 312: Revision 1.219 2016/02/15 00:48:12 brouard
313: *** empty log message ***
314:
1.219 brouard 315: Revision 1.218 2016/02/12 11:29:23 brouard
316: Summary: 0.99 Back projections
317:
1.218 brouard 318: Revision 1.217 2015/12/23 17:18:31 brouard
319: Summary: Experimental backcast
320:
1.217 brouard 321: Revision 1.216 2015/12/18 17:32:11 brouard
322: Summary: 0.98r4 Warning and status=-2
323:
324: Version 0.98r4 is now:
325: - displaying an error when status is -1, date of interview unknown and date of death known;
326: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
327: Older changes concerning s=-2, dating from 2005 have been supersed.
328:
1.216 brouard 329: Revision 1.215 2015/12/16 08:52:24 brouard
330: Summary: 0.98r4 working
331:
1.215 brouard 332: Revision 1.214 2015/12/16 06:57:54 brouard
333: Summary: temporary not working
334:
1.214 brouard 335: Revision 1.213 2015/12/11 18:22:17 brouard
336: Summary: 0.98r4
337:
1.213 brouard 338: Revision 1.212 2015/11/21 12:47:24 brouard
339: Summary: minor typo
340:
1.212 brouard 341: Revision 1.211 2015/11/21 12:41:11 brouard
342: Summary: 0.98r3 with some graph of projected cross-sectional
343:
344: Author: Nicolas Brouard
345:
1.211 brouard 346: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 347: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 348: Summary: Adding ftolpl parameter
349: Author: N Brouard
350:
351: We had difficulties to get smoothed confidence intervals. It was due
352: to the period prevalence which wasn't computed accurately. The inner
353: parameter ftolpl is now an outer parameter of the .imach parameter
354: file after estepm. If ftolpl is small 1.e-4 and estepm too,
355: computation are long.
356:
1.209 brouard 357: Revision 1.208 2015/11/17 14:31:57 brouard
358: Summary: temporary
359:
1.208 brouard 360: Revision 1.207 2015/10/27 17:36:57 brouard
361: *** empty log message ***
362:
1.207 brouard 363: Revision 1.206 2015/10/24 07:14:11 brouard
364: *** empty log message ***
365:
1.206 brouard 366: Revision 1.205 2015/10/23 15:50:53 brouard
367: Summary: 0.98r3 some clarification for graphs on likelihood contributions
368:
1.205 brouard 369: Revision 1.204 2015/10/01 16:20:26 brouard
370: Summary: Some new graphs of contribution to likelihood
371:
1.204 brouard 372: Revision 1.203 2015/09/30 17:45:14 brouard
373: Summary: looking at better estimation of the hessian
374:
375: Also a better criteria for convergence to the period prevalence And
376: therefore adding the number of years needed to converge. (The
377: prevalence in any alive state shold sum to one
378:
1.203 brouard 379: Revision 1.202 2015/09/22 19:45:16 brouard
380: Summary: Adding some overall graph on contribution to likelihood. Might change
381:
1.202 brouard 382: Revision 1.201 2015/09/15 17:34:58 brouard
383: Summary: 0.98r0
384:
385: - Some new graphs like suvival functions
386: - Some bugs fixed like model=1+age+V2.
387:
1.201 brouard 388: Revision 1.200 2015/09/09 16:53:55 brouard
389: Summary: Big bug thanks to Flavia
390:
391: Even model=1+age+V2. did not work anymore
392:
1.200 brouard 393: Revision 1.199 2015/09/07 14:09:23 brouard
394: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
395:
1.199 brouard 396: Revision 1.198 2015/09/03 07:14:39 brouard
397: Summary: 0.98q5 Flavia
398:
1.198 brouard 399: Revision 1.197 2015/09/01 18:24:39 brouard
400: *** empty log message ***
401:
1.197 brouard 402: Revision 1.196 2015/08/18 23:17:52 brouard
403: Summary: 0.98q5
404:
1.196 brouard 405: Revision 1.195 2015/08/18 16:28:39 brouard
406: Summary: Adding a hack for testing purpose
407:
408: After reading the title, ftol and model lines, if the comment line has
409: a q, starting with #q, the answer at the end of the run is quit. It
410: permits to run test files in batch with ctest. The former workaround was
411: $ echo q | imach foo.imach
412:
1.195 brouard 413: Revision 1.194 2015/08/18 13:32:00 brouard
414: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
415:
1.194 brouard 416: Revision 1.193 2015/08/04 07:17:42 brouard
417: Summary: 0.98q4
418:
1.193 brouard 419: Revision 1.192 2015/07/16 16:49:02 brouard
420: Summary: Fixing some outputs
421:
1.192 brouard 422: Revision 1.191 2015/07/14 10:00:33 brouard
423: Summary: Some fixes
424:
1.191 brouard 425: Revision 1.190 2015/05/05 08:51:13 brouard
426: Summary: Adding digits in output parameters (7 digits instead of 6)
427:
428: Fix 1+age+.
429:
1.190 brouard 430: Revision 1.189 2015/04/30 14:45:16 brouard
431: Summary: 0.98q2
432:
1.189 brouard 433: Revision 1.188 2015/04/30 08:27:53 brouard
434: *** empty log message ***
435:
1.188 brouard 436: Revision 1.187 2015/04/29 09:11:15 brouard
437: *** empty log message ***
438:
1.187 brouard 439: Revision 1.186 2015/04/23 12:01:52 brouard
440: Summary: V1*age is working now, version 0.98q1
441:
442: Some codes had been disabled in order to simplify and Vn*age was
443: working in the optimization phase, ie, giving correct MLE parameters,
444: but, as usual, outputs were not correct and program core dumped.
445:
1.186 brouard 446: Revision 1.185 2015/03/11 13:26:42 brouard
447: Summary: Inclusion of compile and links command line for Intel Compiler
448:
1.185 brouard 449: Revision 1.184 2015/03/11 11:52:39 brouard
450: Summary: Back from Windows 8. Intel Compiler
451:
1.184 brouard 452: Revision 1.183 2015/03/10 20:34:32 brouard
453: Summary: 0.98q0, trying with directest, mnbrak fixed
454:
455: We use directest instead of original Powell test; probably no
456: incidence on the results, but better justifications;
457: We fixed Numerical Recipes mnbrak routine which was wrong and gave
458: wrong results.
459:
1.183 brouard 460: Revision 1.182 2015/02/12 08:19:57 brouard
461: Summary: Trying to keep directest which seems simpler and more general
462: Author: Nicolas Brouard
463:
1.182 brouard 464: Revision 1.181 2015/02/11 23:22:24 brouard
465: Summary: Comments on Powell added
466:
467: Author:
468:
1.181 brouard 469: Revision 1.180 2015/02/11 17:33:45 brouard
470: Summary: Finishing move from main to function (hpijx and prevalence_limit)
471:
1.180 brouard 472: Revision 1.179 2015/01/04 09:57:06 brouard
473: Summary: back to OS/X
474:
1.179 brouard 475: Revision 1.178 2015/01/04 09:35:48 brouard
476: *** empty log message ***
477:
1.178 brouard 478: Revision 1.177 2015/01/03 18:40:56 brouard
479: Summary: Still testing ilc32 on OSX
480:
1.177 brouard 481: Revision 1.176 2015/01/03 16:45:04 brouard
482: *** empty log message ***
483:
1.176 brouard 484: Revision 1.175 2015/01/03 16:33:42 brouard
485: *** empty log message ***
486:
1.175 brouard 487: Revision 1.174 2015/01/03 16:15:49 brouard
488: Summary: Still in cross-compilation
489:
1.174 brouard 490: Revision 1.173 2015/01/03 12:06:26 brouard
491: Summary: trying to detect cross-compilation
492:
1.173 brouard 493: Revision 1.172 2014/12/27 12:07:47 brouard
494: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
495:
1.172 brouard 496: Revision 1.171 2014/12/23 13:26:59 brouard
497: Summary: Back from Visual C
498:
499: Still problem with utsname.h on Windows
500:
1.171 brouard 501: Revision 1.170 2014/12/23 11:17:12 brouard
502: Summary: Cleaning some \%% back to %%
503:
504: The escape was mandatory for a specific compiler (which one?), but too many warnings.
505:
1.170 brouard 506: Revision 1.169 2014/12/22 23:08:31 brouard
507: Summary: 0.98p
508:
509: Outputs some informations on compiler used, OS etc. Testing on different platforms.
510:
1.169 brouard 511: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 512: Summary: update
1.169 brouard 513:
1.168 brouard 514: Revision 1.167 2014/12/22 13:50:56 brouard
515: Summary: Testing uname and compiler version and if compiled 32 or 64
516:
517: Testing on Linux 64
518:
1.167 brouard 519: Revision 1.166 2014/12/22 11:40:47 brouard
520: *** empty log message ***
521:
1.166 brouard 522: Revision 1.165 2014/12/16 11:20:36 brouard
523: Summary: After compiling on Visual C
524:
525: * imach.c (Module): Merging 1.61 to 1.162
526:
1.165 brouard 527: Revision 1.164 2014/12/16 10:52:11 brouard
528: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
529:
530: * imach.c (Module): Merging 1.61 to 1.162
531:
1.164 brouard 532: Revision 1.163 2014/12/16 10:30:11 brouard
533: * imach.c (Module): Merging 1.61 to 1.162
534:
1.163 brouard 535: Revision 1.162 2014/09/25 11:43:39 brouard
536: Summary: temporary backup 0.99!
537:
1.162 brouard 538: Revision 1.1 2014/09/16 11:06:58 brouard
539: Summary: With some code (wrong) for nlopt
540:
541: Author:
542:
543: Revision 1.161 2014/09/15 20:41:41 brouard
544: Summary: Problem with macro SQR on Intel compiler
545:
1.161 brouard 546: Revision 1.160 2014/09/02 09:24:05 brouard
547: *** empty log message ***
548:
1.160 brouard 549: Revision 1.159 2014/09/01 10:34:10 brouard
550: Summary: WIN32
551: Author: Brouard
552:
1.159 brouard 553: Revision 1.158 2014/08/27 17:11:51 brouard
554: *** empty log message ***
555:
1.158 brouard 556: Revision 1.157 2014/08/27 16:26:55 brouard
557: Summary: Preparing windows Visual studio version
558: Author: Brouard
559:
560: In order to compile on Visual studio, time.h is now correct and time_t
561: and tm struct should be used. difftime should be used but sometimes I
562: just make the differences in raw time format (time(&now).
563: Trying to suppress #ifdef LINUX
564: Add xdg-open for __linux in order to open default browser.
565:
1.157 brouard 566: Revision 1.156 2014/08/25 20:10:10 brouard
567: *** empty log message ***
568:
1.156 brouard 569: Revision 1.155 2014/08/25 18:32:34 brouard
570: Summary: New compile, minor changes
571: Author: Brouard
572:
1.155 brouard 573: Revision 1.154 2014/06/20 17:32:08 brouard
574: Summary: Outputs now all graphs of convergence to period prevalence
575:
1.154 brouard 576: Revision 1.153 2014/06/20 16:45:46 brouard
577: Summary: If 3 live state, convergence to period prevalence on same graph
578: Author: Brouard
579:
1.153 brouard 580: Revision 1.152 2014/06/18 17:54:09 brouard
581: Summary: open browser, use gnuplot on same dir than imach if not found in the path
582:
1.152 brouard 583: Revision 1.151 2014/06/18 16:43:30 brouard
584: *** empty log message ***
585:
1.151 brouard 586: Revision 1.150 2014/06/18 16:42:35 brouard
587: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
588: Author: brouard
589:
1.150 brouard 590: Revision 1.149 2014/06/18 15:51:14 brouard
591: Summary: Some fixes in parameter files errors
592: Author: Nicolas Brouard
593:
1.149 brouard 594: Revision 1.148 2014/06/17 17:38:48 brouard
595: Summary: Nothing new
596: Author: Brouard
597:
598: Just a new packaging for OS/X version 0.98nS
599:
1.148 brouard 600: Revision 1.147 2014/06/16 10:33:11 brouard
601: *** empty log message ***
602:
1.147 brouard 603: Revision 1.146 2014/06/16 10:20:28 brouard
604: Summary: Merge
605: Author: Brouard
606:
607: Merge, before building revised version.
608:
1.146 brouard 609: Revision 1.145 2014/06/10 21:23:15 brouard
610: Summary: Debugging with valgrind
611: Author: Nicolas Brouard
612:
613: Lot of changes in order to output the results with some covariates
614: After the Edimburgh REVES conference 2014, it seems mandatory to
615: improve the code.
616: No more memory valgrind error but a lot has to be done in order to
617: continue the work of splitting the code into subroutines.
618: Also, decodemodel has been improved. Tricode is still not
619: optimal. nbcode should be improved. Documentation has been added in
620: the source code.
621:
1.144 brouard 622: Revision 1.143 2014/01/26 09:45:38 brouard
623: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
624:
625: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
626: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
627:
1.143 brouard 628: Revision 1.142 2014/01/26 03:57:36 brouard
629: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
630:
631: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
632:
1.142 brouard 633: Revision 1.141 2014/01/26 02:42:01 brouard
634: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
635:
1.141 brouard 636: Revision 1.140 2011/09/02 10:37:54 brouard
637: Summary: times.h is ok with mingw32 now.
638:
1.140 brouard 639: Revision 1.139 2010/06/14 07:50:17 brouard
640: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
641: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
642:
1.139 brouard 643: Revision 1.138 2010/04/30 18:19:40 brouard
644: *** empty log message ***
645:
1.138 brouard 646: Revision 1.137 2010/04/29 18:11:38 brouard
647: (Module): Checking covariates for more complex models
648: than V1+V2. A lot of change to be done. Unstable.
649:
1.137 brouard 650: Revision 1.136 2010/04/26 20:30:53 brouard
651: (Module): merging some libgsl code. Fixing computation
652: of likelione (using inter/intrapolation if mle = 0) in order to
653: get same likelihood as if mle=1.
654: Some cleaning of code and comments added.
655:
1.136 brouard 656: Revision 1.135 2009/10/29 15:33:14 brouard
657: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
658:
1.135 brouard 659: Revision 1.134 2009/10/29 13:18:53 brouard
660: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
661:
1.134 brouard 662: Revision 1.133 2009/07/06 10:21:25 brouard
663: just nforces
664:
1.133 brouard 665: Revision 1.132 2009/07/06 08:22:05 brouard
666: Many tings
667:
1.132 brouard 668: Revision 1.131 2009/06/20 16:22:47 brouard
669: Some dimensions resccaled
670:
1.131 brouard 671: Revision 1.130 2009/05/26 06:44:34 brouard
672: (Module): Max Covariate is now set to 20 instead of 8. A
673: lot of cleaning with variables initialized to 0. Trying to make
674: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
675:
1.130 brouard 676: Revision 1.129 2007/08/31 13:49:27 lievre
677: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
678:
1.129 lievre 679: Revision 1.128 2006/06/30 13:02:05 brouard
680: (Module): Clarifications on computing e.j
681:
1.128 brouard 682: Revision 1.127 2006/04/28 18:11:50 brouard
683: (Module): Yes the sum of survivors was wrong since
684: imach-114 because nhstepm was no more computed in the age
685: loop. Now we define nhstepma in the age loop.
686: (Module): In order to speed up (in case of numerous covariates) we
687: compute health expectancies (without variances) in a first step
688: and then all the health expectancies with variances or standard
689: deviation (needs data from the Hessian matrices) which slows the
690: computation.
691: In the future we should be able to stop the program is only health
692: expectancies and graph are needed without standard deviations.
693:
1.127 brouard 694: Revision 1.126 2006/04/28 17:23:28 brouard
695: (Module): Yes the sum of survivors was wrong since
696: imach-114 because nhstepm was no more computed in the age
697: loop. Now we define nhstepma in the age loop.
698: Version 0.98h
699:
1.126 brouard 700: Revision 1.125 2006/04/04 15:20:31 lievre
701: Errors in calculation of health expectancies. Age was not initialized.
702: Forecasting file added.
703:
704: Revision 1.124 2006/03/22 17:13:53 lievre
705: Parameters are printed with %lf instead of %f (more numbers after the comma).
706: The log-likelihood is printed in the log file
707:
708: Revision 1.123 2006/03/20 10:52:43 brouard
709: * imach.c (Module): <title> changed, corresponds to .htm file
710: name. <head> headers where missing.
711:
712: * imach.c (Module): Weights can have a decimal point as for
713: English (a comma might work with a correct LC_NUMERIC environment,
714: otherwise the weight is truncated).
715: Modification of warning when the covariates values are not 0 or
716: 1.
717: Version 0.98g
718:
719: Revision 1.122 2006/03/20 09:45:41 brouard
720: (Module): Weights can have a decimal point as for
721: English (a comma might work with a correct LC_NUMERIC environment,
722: otherwise the weight is truncated).
723: Modification of warning when the covariates values are not 0 or
724: 1.
725: Version 0.98g
726:
727: Revision 1.121 2006/03/16 17:45:01 lievre
728: * imach.c (Module): Comments concerning covariates added
729:
730: * imach.c (Module): refinements in the computation of lli if
731: status=-2 in order to have more reliable computation if stepm is
732: not 1 month. Version 0.98f
733:
734: Revision 1.120 2006/03/16 15:10:38 lievre
735: (Module): refinements in the computation of lli if
736: status=-2 in order to have more reliable computation if stepm is
737: not 1 month. Version 0.98f
738:
739: Revision 1.119 2006/03/15 17:42:26 brouard
740: (Module): Bug if status = -2, the loglikelihood was
741: computed as likelihood omitting the logarithm. Version O.98e
742:
743: Revision 1.118 2006/03/14 18:20:07 brouard
744: (Module): varevsij Comments added explaining the second
745: table of variances if popbased=1 .
746: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
747: (Module): Function pstamp added
748: (Module): Version 0.98d
749:
750: Revision 1.117 2006/03/14 17:16:22 brouard
751: (Module): varevsij Comments added explaining the second
752: table of variances if popbased=1 .
753: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
754: (Module): Function pstamp added
755: (Module): Version 0.98d
756:
757: Revision 1.116 2006/03/06 10:29:27 brouard
758: (Module): Variance-covariance wrong links and
759: varian-covariance of ej. is needed (Saito).
760:
761: Revision 1.115 2006/02/27 12:17:45 brouard
762: (Module): One freematrix added in mlikeli! 0.98c
763:
764: Revision 1.114 2006/02/26 12:57:58 brouard
765: (Module): Some improvements in processing parameter
766: filename with strsep.
767:
768: Revision 1.113 2006/02/24 14:20:24 brouard
769: (Module): Memory leaks checks with valgrind and:
770: datafile was not closed, some imatrix were not freed and on matrix
771: allocation too.
772:
773: Revision 1.112 2006/01/30 09:55:26 brouard
774: (Module): Back to gnuplot.exe instead of wgnuplot.exe
775:
776: Revision 1.111 2006/01/25 20:38:18 brouard
777: (Module): Lots of cleaning and bugs added (Gompertz)
778: (Module): Comments can be added in data file. Missing date values
779: can be a simple dot '.'.
780:
781: Revision 1.110 2006/01/25 00:51:50 brouard
782: (Module): Lots of cleaning and bugs added (Gompertz)
783:
784: Revision 1.109 2006/01/24 19:37:15 brouard
785: (Module): Comments (lines starting with a #) are allowed in data.
786:
787: Revision 1.108 2006/01/19 18:05:42 lievre
788: Gnuplot problem appeared...
789: To be fixed
790:
791: Revision 1.107 2006/01/19 16:20:37 brouard
792: Test existence of gnuplot in imach path
793:
794: Revision 1.106 2006/01/19 13:24:36 brouard
795: Some cleaning and links added in html output
796:
797: Revision 1.105 2006/01/05 20:23:19 lievre
798: *** empty log message ***
799:
800: Revision 1.104 2005/09/30 16:11:43 lievre
801: (Module): sump fixed, loop imx fixed, and simplifications.
802: (Module): If the status is missing at the last wave but we know
803: that the person is alive, then we can code his/her status as -2
804: (instead of missing=-1 in earlier versions) and his/her
805: contributions to the likelihood is 1 - Prob of dying from last
806: health status (= 1-p13= p11+p12 in the easiest case of somebody in
807: the healthy state at last known wave). Version is 0.98
808:
809: Revision 1.103 2005/09/30 15:54:49 lievre
810: (Module): sump fixed, loop imx fixed, and simplifications.
811:
812: Revision 1.102 2004/09/15 17:31:30 brouard
813: Add the possibility to read data file including tab characters.
814:
815: Revision 1.101 2004/09/15 10:38:38 brouard
816: Fix on curr_time
817:
818: Revision 1.100 2004/07/12 18:29:06 brouard
819: Add version for Mac OS X. Just define UNIX in Makefile
820:
821: Revision 1.99 2004/06/05 08:57:40 brouard
822: *** empty log message ***
823:
824: Revision 1.98 2004/05/16 15:05:56 brouard
825: New version 0.97 . First attempt to estimate force of mortality
826: directly from the data i.e. without the need of knowing the health
827: state at each age, but using a Gompertz model: log u =a + b*age .
828: This is the basic analysis of mortality and should be done before any
829: other analysis, in order to test if the mortality estimated from the
830: cross-longitudinal survey is different from the mortality estimated
831: from other sources like vital statistic data.
832:
833: The same imach parameter file can be used but the option for mle should be -3.
834:
1.133 brouard 835: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 836: former routines in order to include the new code within the former code.
837:
838: The output is very simple: only an estimate of the intercept and of
839: the slope with 95% confident intervals.
840:
841: Current limitations:
842: A) Even if you enter covariates, i.e. with the
843: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
844: B) There is no computation of Life Expectancy nor Life Table.
845:
846: Revision 1.97 2004/02/20 13:25:42 lievre
847: Version 0.96d. Population forecasting command line is (temporarily)
848: suppressed.
849:
850: Revision 1.96 2003/07/15 15:38:55 brouard
851: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
852: rewritten within the same printf. Workaround: many printfs.
853:
854: Revision 1.95 2003/07/08 07:54:34 brouard
855: * imach.c (Repository):
856: (Repository): Using imachwizard code to output a more meaningful covariance
857: matrix (cov(a12,c31) instead of numbers.
858:
859: Revision 1.94 2003/06/27 13:00:02 brouard
860: Just cleaning
861:
862: Revision 1.93 2003/06/25 16:33:55 brouard
863: (Module): On windows (cygwin) function asctime_r doesn't
864: exist so I changed back to asctime which exists.
865: (Module): Version 0.96b
866:
867: Revision 1.92 2003/06/25 16:30:45 brouard
868: (Module): On windows (cygwin) function asctime_r doesn't
869: exist so I changed back to asctime which exists.
870:
871: Revision 1.91 2003/06/25 15:30:29 brouard
872: * imach.c (Repository): Duplicated warning errors corrected.
873: (Repository): Elapsed time after each iteration is now output. It
874: helps to forecast when convergence will be reached. Elapsed time
875: is stamped in powell. We created a new html file for the graphs
876: concerning matrix of covariance. It has extension -cov.htm.
877:
878: Revision 1.90 2003/06/24 12:34:15 brouard
879: (Module): Some bugs corrected for windows. Also, when
880: mle=-1 a template is output in file "or"mypar.txt with the design
881: of the covariance matrix to be input.
882:
883: Revision 1.89 2003/06/24 12:30:52 brouard
884: (Module): Some bugs corrected for windows. Also, when
885: mle=-1 a template is output in file "or"mypar.txt with the design
886: of the covariance matrix to be input.
887:
888: Revision 1.88 2003/06/23 17:54:56 brouard
889: * 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.
890:
891: Revision 1.87 2003/06/18 12:26:01 brouard
892: Version 0.96
893:
894: Revision 1.86 2003/06/17 20:04:08 brouard
895: (Module): Change position of html and gnuplot routines and added
896: routine fileappend.
897:
898: Revision 1.85 2003/06/17 13:12:43 brouard
899: * imach.c (Repository): Check when date of death was earlier that
900: current date of interview. It may happen when the death was just
901: prior to the death. In this case, dh was negative and likelihood
902: was wrong (infinity). We still send an "Error" but patch by
903: assuming that the date of death was just one stepm after the
904: interview.
905: (Repository): Because some people have very long ID (first column)
906: we changed int to long in num[] and we added a new lvector for
907: memory allocation. But we also truncated to 8 characters (left
908: truncation)
909: (Repository): No more line truncation errors.
910:
911: Revision 1.84 2003/06/13 21:44:43 brouard
912: * imach.c (Repository): Replace "freqsummary" at a correct
913: place. It differs from routine "prevalence" which may be called
914: many times. Probs is memory consuming and must be used with
915: parcimony.
916: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
917:
918: Revision 1.83 2003/06/10 13:39:11 lievre
919: *** empty log message ***
920:
921: Revision 1.82 2003/06/05 15:57:20 brouard
922: Add log in imach.c and fullversion number is now printed.
923:
924: */
925: /*
926: Interpolated Markov Chain
927:
928: Short summary of the programme:
929:
1.227 brouard 930: This program computes Healthy Life Expectancies or State-specific
931: (if states aren't health statuses) Expectancies from
932: cross-longitudinal data. Cross-longitudinal data consist in:
933:
934: -1- a first survey ("cross") where individuals from different ages
935: are interviewed on their health status or degree of disability (in
936: the case of a health survey which is our main interest)
937:
938: -2- at least a second wave of interviews ("longitudinal") which
939: measure each change (if any) in individual health status. Health
940: expectancies are computed from the time spent in each health state
941: according to a model. More health states you consider, more time is
942: necessary to reach the Maximum Likelihood of the parameters involved
943: in the model. The simplest model is the multinomial logistic model
944: where pij is the probability to be observed in state j at the second
945: wave conditional to be observed in state i at the first
946: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
947: etc , where 'age' is age and 'sex' is a covariate. If you want to
948: have a more complex model than "constant and age", you should modify
949: the program where the markup *Covariates have to be included here
950: again* invites you to do it. More covariates you add, slower the
1.126 brouard 951: convergence.
952:
953: The advantage of this computer programme, compared to a simple
954: multinomial logistic model, is clear when the delay between waves is not
955: identical for each individual. Also, if a individual missed an
956: intermediate interview, the information is lost, but taken into
957: account using an interpolation or extrapolation.
958:
959: hPijx is the probability to be observed in state i at age x+h
960: conditional to the observed state i at age x. The delay 'h' can be
961: split into an exact number (nh*stepm) of unobserved intermediate
962: states. This elementary transition (by month, quarter,
963: semester or year) is modelled as a multinomial logistic. The hPx
964: matrix is simply the matrix product of nh*stepm elementary matrices
965: and the contribution of each individual to the likelihood is simply
966: hPijx.
967:
968: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 969: of the life expectancies. It also computes the period (stable) prevalence.
970:
971: Back prevalence and projections:
1.227 brouard 972:
973: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
974: double agemaxpar, double ftolpl, int *ncvyearp, double
975: dateprev1,double dateprev2, int firstpass, int lastpass, int
976: mobilavproj)
977:
978: Computes the back prevalence limit for any combination of
979: covariate values k at any age between ageminpar and agemaxpar and
980: returns it in **bprlim. In the loops,
981:
982: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
983: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
984:
985: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 986: Computes for any combination of covariates k and any age between bage and fage
987: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
988: oldm=oldms;savm=savms;
1.227 brouard 989:
1.267 brouard 990: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 991: Computes the transition matrix starting at age 'age' over
992: 'nhstepm*hstepm*stepm' months (i.e. until
993: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 994: nhstepm*hstepm matrices.
995:
996: Returns p3mat[i][j][h] after calling
997: p3mat[i][j][h]=matprod2(newm,
998: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
999: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1000: oldm);
1.226 brouard 1001:
1002: Important routines
1003:
1004: - func (or funcone), computes logit (pij) distinguishing
1005: o fixed variables (single or product dummies or quantitative);
1006: o varying variables by:
1007: (1) wave (single, product dummies, quantitative),
1008: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1009: % fixed dummy (treated) or quantitative (not done because time-consuming);
1010: % varying dummy (not done) or quantitative (not done);
1011: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1012: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1013: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1014: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1015: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1016:
1.226 brouard 1017:
1018:
1.133 brouard 1019: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1020: Institut national d'études démographiques, Paris.
1.126 brouard 1021: This software have been partly granted by Euro-REVES, a concerted action
1022: from the European Union.
1023: It is copyrighted identically to a GNU software product, ie programme and
1024: software can be distributed freely for non commercial use. Latest version
1025: can be accessed at http://euroreves.ined.fr/imach .
1026:
1027: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1028: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1029:
1030: **********************************************************************/
1031: /*
1032: main
1033: read parameterfile
1034: read datafile
1035: concatwav
1036: freqsummary
1037: if (mle >= 1)
1038: mlikeli
1039: print results files
1040: if mle==1
1041: computes hessian
1042: read end of parameter file: agemin, agemax, bage, fage, estepm
1043: begin-prev-date,...
1044: open gnuplot file
1045: open html file
1.145 brouard 1046: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1047: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1048: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1049: freexexit2 possible for memory heap.
1050:
1051: h Pij x | pij_nom ficrestpij
1052: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1053: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1054: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1055:
1056: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1057: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1058: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1059: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1060: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1061:
1.126 brouard 1062: forecasting if prevfcast==1 prevforecast call prevalence()
1063: health expectancies
1064: Variance-covariance of DFLE
1065: prevalence()
1066: movingaverage()
1067: varevsij()
1068: if popbased==1 varevsij(,popbased)
1069: total life expectancies
1070: Variance of period (stable) prevalence
1071: end
1072: */
1073:
1.187 brouard 1074: /* #define DEBUG */
1075: /* #define DEBUGBRENT */
1.203 brouard 1076: /* #define DEBUGLINMIN */
1077: /* #define DEBUGHESS */
1078: #define DEBUGHESSIJ
1.224 brouard 1079: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1080: #define POWELL /* Instead of NLOPT */
1.224 brouard 1081: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1082: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1083: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 1084:
1085: #include <math.h>
1086: #include <stdio.h>
1087: #include <stdlib.h>
1088: #include <string.h>
1.226 brouard 1089: #include <ctype.h>
1.159 brouard 1090:
1091: #ifdef _WIN32
1092: #include <io.h>
1.172 brouard 1093: #include <windows.h>
1094: #include <tchar.h>
1.159 brouard 1095: #else
1.126 brouard 1096: #include <unistd.h>
1.159 brouard 1097: #endif
1.126 brouard 1098:
1099: #include <limits.h>
1100: #include <sys/types.h>
1.171 brouard 1101:
1102: #if defined(__GNUC__)
1103: #include <sys/utsname.h> /* Doesn't work on Windows */
1104: #endif
1105:
1.126 brouard 1106: #include <sys/stat.h>
1107: #include <errno.h>
1.159 brouard 1108: /* extern int errno; */
1.126 brouard 1109:
1.157 brouard 1110: /* #ifdef LINUX */
1111: /* #include <time.h> */
1112: /* #include "timeval.h" */
1113: /* #else */
1114: /* #include <sys/time.h> */
1115: /* #endif */
1116:
1.126 brouard 1117: #include <time.h>
1118:
1.136 brouard 1119: #ifdef GSL
1120: #include <gsl/gsl_errno.h>
1121: #include <gsl/gsl_multimin.h>
1122: #endif
1123:
1.167 brouard 1124:
1.162 brouard 1125: #ifdef NLOPT
1126: #include <nlopt.h>
1127: typedef struct {
1128: double (* function)(double [] );
1129: } myfunc_data ;
1130: #endif
1131:
1.126 brouard 1132: /* #include <libintl.h> */
1133: /* #define _(String) gettext (String) */
1134:
1.251 brouard 1135: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1136:
1137: #define GNUPLOTPROGRAM "gnuplot"
1138: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1139: #define FILENAMELENGTH 132
1140:
1141: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1142: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1143:
1.144 brouard 1144: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1145: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1146:
1147: #define NINTERVMAX 8
1.144 brouard 1148: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1149: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.291 brouard 1150: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 1151: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1152: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1153: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1154: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1155: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1156: /* #define AGESUP 130 */
1.288 brouard 1157: /* #define AGESUP 150 */
1158: #define AGESUP 200
1.268 brouard 1159: #define AGEINF 0
1.218 brouard 1160: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1161: #define AGEBASE 40
1.194 brouard 1162: #define AGEOVERFLOW 1.e20
1.164 brouard 1163: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1164: #ifdef _WIN32
1165: #define DIRSEPARATOR '\\'
1166: #define CHARSEPARATOR "\\"
1167: #define ODIRSEPARATOR '/'
1168: #else
1.126 brouard 1169: #define DIRSEPARATOR '/'
1170: #define CHARSEPARATOR "/"
1171: #define ODIRSEPARATOR '\\'
1172: #endif
1173:
1.313 ! brouard 1174: /* $Id: imach.c,v 1.312 2022/04/05 21:24:39 brouard Exp $ */
1.126 brouard 1175: /* $State: Exp $ */
1.196 brouard 1176: #include "version.h"
1177: char version[]=__IMACH_VERSION__;
1.308 brouard 1178: char copyright[]="March 2021,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, INED 2000-2021";
1.313 ! brouard 1179: char fullversion[]="$Revision: 1.312 $ $Date: 2022/04/05 21:24:39 $";
1.126 brouard 1180: char strstart[80];
1181: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1182: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1183: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1184: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1185: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1186: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1187: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1188: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1189: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1190: int cptcovprodnoage=0; /**< Number of covariate products without age */
1191: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1192: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1193: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1194: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1195: int nsd=0; /**< Total number of single dummy variables (output) */
1196: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1197: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1198: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1199: int ntveff=0; /**< ntveff number of effective time varying variables */
1200: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1201: int cptcov=0; /* Working variable */
1.290 brouard 1202: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1203: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1204: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1205: int nlstate=2; /* Number of live states */
1206: int ndeath=1; /* Number of dead states */
1.130 brouard 1207: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1208: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1209: int popbased=0;
1210:
1211: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1212: int maxwav=0; /* Maxim number of waves */
1213: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1214: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1215: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1216: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1217: int mle=1, weightopt=0;
1.126 brouard 1218: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1219: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1220: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1221: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1222: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1223: int selected(int kvar); /* Is covariate kvar selected for printing results */
1224:
1.130 brouard 1225: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1226: double **matprod2(); /* test */
1.126 brouard 1227: double **oldm, **newm, **savm; /* Working pointers to matrices */
1228: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1229: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1230:
1.136 brouard 1231: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1232: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1233: FILE *ficlog, *ficrespow;
1.130 brouard 1234: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1235: double fretone; /* Only one call to likelihood */
1.130 brouard 1236: long ipmx=0; /* Number of contributions */
1.126 brouard 1237: double sw; /* Sum of weights */
1238: char filerespow[FILENAMELENGTH];
1239: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1240: FILE *ficresilk;
1241: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1242: FILE *ficresprobmorprev;
1243: FILE *fichtm, *fichtmcov; /* Html File */
1244: FILE *ficreseij;
1245: char filerese[FILENAMELENGTH];
1246: FILE *ficresstdeij;
1247: char fileresstde[FILENAMELENGTH];
1248: FILE *ficrescveij;
1249: char filerescve[FILENAMELENGTH];
1250: FILE *ficresvij;
1251: char fileresv[FILENAMELENGTH];
1.269 brouard 1252:
1.126 brouard 1253: char title[MAXLINE];
1.234 brouard 1254: char model[MAXLINE]; /**< The model line */
1.217 brouard 1255: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1256: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1257: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1258: char command[FILENAMELENGTH];
1259: int outcmd=0;
1260:
1.217 brouard 1261: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1262: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1263: char filelog[FILENAMELENGTH]; /* Log file */
1264: char filerest[FILENAMELENGTH];
1265: char fileregp[FILENAMELENGTH];
1266: char popfile[FILENAMELENGTH];
1267:
1268: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1269:
1.157 brouard 1270: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1271: /* struct timezone tzp; */
1272: /* extern int gettimeofday(); */
1273: struct tm tml, *gmtime(), *localtime();
1274:
1275: extern time_t time();
1276:
1277: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1278: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1279: struct tm tm;
1280:
1.126 brouard 1281: char strcurr[80], strfor[80];
1282:
1283: char *endptr;
1284: long lval;
1285: double dval;
1286:
1287: #define NR_END 1
1288: #define FREE_ARG char*
1289: #define FTOL 1.0e-10
1290:
1291: #define NRANSI
1.240 brouard 1292: #define ITMAX 200
1293: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1294:
1295: #define TOL 2.0e-4
1296:
1297: #define CGOLD 0.3819660
1298: #define ZEPS 1.0e-10
1299: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1300:
1301: #define GOLD 1.618034
1302: #define GLIMIT 100.0
1303: #define TINY 1.0e-20
1304:
1305: static double maxarg1,maxarg2;
1306: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1307: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1308:
1309: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1310: #define rint(a) floor(a+0.5)
1.166 brouard 1311: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1312: #define mytinydouble 1.0e-16
1.166 brouard 1313: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1314: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1315: /* static double dsqrarg; */
1316: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1317: static double sqrarg;
1318: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1319: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1320: int agegomp= AGEGOMP;
1321:
1322: int imx;
1323: int stepm=1;
1324: /* Stepm, step in month: minimum step interpolation*/
1325:
1326: int estepm;
1327: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1328:
1329: int m,nb;
1330: long *num;
1.197 brouard 1331: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1332: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1333: covariate for which somebody answered excluding
1334: undefined. Usually 2: 0 and 1. */
1335: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1336: covariate for which somebody answered including
1337: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1338: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1339: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1340: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1341: double *ageexmed,*agecens;
1342: double dateintmean=0;
1.296 brouard 1343: double anprojd, mprojd, jprojd; /* For eventual projections */
1344: double anprojf, mprojf, jprojf;
1.126 brouard 1345:
1.296 brouard 1346: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1347: double anbackf, mbackf, jbackf;
1348: double jintmean,mintmean,aintmean;
1.126 brouard 1349: double *weight;
1350: int **s; /* Status */
1.141 brouard 1351: double *agedc;
1.145 brouard 1352: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1353: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1354: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1355: double **coqvar; /* Fixed quantitative covariate nqv */
1356: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1357: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1358: double idx;
1359: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1360: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1361: /*k 1 2 3 4 5 6 7 8 9 */
1362: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1363: /* Tndvar[k] 1 2 3 4 5 */
1364: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1365: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1366: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1367: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1368: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1369: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1370: /* Tprod[i]=k 4 7 */
1371: /* Tage[i]=k 5 8 */
1372: /* */
1373: /* Type */
1374: /* V 1 2 3 4 5 */
1375: /* F F V V V */
1376: /* D Q D D Q */
1377: /* */
1378: int *TvarsD;
1379: int *TvarsDind;
1380: int *TvarsQ;
1381: int *TvarsQind;
1382:
1.235 brouard 1383: #define MAXRESULTLINES 10
1384: int nresult=0;
1.258 brouard 1385: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1386: int TKresult[MAXRESULTLINES];
1.237 brouard 1387: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1388: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1389: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1390: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1391: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1392: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1393:
1.234 brouard 1394: /* 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 1395: 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 */
1396: 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 */
1397: 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 */
1398: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1399: 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 */
1400: 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 1401: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1402: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1403: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1404: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1405: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1406: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1407: 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 */
1408: 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 */
1409:
1.230 brouard 1410: int *Tvarsel; /**< Selected covariates for output */
1411: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1412: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1413: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1414: 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 1415: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1416: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1417: int *Tage;
1.227 brouard 1418: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1419: 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 1420: 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*/
1421: 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 1422: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1423: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1424: int **Tvard;
1425: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1426: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1427: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1428: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1429: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1430: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1431: double *lsurv, *lpop, *tpop;
1432:
1.231 brouard 1433: #define FD 1; /* Fixed dummy covariate */
1434: #define FQ 2; /* Fixed quantitative covariate */
1435: #define FP 3; /* Fixed product covariate */
1436: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1437: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1438: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1439: #define VD 10; /* Varying dummy covariate */
1440: #define VQ 11; /* Varying quantitative covariate */
1441: #define VP 12; /* Varying product covariate */
1442: #define VPDD 13; /* Varying product dummy*dummy covariate */
1443: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1444: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1445: #define APFD 16; /* Age product * fixed dummy covariate */
1446: #define APFQ 17; /* Age product * fixed quantitative covariate */
1447: #define APVD 18; /* Age product * varying dummy covariate */
1448: #define APVQ 19; /* Age product * varying quantitative covariate */
1449:
1450: #define FTYPE 1; /* Fixed covariate */
1451: #define VTYPE 2; /* Varying covariate (loop in wave) */
1452: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1453:
1454: struct kmodel{
1455: int maintype; /* main type */
1456: int subtype; /* subtype */
1457: };
1458: struct kmodel modell[NCOVMAX];
1459:
1.143 brouard 1460: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1461: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1462:
1463: /**************** split *************************/
1464: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1465: {
1466: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1467: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1468: */
1469: char *ss; /* pointer */
1.186 brouard 1470: int l1=0, l2=0; /* length counters */
1.126 brouard 1471:
1472: l1 = strlen(path ); /* length of path */
1473: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1474: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1475: if ( ss == NULL ) { /* no directory, so determine current directory */
1476: strcpy( name, path ); /* we got the fullname name because no directory */
1477: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1478: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1479: /* get current working directory */
1480: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1481: #ifdef WIN32
1482: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1483: #else
1484: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1485: #endif
1.126 brouard 1486: return( GLOCK_ERROR_GETCWD );
1487: }
1488: /* got dirc from getcwd*/
1489: printf(" DIRC = %s \n",dirc);
1.205 brouard 1490: } else { /* strip directory from path */
1.126 brouard 1491: ss++; /* after this, the filename */
1492: l2 = strlen( ss ); /* length of filename */
1493: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1494: strcpy( name, ss ); /* save file name */
1495: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1496: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1497: printf(" DIRC2 = %s \n",dirc);
1498: }
1499: /* We add a separator at the end of dirc if not exists */
1500: l1 = strlen( dirc ); /* length of directory */
1501: if( dirc[l1-1] != DIRSEPARATOR ){
1502: dirc[l1] = DIRSEPARATOR;
1503: dirc[l1+1] = 0;
1504: printf(" DIRC3 = %s \n",dirc);
1505: }
1506: ss = strrchr( name, '.' ); /* find last / */
1507: if (ss >0){
1508: ss++;
1509: strcpy(ext,ss); /* save extension */
1510: l1= strlen( name);
1511: l2= strlen(ss)+1;
1512: strncpy( finame, name, l1-l2);
1513: finame[l1-l2]= 0;
1514: }
1515:
1516: return( 0 ); /* we're done */
1517: }
1518:
1519:
1520: /******************************************/
1521:
1522: void replace_back_to_slash(char *s, char*t)
1523: {
1524: int i;
1525: int lg=0;
1526: i=0;
1527: lg=strlen(t);
1528: for(i=0; i<= lg; i++) {
1529: (s[i] = t[i]);
1530: if (t[i]== '\\') s[i]='/';
1531: }
1532: }
1533:
1.132 brouard 1534: char *trimbb(char *out, char *in)
1.137 brouard 1535: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1536: char *s;
1537: s=out;
1538: while (*in != '\0'){
1.137 brouard 1539: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1540: in++;
1541: }
1542: *out++ = *in++;
1543: }
1544: *out='\0';
1545: return s;
1546: }
1547:
1.187 brouard 1548: /* char *substrchaine(char *out, char *in, char *chain) */
1549: /* { */
1550: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1551: /* char *s, *t; */
1552: /* t=in;s=out; */
1553: /* while ((*in != *chain) && (*in != '\0')){ */
1554: /* *out++ = *in++; */
1555: /* } */
1556:
1557: /* /\* *in matches *chain *\/ */
1558: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1559: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1560: /* } */
1561: /* in--; chain--; */
1562: /* while ( (*in != '\0')){ */
1563: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1564: /* *out++ = *in++; */
1565: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1566: /* } */
1567: /* *out='\0'; */
1568: /* out=s; */
1569: /* return out; */
1570: /* } */
1571: char *substrchaine(char *out, char *in, char *chain)
1572: {
1573: /* Substract chain 'chain' from 'in', return and output 'out' */
1574: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1575:
1576: char *strloc;
1577:
1578: strcpy (out, in);
1579: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1580: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1581: if(strloc != NULL){
1582: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1583: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1584: /* strcpy (strloc, strloc +strlen(chain));*/
1585: }
1586: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1587: return out;
1588: }
1589:
1590:
1.145 brouard 1591: char *cutl(char *blocc, char *alocc, char *in, char occ)
1592: {
1.187 brouard 1593: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1594: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1595: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1596: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1597: */
1.160 brouard 1598: char *s, *t;
1.145 brouard 1599: t=in;s=in;
1600: while ((*in != occ) && (*in != '\0')){
1601: *alocc++ = *in++;
1602: }
1603: if( *in == occ){
1604: *(alocc)='\0';
1605: s=++in;
1606: }
1607:
1608: if (s == t) {/* occ not found */
1609: *(alocc-(in-s))='\0';
1610: in=s;
1611: }
1612: while ( *in != '\0'){
1613: *blocc++ = *in++;
1614: }
1615:
1616: *blocc='\0';
1617: return t;
1618: }
1.137 brouard 1619: char *cutv(char *blocc, char *alocc, char *in, char occ)
1620: {
1.187 brouard 1621: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1622: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1623: gives blocc="abcdef2ghi" and alocc="j".
1624: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1625: */
1626: char *s, *t;
1627: t=in;s=in;
1628: while (*in != '\0'){
1629: while( *in == occ){
1630: *blocc++ = *in++;
1631: s=in;
1632: }
1633: *blocc++ = *in++;
1634: }
1635: if (s == t) /* occ not found */
1636: *(blocc-(in-s))='\0';
1637: else
1638: *(blocc-(in-s)-1)='\0';
1639: in=s;
1640: while ( *in != '\0'){
1641: *alocc++ = *in++;
1642: }
1643:
1644: *alocc='\0';
1645: return s;
1646: }
1647:
1.126 brouard 1648: int nbocc(char *s, char occ)
1649: {
1650: int i,j=0;
1651: int lg=20;
1652: i=0;
1653: lg=strlen(s);
1654: for(i=0; i<= lg; i++) {
1.234 brouard 1655: if (s[i] == occ ) j++;
1.126 brouard 1656: }
1657: return j;
1658: }
1659:
1.137 brouard 1660: /* void cutv(char *u,char *v, char*t, char occ) */
1661: /* { */
1662: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1663: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1664: /* gives u="abcdef2ghi" and v="j" *\/ */
1665: /* int i,lg,j,p=0; */
1666: /* i=0; */
1667: /* lg=strlen(t); */
1668: /* for(j=0; j<=lg-1; j++) { */
1669: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1670: /* } */
1.126 brouard 1671:
1.137 brouard 1672: /* for(j=0; j<p; j++) { */
1673: /* (u[j] = t[j]); */
1674: /* } */
1675: /* u[p]='\0'; */
1.126 brouard 1676:
1.137 brouard 1677: /* for(j=0; j<= lg; j++) { */
1678: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1679: /* } */
1680: /* } */
1.126 brouard 1681:
1.160 brouard 1682: #ifdef _WIN32
1683: char * strsep(char **pp, const char *delim)
1684: {
1685: char *p, *q;
1686:
1687: if ((p = *pp) == NULL)
1688: return 0;
1689: if ((q = strpbrk (p, delim)) != NULL)
1690: {
1691: *pp = q + 1;
1692: *q = '\0';
1693: }
1694: else
1695: *pp = 0;
1696: return p;
1697: }
1698: #endif
1699:
1.126 brouard 1700: /********************** nrerror ********************/
1701:
1702: void nrerror(char error_text[])
1703: {
1704: fprintf(stderr,"ERREUR ...\n");
1705: fprintf(stderr,"%s\n",error_text);
1706: exit(EXIT_FAILURE);
1707: }
1708: /*********************** vector *******************/
1709: double *vector(int nl, int nh)
1710: {
1711: double *v;
1712: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1713: if (!v) nrerror("allocation failure in vector");
1714: return v-nl+NR_END;
1715: }
1716:
1717: /************************ free vector ******************/
1718: void free_vector(double*v, int nl, int nh)
1719: {
1720: free((FREE_ARG)(v+nl-NR_END));
1721: }
1722:
1723: /************************ivector *******************************/
1724: int *ivector(long nl,long nh)
1725: {
1726: int *v;
1727: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1728: if (!v) nrerror("allocation failure in ivector");
1729: return v-nl+NR_END;
1730: }
1731:
1732: /******************free ivector **************************/
1733: void free_ivector(int *v, long nl, long nh)
1734: {
1735: free((FREE_ARG)(v+nl-NR_END));
1736: }
1737:
1738: /************************lvector *******************************/
1739: long *lvector(long nl,long nh)
1740: {
1741: long *v;
1742: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1743: if (!v) nrerror("allocation failure in ivector");
1744: return v-nl+NR_END;
1745: }
1746:
1747: /******************free lvector **************************/
1748: void free_lvector(long *v, long nl, long nh)
1749: {
1750: free((FREE_ARG)(v+nl-NR_END));
1751: }
1752:
1753: /******************* imatrix *******************************/
1754: int **imatrix(long nrl, long nrh, long ncl, long nch)
1755: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1756: {
1757: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1758: int **m;
1759:
1760: /* allocate pointers to rows */
1761: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1762: if (!m) nrerror("allocation failure 1 in matrix()");
1763: m += NR_END;
1764: m -= nrl;
1765:
1766:
1767: /* allocate rows and set pointers to them */
1768: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1769: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1770: m[nrl] += NR_END;
1771: m[nrl] -= ncl;
1772:
1773: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1774:
1775: /* return pointer to array of pointers to rows */
1776: return m;
1777: }
1778:
1779: /****************** free_imatrix *************************/
1780: void free_imatrix(m,nrl,nrh,ncl,nch)
1781: int **m;
1782: long nch,ncl,nrh,nrl;
1783: /* free an int matrix allocated by imatrix() */
1784: {
1785: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1786: free((FREE_ARG) (m+nrl-NR_END));
1787: }
1788:
1789: /******************* matrix *******************************/
1790: double **matrix(long nrl, long nrh, long ncl, long nch)
1791: {
1792: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1793: double **m;
1794:
1795: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1796: if (!m) nrerror("allocation failure 1 in matrix()");
1797: m += NR_END;
1798: m -= nrl;
1799:
1800: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1801: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1802: m[nrl] += NR_END;
1803: m[nrl] -= ncl;
1804:
1805: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1806: return m;
1.145 brouard 1807: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1808: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1809: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1810: */
1811: }
1812:
1813: /*************************free matrix ************************/
1814: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1815: {
1816: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1817: free((FREE_ARG)(m+nrl-NR_END));
1818: }
1819:
1820: /******************* ma3x *******************************/
1821: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1822: {
1823: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1824: double ***m;
1825:
1826: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1827: if (!m) nrerror("allocation failure 1 in matrix()");
1828: m += NR_END;
1829: m -= nrl;
1830:
1831: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1832: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1833: m[nrl] += NR_END;
1834: m[nrl] -= ncl;
1835:
1836: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1837:
1838: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1839: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1840: m[nrl][ncl] += NR_END;
1841: m[nrl][ncl] -= nll;
1842: for (j=ncl+1; j<=nch; j++)
1843: m[nrl][j]=m[nrl][j-1]+nlay;
1844:
1845: for (i=nrl+1; i<=nrh; i++) {
1846: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1847: for (j=ncl+1; j<=nch; j++)
1848: m[i][j]=m[i][j-1]+nlay;
1849: }
1850: return m;
1851: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1852: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1853: */
1854: }
1855:
1856: /*************************free ma3x ************************/
1857: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1858: {
1859: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1860: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1861: free((FREE_ARG)(m+nrl-NR_END));
1862: }
1863:
1864: /*************** function subdirf ***********/
1865: char *subdirf(char fileres[])
1866: {
1867: /* Caution optionfilefiname is hidden */
1868: strcpy(tmpout,optionfilefiname);
1869: strcat(tmpout,"/"); /* Add to the right */
1870: strcat(tmpout,fileres);
1871: return tmpout;
1872: }
1873:
1874: /*************** function subdirf2 ***********/
1875: char *subdirf2(char fileres[], char *preop)
1876: {
1877:
1878: /* Caution optionfilefiname is hidden */
1879: strcpy(tmpout,optionfilefiname);
1880: strcat(tmpout,"/");
1881: strcat(tmpout,preop);
1882: strcat(tmpout,fileres);
1883: return tmpout;
1884: }
1885:
1886: /*************** function subdirf3 ***********/
1887: char *subdirf3(char fileres[], char *preop, char *preop2)
1888: {
1889:
1890: /* Caution optionfilefiname is hidden */
1891: strcpy(tmpout,optionfilefiname);
1892: strcat(tmpout,"/");
1893: strcat(tmpout,preop);
1894: strcat(tmpout,preop2);
1895: strcat(tmpout,fileres);
1896: return tmpout;
1897: }
1.213 brouard 1898:
1899: /*************** function subdirfext ***********/
1900: char *subdirfext(char fileres[], char *preop, char *postop)
1901: {
1902:
1903: strcpy(tmpout,preop);
1904: strcat(tmpout,fileres);
1905: strcat(tmpout,postop);
1906: return tmpout;
1907: }
1.126 brouard 1908:
1.213 brouard 1909: /*************** function subdirfext3 ***********/
1910: char *subdirfext3(char fileres[], char *preop, char *postop)
1911: {
1912:
1913: /* Caution optionfilefiname is hidden */
1914: strcpy(tmpout,optionfilefiname);
1915: strcat(tmpout,"/");
1916: strcat(tmpout,preop);
1917: strcat(tmpout,fileres);
1918: strcat(tmpout,postop);
1919: return tmpout;
1920: }
1921:
1.162 brouard 1922: char *asc_diff_time(long time_sec, char ascdiff[])
1923: {
1924: long sec_left, days, hours, minutes;
1925: days = (time_sec) / (60*60*24);
1926: sec_left = (time_sec) % (60*60*24);
1927: hours = (sec_left) / (60*60) ;
1928: sec_left = (sec_left) %(60*60);
1929: minutes = (sec_left) /60;
1930: sec_left = (sec_left) % (60);
1931: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1932: return ascdiff;
1933: }
1934:
1.126 brouard 1935: /***************** f1dim *************************/
1936: extern int ncom;
1937: extern double *pcom,*xicom;
1938: extern double (*nrfunc)(double []);
1939:
1940: double f1dim(double x)
1941: {
1942: int j;
1943: double f;
1944: double *xt;
1945:
1946: xt=vector(1,ncom);
1947: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1948: f=(*nrfunc)(xt);
1949: free_vector(xt,1,ncom);
1950: return f;
1951: }
1952:
1953: /*****************brent *************************/
1954: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1955: {
1956: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1957: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1958: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1959: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1960: * returned function value.
1961: */
1.126 brouard 1962: int iter;
1963: double a,b,d,etemp;
1.159 brouard 1964: double fu=0,fv,fw,fx;
1.164 brouard 1965: double ftemp=0.;
1.126 brouard 1966: double p,q,r,tol1,tol2,u,v,w,x,xm;
1967: double e=0.0;
1968:
1969: a=(ax < cx ? ax : cx);
1970: b=(ax > cx ? ax : cx);
1971: x=w=v=bx;
1972: fw=fv=fx=(*f)(x);
1973: for (iter=1;iter<=ITMAX;iter++) {
1974: xm=0.5*(a+b);
1975: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1976: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1977: printf(".");fflush(stdout);
1978: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1979: #ifdef DEBUGBRENT
1.126 brouard 1980: 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);
1981: 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);
1982: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1983: #endif
1984: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1985: *xmin=x;
1986: return fx;
1987: }
1988: ftemp=fu;
1989: if (fabs(e) > tol1) {
1990: r=(x-w)*(fx-fv);
1991: q=(x-v)*(fx-fw);
1992: p=(x-v)*q-(x-w)*r;
1993: q=2.0*(q-r);
1994: if (q > 0.0) p = -p;
1995: q=fabs(q);
1996: etemp=e;
1997: e=d;
1998: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1999: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2000: else {
1.224 brouard 2001: d=p/q;
2002: u=x+d;
2003: if (u-a < tol2 || b-u < tol2)
2004: d=SIGN(tol1,xm-x);
1.126 brouard 2005: }
2006: } else {
2007: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2008: }
2009: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2010: fu=(*f)(u);
2011: if (fu <= fx) {
2012: if (u >= x) a=x; else b=x;
2013: SHFT(v,w,x,u)
1.183 brouard 2014: SHFT(fv,fw,fx,fu)
2015: } else {
2016: if (u < x) a=u; else b=u;
2017: if (fu <= fw || w == x) {
1.224 brouard 2018: v=w;
2019: w=u;
2020: fv=fw;
2021: fw=fu;
1.183 brouard 2022: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2023: v=u;
2024: fv=fu;
1.183 brouard 2025: }
2026: }
1.126 brouard 2027: }
2028: nrerror("Too many iterations in brent");
2029: *xmin=x;
2030: return fx;
2031: }
2032:
2033: /****************** mnbrak ***********************/
2034:
2035: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2036: double (*func)(double))
1.183 brouard 2037: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2038: the downhill direction (defined by the function as evaluated at the initial points) and returns
2039: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2040: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2041: */
1.126 brouard 2042: double ulim,u,r,q, dum;
2043: double fu;
1.187 brouard 2044:
2045: double scale=10.;
2046: int iterscale=0;
2047:
2048: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2049: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2050:
2051:
2052: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2053: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2054: /* *bx = *ax - (*ax - *bx)/scale; */
2055: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2056: /* } */
2057:
1.126 brouard 2058: if (*fb > *fa) {
2059: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2060: SHFT(dum,*fb,*fa,dum)
2061: }
1.126 brouard 2062: *cx=(*bx)+GOLD*(*bx-*ax);
2063: *fc=(*func)(*cx);
1.183 brouard 2064: #ifdef DEBUG
1.224 brouard 2065: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2066: 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 2067: #endif
1.224 brouard 2068: 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 2069: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2070: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2071: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2072: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2073: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2074: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2075: fu=(*func)(u);
1.163 brouard 2076: #ifdef DEBUG
2077: /* f(x)=A(x-u)**2+f(u) */
2078: double A, fparabu;
2079: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2080: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2081: 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);
2082: 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 2083: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2084: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2085: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2086: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2087: #endif
1.184 brouard 2088: #ifdef MNBRAKORIGINAL
1.183 brouard 2089: #else
1.191 brouard 2090: /* if (fu > *fc) { */
2091: /* #ifdef DEBUG */
2092: /* printf("mnbrak4 fu > fc \n"); */
2093: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2094: /* #endif */
2095: /* /\* 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 *\\/ *\/ */
2096: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2097: /* dum=u; /\* Shifting c and u *\/ */
2098: /* u = *cx; */
2099: /* *cx = dum; */
2100: /* dum = fu; */
2101: /* fu = *fc; */
2102: /* *fc =dum; */
2103: /* } else { /\* end *\/ */
2104: /* #ifdef DEBUG */
2105: /* printf("mnbrak3 fu < fc \n"); */
2106: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2107: /* #endif */
2108: /* dum=u; /\* Shifting c and u *\/ */
2109: /* u = *cx; */
2110: /* *cx = dum; */
2111: /* dum = fu; */
2112: /* fu = *fc; */
2113: /* *fc =dum; */
2114: /* } */
1.224 brouard 2115: #ifdef DEBUGMNBRAK
2116: double A, fparabu;
2117: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2118: fparabu= *fa - A*(*ax-u)*(*ax-u);
2119: 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);
2120: 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 2121: #endif
1.191 brouard 2122: dum=u; /* Shifting c and u */
2123: u = *cx;
2124: *cx = dum;
2125: dum = fu;
2126: fu = *fc;
2127: *fc =dum;
1.183 brouard 2128: #endif
1.162 brouard 2129: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2130: #ifdef DEBUG
1.224 brouard 2131: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2132: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2133: #endif
1.126 brouard 2134: fu=(*func)(u);
2135: if (fu < *fc) {
1.183 brouard 2136: #ifdef DEBUG
1.224 brouard 2137: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2138: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2139: #endif
2140: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2141: SHFT(*fb,*fc,fu,(*func)(u))
2142: #ifdef DEBUG
2143: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2144: #endif
2145: }
1.162 brouard 2146: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2147: #ifdef DEBUG
1.224 brouard 2148: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2149: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2150: #endif
1.126 brouard 2151: u=ulim;
2152: fu=(*func)(u);
1.183 brouard 2153: } else { /* u could be left to b (if r > q parabola has a maximum) */
2154: #ifdef DEBUG
1.224 brouard 2155: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2156: 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 2157: #endif
1.126 brouard 2158: u=(*cx)+GOLD*(*cx-*bx);
2159: fu=(*func)(u);
1.224 brouard 2160: #ifdef DEBUG
2161: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2162: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2163: #endif
1.183 brouard 2164: } /* end tests */
1.126 brouard 2165: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2166: SHFT(*fa,*fb,*fc,fu)
2167: #ifdef DEBUG
1.224 brouard 2168: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2169: 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 2170: #endif
2171: } /* 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 2172: }
2173:
2174: /*************** linmin ************************/
1.162 brouard 2175: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2176: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2177: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2178: the value of func at the returned location p . This is actually all accomplished by calling the
2179: routines mnbrak and brent .*/
1.126 brouard 2180: int ncom;
2181: double *pcom,*xicom;
2182: double (*nrfunc)(double []);
2183:
1.224 brouard 2184: #ifdef LINMINORIGINAL
1.126 brouard 2185: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2186: #else
2187: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2188: #endif
1.126 brouard 2189: {
2190: double brent(double ax, double bx, double cx,
2191: double (*f)(double), double tol, double *xmin);
2192: double f1dim(double x);
2193: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2194: double *fc, double (*func)(double));
2195: int j;
2196: double xx,xmin,bx,ax;
2197: double fx,fb,fa;
1.187 brouard 2198:
1.203 brouard 2199: #ifdef LINMINORIGINAL
2200: #else
2201: double scale=10., axs, xxs; /* Scale added for infinity */
2202: #endif
2203:
1.126 brouard 2204: ncom=n;
2205: pcom=vector(1,n);
2206: xicom=vector(1,n);
2207: nrfunc=func;
2208: for (j=1;j<=n;j++) {
2209: pcom[j]=p[j];
1.202 brouard 2210: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2211: }
1.187 brouard 2212:
1.203 brouard 2213: #ifdef LINMINORIGINAL
2214: xx=1.;
2215: #else
2216: axs=0.0;
2217: xxs=1.;
2218: do{
2219: xx= xxs;
2220: #endif
1.187 brouard 2221: ax=0.;
2222: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2223: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2224: /* 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)) */
2225: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2226: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2227: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2228: /* 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 2229: #ifdef LINMINORIGINAL
2230: #else
2231: if (fx != fx){
1.224 brouard 2232: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2233: printf("|");
2234: fprintf(ficlog,"|");
1.203 brouard 2235: #ifdef DEBUGLINMIN
1.224 brouard 2236: 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 2237: #endif
2238: }
1.224 brouard 2239: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2240: #endif
2241:
1.191 brouard 2242: #ifdef DEBUGLINMIN
2243: 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 2244: 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 2245: #endif
1.224 brouard 2246: #ifdef LINMINORIGINAL
2247: #else
2248: if(fb == fx){ /* Flat function in the direction */
2249: xmin=xx;
2250: *flat=1;
2251: }else{
2252: *flat=0;
2253: #endif
2254: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2255: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2256: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2257: /* fmin = f(p[j] + xmin * xi[j]) */
2258: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2259: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2260: #ifdef DEBUG
1.224 brouard 2261: 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);
2262: 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);
2263: #endif
2264: #ifdef LINMINORIGINAL
2265: #else
2266: }
1.126 brouard 2267: #endif
1.191 brouard 2268: #ifdef DEBUGLINMIN
2269: printf("linmin end ");
1.202 brouard 2270: fprintf(ficlog,"linmin end ");
1.191 brouard 2271: #endif
1.126 brouard 2272: for (j=1;j<=n;j++) {
1.203 brouard 2273: #ifdef LINMINORIGINAL
2274: xi[j] *= xmin;
2275: #else
2276: #ifdef DEBUGLINMIN
2277: if(xxs <1.0)
2278: printf(" before xi[%d]=%12.8f", j,xi[j]);
2279: #endif
2280: 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) */
2281: #ifdef DEBUGLINMIN
2282: if(xxs <1.0)
2283: 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 );
2284: #endif
2285: #endif
1.187 brouard 2286: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2287: }
1.191 brouard 2288: #ifdef DEBUGLINMIN
1.203 brouard 2289: printf("\n");
1.191 brouard 2290: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2291: 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 2292: for (j=1;j<=n;j++) {
1.202 brouard 2293: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2294: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2295: if(j % ncovmodel == 0){
1.191 brouard 2296: printf("\n");
1.202 brouard 2297: fprintf(ficlog,"\n");
2298: }
1.191 brouard 2299: }
1.203 brouard 2300: #else
1.191 brouard 2301: #endif
1.126 brouard 2302: free_vector(xicom,1,n);
2303: free_vector(pcom,1,n);
2304: }
2305:
2306:
2307: /*************** powell ************************/
1.162 brouard 2308: /*
2309: Minimization of a function func of n variables. Input consists of an initial starting point
2310: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2311: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2312: such that failure to decrease by more than this amount on one iteration signals doneness. On
2313: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2314: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2315: */
1.224 brouard 2316: #ifdef LINMINORIGINAL
2317: #else
2318: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2319: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2320: #endif
1.126 brouard 2321: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2322: double (*func)(double []))
2323: {
1.224 brouard 2324: #ifdef LINMINORIGINAL
2325: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2326: double (*func)(double []));
1.224 brouard 2327: #else
1.241 brouard 2328: void linmin(double p[], double xi[], int n, double *fret,
2329: double (*func)(double []),int *flat);
1.224 brouard 2330: #endif
1.239 brouard 2331: int i,ibig,j,jk,k;
1.126 brouard 2332: double del,t,*pt,*ptt,*xit;
1.181 brouard 2333: double directest;
1.126 brouard 2334: double fp,fptt;
2335: double *xits;
2336: int niterf, itmp;
1.224 brouard 2337: #ifdef LINMINORIGINAL
2338: #else
2339:
2340: flatdir=ivector(1,n);
2341: for (j=1;j<=n;j++) flatdir[j]=0;
2342: #endif
1.126 brouard 2343:
2344: pt=vector(1,n);
2345: ptt=vector(1,n);
2346: xit=vector(1,n);
2347: xits=vector(1,n);
2348: *fret=(*func)(p);
2349: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2350: rcurr_time = time(NULL);
1.126 brouard 2351: for (*iter=1;;++(*iter)) {
1.187 brouard 2352: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2353: ibig=0;
2354: del=0.0;
1.157 brouard 2355: rlast_time=rcurr_time;
2356: /* (void) gettimeofday(&curr_time,&tzp); */
2357: rcurr_time = time(NULL);
2358: curr_time = *localtime(&rcurr_time);
2359: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2360: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2361: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2362: for (i=1;i<=n;i++) {
1.126 brouard 2363: fprintf(ficrespow," %.12lf", p[i]);
2364: }
1.239 brouard 2365: fprintf(ficrespow,"\n");fflush(ficrespow);
2366: printf("\n#model= 1 + age ");
2367: fprintf(ficlog,"\n#model= 1 + age ");
2368: if(nagesqr==1){
1.241 brouard 2369: printf(" + age*age ");
2370: fprintf(ficlog," + age*age ");
1.239 brouard 2371: }
2372: for(j=1;j <=ncovmodel-2;j++){
2373: if(Typevar[j]==0) {
2374: printf(" + V%d ",Tvar[j]);
2375: fprintf(ficlog," + V%d ",Tvar[j]);
2376: }else if(Typevar[j]==1) {
2377: printf(" + V%d*age ",Tvar[j]);
2378: fprintf(ficlog," + V%d*age ",Tvar[j]);
2379: }else if(Typevar[j]==2) {
2380: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2381: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2382: }
2383: }
1.126 brouard 2384: printf("\n");
1.239 brouard 2385: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2386: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2387: fprintf(ficlog,"\n");
1.239 brouard 2388: for(i=1,jk=1; i <=nlstate; i++){
2389: for(k=1; k <=(nlstate+ndeath); k++){
2390: if (k != i) {
2391: printf("%d%d ",i,k);
2392: fprintf(ficlog,"%d%d ",i,k);
2393: for(j=1; j <=ncovmodel; j++){
2394: printf("%12.7f ",p[jk]);
2395: fprintf(ficlog,"%12.7f ",p[jk]);
2396: jk++;
2397: }
2398: printf("\n");
2399: fprintf(ficlog,"\n");
2400: }
2401: }
2402: }
1.241 brouard 2403: if(*iter <=3 && *iter >1){
1.157 brouard 2404: tml = *localtime(&rcurr_time);
2405: strcpy(strcurr,asctime(&tml));
2406: rforecast_time=rcurr_time;
1.126 brouard 2407: itmp = strlen(strcurr);
2408: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2409: strcurr[itmp-1]='\0';
1.162 brouard 2410: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2411: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2412: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2413: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2414: forecast_time = *localtime(&rforecast_time);
2415: strcpy(strfor,asctime(&forecast_time));
2416: itmp = strlen(strfor);
2417: if(strfor[itmp-1]=='\n')
2418: strfor[itmp-1]='\0';
2419: 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);
2420: 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 2421: }
2422: }
1.187 brouard 2423: for (i=1;i<=n;i++) { /* For each direction i */
2424: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2425: fptt=(*fret);
2426: #ifdef DEBUG
1.203 brouard 2427: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2428: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2429: #endif
1.203 brouard 2430: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2431: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2432: #ifdef LINMINORIGINAL
1.188 brouard 2433: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2434: #else
2435: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2436: flatdir[i]=flat; /* Function is vanishing in that direction i */
2437: #endif
2438: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2439: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2440: /* because that direction will be replaced unless the gain del is small */
2441: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2442: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2443: /* with the new direction. */
2444: del=fabs(fptt-(*fret));
2445: ibig=i;
1.126 brouard 2446: }
2447: #ifdef DEBUG
2448: printf("%d %.12e",i,(*fret));
2449: fprintf(ficlog,"%d %.12e",i,(*fret));
2450: for (j=1;j<=n;j++) {
1.224 brouard 2451: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2452: printf(" x(%d)=%.12e",j,xit[j]);
2453: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2454: }
2455: for(j=1;j<=n;j++) {
1.225 brouard 2456: printf(" p(%d)=%.12e",j,p[j]);
2457: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2458: }
2459: printf("\n");
2460: fprintf(ficlog,"\n");
2461: #endif
1.187 brouard 2462: } /* end loop on each direction i */
2463: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2464: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2465: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2466: for(j=1;j<=n;j++) {
1.302 brouard 2467: if(flatdir[j] >0){
2468: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2469: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2470: }
2471: /* printf("\n"); */
2472: /* fprintf(ficlog,"\n"); */
2473: }
1.243 brouard 2474: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2475: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2476: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2477: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2478: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2479: /* decreased of more than 3.84 */
2480: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2481: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2482: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2483:
1.188 brouard 2484: /* Starting the program with initial values given by a former maximization will simply change */
2485: /* the scales of the directions and the directions, because the are reset to canonical directions */
2486: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2487: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2488: #ifdef DEBUG
2489: int k[2],l;
2490: k[0]=1;
2491: k[1]=-1;
2492: printf("Max: %.12e",(*func)(p));
2493: fprintf(ficlog,"Max: %.12e",(*func)(p));
2494: for (j=1;j<=n;j++) {
2495: printf(" %.12e",p[j]);
2496: fprintf(ficlog," %.12e",p[j]);
2497: }
2498: printf("\n");
2499: fprintf(ficlog,"\n");
2500: for(l=0;l<=1;l++) {
2501: for (j=1;j<=n;j++) {
2502: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2503: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2504: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2505: }
2506: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2507: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2508: }
2509: #endif
2510:
1.224 brouard 2511: #ifdef LINMINORIGINAL
2512: #else
2513: free_ivector(flatdir,1,n);
2514: #endif
1.126 brouard 2515: free_vector(xit,1,n);
2516: free_vector(xits,1,n);
2517: free_vector(ptt,1,n);
2518: free_vector(pt,1,n);
2519: return;
1.192 brouard 2520: } /* enough precision */
1.240 brouard 2521: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2522: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2523: ptt[j]=2.0*p[j]-pt[j];
2524: xit[j]=p[j]-pt[j];
2525: pt[j]=p[j];
2526: }
1.181 brouard 2527: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2528: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2529: if (*iter <=4) {
1.225 brouard 2530: #else
2531: #endif
1.224 brouard 2532: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2533: #else
1.161 brouard 2534: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2535: #endif
1.162 brouard 2536: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2537: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2538: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2539: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2540: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2541: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2542: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2543: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2544: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2545: /* Even if f3 <f1, directest can be negative and t >0 */
2546: /* mu² and del² are equal when f3=f1 */
2547: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2548: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2549: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2550: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2551: #ifdef NRCORIGINAL
2552: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2553: #else
2554: 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 2555: t= t- del*SQR(fp-fptt);
1.183 brouard 2556: #endif
1.202 brouard 2557: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2558: #ifdef DEBUG
1.181 brouard 2559: 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);
2560: 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 2561: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2562: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2563: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2564: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2565: 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);
2566: 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);
2567: #endif
1.183 brouard 2568: #ifdef POWELLORIGINAL
2569: if (t < 0.0) { /* Then we use it for new direction */
2570: #else
1.182 brouard 2571: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2572: 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 2573: 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 2574: 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 2575: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2576: }
1.181 brouard 2577: if (directest < 0.0) { /* Then we use it for new direction */
2578: #endif
1.191 brouard 2579: #ifdef DEBUGLINMIN
1.234 brouard 2580: printf("Before linmin in direction P%d-P0\n",n);
2581: for (j=1;j<=n;j++) {
2582: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2583: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2584: if(j % ncovmodel == 0){
2585: printf("\n");
2586: fprintf(ficlog,"\n");
2587: }
2588: }
1.224 brouard 2589: #endif
2590: #ifdef LINMINORIGINAL
1.234 brouard 2591: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2592: #else
1.234 brouard 2593: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2594: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2595: #endif
1.234 brouard 2596:
1.191 brouard 2597: #ifdef DEBUGLINMIN
1.234 brouard 2598: for (j=1;j<=n;j++) {
2599: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2600: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2601: if(j % ncovmodel == 0){
2602: printf("\n");
2603: fprintf(ficlog,"\n");
2604: }
2605: }
1.224 brouard 2606: #endif
1.234 brouard 2607: for (j=1;j<=n;j++) {
2608: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2609: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2610: }
1.224 brouard 2611: #ifdef LINMINORIGINAL
2612: #else
1.234 brouard 2613: for (j=1, flatd=0;j<=n;j++) {
2614: if(flatdir[j]>0)
2615: flatd++;
2616: }
2617: if(flatd >0){
1.255 brouard 2618: printf("%d flat directions: ",flatd);
2619: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2620: for (j=1;j<=n;j++) {
2621: if(flatdir[j]>0){
2622: printf("%d ",j);
2623: fprintf(ficlog,"%d ",j);
2624: }
2625: }
2626: printf("\n");
2627: fprintf(ficlog,"\n");
2628: }
1.191 brouard 2629: #endif
1.234 brouard 2630: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2631: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2632:
1.126 brouard 2633: #ifdef DEBUG
1.234 brouard 2634: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2635: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2636: for(j=1;j<=n;j++){
2637: printf(" %lf",xit[j]);
2638: fprintf(ficlog," %lf",xit[j]);
2639: }
2640: printf("\n");
2641: fprintf(ficlog,"\n");
1.126 brouard 2642: #endif
1.192 brouard 2643: } /* end of t or directest negative */
1.224 brouard 2644: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2645: #else
1.234 brouard 2646: } /* end if (fptt < fp) */
1.192 brouard 2647: #endif
1.225 brouard 2648: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2649: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2650: #else
1.224 brouard 2651: #endif
1.234 brouard 2652: } /* loop iteration */
1.126 brouard 2653: }
1.234 brouard 2654:
1.126 brouard 2655: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2656:
1.235 brouard 2657: 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 2658: {
1.279 brouard 2659: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2660: * (and selected quantitative values in nres)
2661: * by left multiplying the unit
2662: * matrix by transitions matrix until convergence is reached with precision ftolpl
2663: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2664: * Wx is row vector: population in state 1, population in state 2, population dead
2665: * or prevalence in state 1, prevalence in state 2, 0
2666: * newm is the matrix after multiplications, its rows are identical at a factor.
2667: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2668: * Output is prlim.
2669: * Initial matrix pimij
2670: */
1.206 brouard 2671: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2672: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2673: /* 0, 0 , 1} */
2674: /*
2675: * and after some iteration: */
2676: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2677: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2678: /* 0, 0 , 1} */
2679: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2680: /* {0.51571254859325999, 0.4842874514067399, */
2681: /* 0.51326036147820708, 0.48673963852179264} */
2682: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2683:
1.126 brouard 2684: int i, ii,j,k;
1.209 brouard 2685: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2686: /* double **matprod2(); */ /* test */
1.218 brouard 2687: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2688: double **newm;
1.209 brouard 2689: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2690: int ncvloop=0;
1.288 brouard 2691: int first=0;
1.169 brouard 2692:
1.209 brouard 2693: min=vector(1,nlstate);
2694: max=vector(1,nlstate);
2695: meandiff=vector(1,nlstate);
2696:
1.218 brouard 2697: /* Starting with matrix unity */
1.126 brouard 2698: for (ii=1;ii<=nlstate+ndeath;ii++)
2699: for (j=1;j<=nlstate+ndeath;j++){
2700: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2701: }
1.169 brouard 2702:
2703: cov[1]=1.;
2704:
2705: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2706: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2707: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2708: ncvloop++;
1.126 brouard 2709: newm=savm;
2710: /* Covariates have to be included here again */
1.138 brouard 2711: cov[2]=agefin;
1.187 brouard 2712: if(nagesqr==1)
2713: cov[3]= agefin*agefin;;
1.234 brouard 2714: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2715: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2716: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2717: /* 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 2718: }
2719: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2720: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2721: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2722: /* 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 2723: }
1.237 brouard 2724: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2725: if(Dummy[Tvar[Tage[k]]]){
2726: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2727: } else{
1.235 brouard 2728: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2729: }
1.235 brouard 2730: /* 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 2731: }
1.237 brouard 2732: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2733: /* 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 2734: if(Dummy[Tvard[k][1]==0]){
2735: if(Dummy[Tvard[k][2]==0]){
2736: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2737: }else{
2738: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2739: }
2740: }else{
2741: if(Dummy[Tvard[k][2]==0]){
2742: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2743: }else{
2744: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2745: }
2746: }
1.234 brouard 2747: }
1.138 brouard 2748: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2749: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2750: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2751: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2752: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2753: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2754: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2755:
1.126 brouard 2756: savm=oldm;
2757: oldm=newm;
1.209 brouard 2758:
2759: for(j=1; j<=nlstate; j++){
2760: max[j]=0.;
2761: min[j]=1.;
2762: }
2763: for(i=1;i<=nlstate;i++){
2764: sumnew=0;
2765: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2766: for(j=1; j<=nlstate; j++){
2767: prlim[i][j]= newm[i][j]/(1-sumnew);
2768: max[j]=FMAX(max[j],prlim[i][j]);
2769: min[j]=FMIN(min[j],prlim[i][j]);
2770: }
2771: }
2772:
1.126 brouard 2773: maxmax=0.;
1.209 brouard 2774: for(j=1; j<=nlstate; j++){
2775: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2776: maxmax=FMAX(maxmax,meandiff[j]);
2777: /* 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 2778: } /* j loop */
1.203 brouard 2779: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2780: /* 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 2781: if(maxmax < ftolpl){
1.209 brouard 2782: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2783: free_vector(min,1,nlstate);
2784: free_vector(max,1,nlstate);
2785: free_vector(meandiff,1,nlstate);
1.126 brouard 2786: return prlim;
2787: }
1.288 brouard 2788: } /* agefin loop */
1.208 brouard 2789: /* After some age loop it doesn't converge */
1.288 brouard 2790: if(!first){
2791: first=1;
2792: 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);
2793: }
2794: 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);
2795:
1.209 brouard 2796: /* 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); */
2797: free_vector(min,1,nlstate);
2798: free_vector(max,1,nlstate);
2799: free_vector(meandiff,1,nlstate);
1.208 brouard 2800:
1.169 brouard 2801: return prlim; /* should not reach here */
1.126 brouard 2802: }
2803:
1.217 brouard 2804:
2805: /**** Back Prevalence limit (stable or period prevalence) ****************/
2806:
1.218 brouard 2807: /* 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) */
2808: /* 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 2809: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2810: {
1.264 brouard 2811: /* 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 2812: matrix by transitions matrix until convergence is reached with precision ftolpl */
2813: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2814: /* Wx is row vector: population in state 1, population in state 2, population dead */
2815: /* or prevalence in state 1, prevalence in state 2, 0 */
2816: /* newm is the matrix after multiplications, its rows are identical at a factor */
2817: /* Initial matrix pimij */
2818: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2819: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2820: /* 0, 0 , 1} */
2821: /*
2822: * and after some iteration: */
2823: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2824: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2825: /* 0, 0 , 1} */
2826: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2827: /* {0.51571254859325999, 0.4842874514067399, */
2828: /* 0.51326036147820708, 0.48673963852179264} */
2829: /* If we start from prlim again, prlim tends to a constant matrix */
2830:
2831: int i, ii,j,k;
1.247 brouard 2832: int first=0;
1.217 brouard 2833: double *min, *max, *meandiff, maxmax,sumnew=0.;
2834: /* double **matprod2(); */ /* test */
2835: double **out, cov[NCOVMAX+1], **bmij();
2836: double **newm;
1.218 brouard 2837: double **dnewm, **doldm, **dsavm; /* for use */
2838: double **oldm, **savm; /* for use */
2839:
1.217 brouard 2840: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2841: int ncvloop=0;
2842:
2843: min=vector(1,nlstate);
2844: max=vector(1,nlstate);
2845: meandiff=vector(1,nlstate);
2846:
1.266 brouard 2847: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2848: oldm=oldms; savm=savms;
2849:
2850: /* Starting with matrix unity */
2851: for (ii=1;ii<=nlstate+ndeath;ii++)
2852: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2853: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2854: }
2855:
2856: cov[1]=1.;
2857:
2858: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2859: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2860: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 2861: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2862: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2863: ncvloop++;
1.218 brouard 2864: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2865: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2866: /* Covariates have to be included here again */
2867: cov[2]=agefin;
2868: if(nagesqr==1)
2869: cov[3]= agefin*agefin;;
1.242 brouard 2870: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2871: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2872: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2873: /* 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 2874: }
2875: /* for (k=1; k<=cptcovn;k++) { */
2876: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2877: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2878: /* /\* 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])]); *\/ */
2879: /* } */
2880: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2881: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2882: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2883: /* 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]); */
2884: }
2885: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2886: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2887: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2888: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2889: for (k=1; k<=cptcovage;k++){ /* For product with age */
2890: if(Dummy[Tvar[Tage[k]]]){
2891: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2892: } else{
2893: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2894: }
2895: /* 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]); */
2896: }
2897: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2898: /* 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]); */
2899: if(Dummy[Tvard[k][1]==0]){
2900: if(Dummy[Tvard[k][2]==0]){
2901: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2902: }else{
2903: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2904: }
2905: }else{
2906: if(Dummy[Tvard[k][2]==0]){
2907: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2908: }else{
2909: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2910: }
2911: }
1.217 brouard 2912: }
2913:
2914: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2915: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2916: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2917: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2918: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2919: /* ij should be linked to the correct index of cov */
2920: /* age and covariate values ij are in 'cov', but we need to pass
2921: * ij for the observed prevalence at age and status and covariate
2922: * number: prevacurrent[(int)agefin][ii][ij]
2923: */
2924: /* 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 *\/ */
2925: /* 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 *\/ */
2926: 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 2927: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2928: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2929: /* for(i=1; i<=nlstate+ndeath; i++) { */
2930: /* printf("%d newm= ",i); */
2931: /* for(j=1;j<=nlstate+ndeath;j++) { */
2932: /* printf("%f ",newm[i][j]); */
2933: /* } */
2934: /* printf("oldm * "); */
2935: /* for(j=1;j<=nlstate+ndeath;j++) { */
2936: /* printf("%f ",oldm[i][j]); */
2937: /* } */
1.268 brouard 2938: /* printf(" bmmij "); */
1.266 brouard 2939: /* for(j=1;j<=nlstate+ndeath;j++) { */
2940: /* printf("%f ",pmmij[i][j]); */
2941: /* } */
2942: /* printf("\n"); */
2943: /* } */
2944: /* } */
1.217 brouard 2945: savm=oldm;
2946: oldm=newm;
1.266 brouard 2947:
1.217 brouard 2948: for(j=1; j<=nlstate; j++){
2949: max[j]=0.;
2950: min[j]=1.;
2951: }
2952: for(j=1; j<=nlstate; j++){
2953: for(i=1;i<=nlstate;i++){
1.234 brouard 2954: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2955: bprlim[i][j]= newm[i][j];
2956: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2957: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2958: }
2959: }
1.218 brouard 2960:
1.217 brouard 2961: maxmax=0.;
2962: for(i=1; i<=nlstate; i++){
2963: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2964: maxmax=FMAX(maxmax,meandiff[i]);
2965: /* 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 2966: } /* i loop */
1.217 brouard 2967: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 2968: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2969: if(maxmax < ftolpl){
1.220 brouard 2970: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2971: free_vector(min,1,nlstate);
2972: free_vector(max,1,nlstate);
2973: free_vector(meandiff,1,nlstate);
2974: return bprlim;
2975: }
1.288 brouard 2976: } /* agefin loop */
1.217 brouard 2977: /* After some age loop it doesn't converge */
1.288 brouard 2978: if(!first){
1.247 brouard 2979: first=1;
2980: 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\
2981: 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);
2982: }
2983: 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 2984: 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);
2985: /* 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); */
2986: free_vector(min,1,nlstate);
2987: free_vector(max,1,nlstate);
2988: free_vector(meandiff,1,nlstate);
2989:
2990: return bprlim; /* should not reach here */
2991: }
2992:
1.126 brouard 2993: /*************** transition probabilities ***************/
2994:
2995: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2996: {
1.138 brouard 2997: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2998: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2999: model to the ncovmodel covariates (including constant and age).
3000: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3001: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3002: ncth covariate in the global vector x is given by the formula:
3003: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3004: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3005: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3006: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3007: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3008: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3009: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3010: */
3011: double s1, lnpijopii;
1.126 brouard 3012: /*double t34;*/
1.164 brouard 3013: int i,j, nc, ii, jj;
1.126 brouard 3014:
1.223 brouard 3015: for(i=1; i<= nlstate; i++){
3016: for(j=1; j<i;j++){
3017: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3018: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3019: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3020: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3021: }
3022: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3023: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3024: }
3025: for(j=i+1; j<=nlstate+ndeath;j++){
3026: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3027: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3028: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3029: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3030: }
3031: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3032: }
3033: }
1.218 brouard 3034:
1.223 brouard 3035: for(i=1; i<= nlstate; i++){
3036: s1=0;
3037: for(j=1; j<i; j++){
3038: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3039: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3040: }
3041: for(j=i+1; j<=nlstate+ndeath; j++){
3042: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3043: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3044: }
3045: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3046: ps[i][i]=1./(s1+1.);
3047: /* Computing other pijs */
3048: for(j=1; j<i; j++)
3049: ps[i][j]= exp(ps[i][j])*ps[i][i];
3050: for(j=i+1; j<=nlstate+ndeath; j++)
3051: ps[i][j]= exp(ps[i][j])*ps[i][i];
3052: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3053: } /* end i */
1.218 brouard 3054:
1.223 brouard 3055: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3056: for(jj=1; jj<= nlstate+ndeath; jj++){
3057: ps[ii][jj]=0;
3058: ps[ii][ii]=1;
3059: }
3060: }
1.294 brouard 3061:
3062:
1.223 brouard 3063: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3064: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3065: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3066: /* } */
3067: /* printf("\n "); */
3068: /* } */
3069: /* printf("\n ");printf("%lf ",cov[2]);*/
3070: /*
3071: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3072: goto end;*/
1.266 brouard 3073: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3074: }
3075:
1.218 brouard 3076: /*************** backward transition probabilities ***************/
3077:
3078: /* 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 ) */
3079: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3080: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3081: {
1.302 brouard 3082: /* 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 3083: * 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 3084: */
1.218 brouard 3085: int i, ii, j,k;
1.222 brouard 3086:
3087: double **out, **pmij();
3088: double sumnew=0.;
1.218 brouard 3089: double agefin;
1.292 brouard 3090: 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 3091: double **dnewm, **dsavm, **doldm;
3092: double **bbmij;
3093:
1.218 brouard 3094: doldm=ddoldms; /* global pointers */
1.222 brouard 3095: dnewm=ddnewms;
3096: dsavm=ddsavms;
3097:
3098: agefin=cov[2];
1.268 brouard 3099: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3100: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3101: the observed prevalence (with this covariate ij) at beginning of transition */
3102: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3103:
3104: /* P_x */
1.266 brouard 3105: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 3106: /* outputs pmmij which is a stochastic matrix in row */
3107:
3108: /* Diag(w_x) */
1.292 brouard 3109: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3110: sumnew=0.;
1.269 brouard 3111: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3112: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3113: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3114: sumnew+=prevacurrent[(int)agefin][ii][ij];
3115: }
3116: if(sumnew >0.01){ /* At least some value in the prevalence */
3117: for (ii=1;ii<=nlstate+ndeath;ii++){
3118: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3119: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3120: }
3121: }else{
3122: for (ii=1;ii<=nlstate+ndeath;ii++){
3123: for (j=1;j<=nlstate+ndeath;j++)
3124: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3125: }
3126: /* if(sumnew <0.9){ */
3127: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3128: /* } */
3129: }
3130: k3=0.0; /* We put the last diagonal to 0 */
3131: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3132: doldm[ii][ii]= k3;
3133: }
3134: /* End doldm, At the end doldm is diag[(w_i)] */
3135:
1.292 brouard 3136: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3137: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3138:
1.292 brouard 3139: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3140: /* 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 3141: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3142: sumnew=0.;
1.222 brouard 3143: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3144: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3145: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3146: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3147: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3148: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3149: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3150: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3151: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3152: /* }else */
1.268 brouard 3153: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3154: } /*End ii */
3155: } /* 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 */
3156:
1.292 brouard 3157: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3158: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3159: /* end bmij */
1.266 brouard 3160: return ps; /*pointer is unchanged */
1.218 brouard 3161: }
1.217 brouard 3162: /*************** transition probabilities ***************/
3163:
1.218 brouard 3164: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3165: {
3166: /* According to parameters values stored in x and the covariate's values stored in cov,
3167: computes the probability to be observed in state j being in state i by appying the
3168: model to the ncovmodel covariates (including constant and age).
3169: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3170: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3171: ncth covariate in the global vector x is given by the formula:
3172: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3173: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3174: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3175: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3176: Outputs ps[i][j] the probability to be observed in j being in j according to
3177: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3178: */
3179: double s1, lnpijopii;
3180: /*double t34;*/
3181: int i,j, nc, ii, jj;
3182:
1.234 brouard 3183: for(i=1; i<= nlstate; i++){
3184: for(j=1; j<i;j++){
3185: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3186: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3187: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3188: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3189: }
3190: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3191: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3192: }
3193: for(j=i+1; j<=nlstate+ndeath;j++){
3194: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3195: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3196: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3197: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3198: }
3199: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3200: }
3201: }
3202:
3203: for(i=1; i<= nlstate; i++){
3204: s1=0;
3205: for(j=1; j<i; j++){
3206: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3207: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3208: }
3209: for(j=i+1; j<=nlstate+ndeath; j++){
3210: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3211: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3212: }
3213: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3214: ps[i][i]=1./(s1+1.);
3215: /* Computing other pijs */
3216: for(j=1; j<i; j++)
3217: ps[i][j]= exp(ps[i][j])*ps[i][i];
3218: for(j=i+1; j<=nlstate+ndeath; j++)
3219: ps[i][j]= exp(ps[i][j])*ps[i][i];
3220: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3221: } /* end i */
3222:
3223: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3224: for(jj=1; jj<= nlstate+ndeath; jj++){
3225: ps[ii][jj]=0;
3226: ps[ii][ii]=1;
3227: }
3228: }
1.296 brouard 3229: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3230: for(jj=1; jj<= nlstate+ndeath; jj++){
3231: s1=0.;
3232: for(ii=1; ii<= nlstate+ndeath; ii++){
3233: s1+=ps[ii][jj];
3234: }
3235: for(ii=1; ii<= nlstate; ii++){
3236: ps[ii][jj]=ps[ii][jj]/s1;
3237: }
3238: }
3239: /* Transposition */
3240: for(jj=1; jj<= nlstate+ndeath; jj++){
3241: for(ii=jj; ii<= nlstate+ndeath; ii++){
3242: s1=ps[ii][jj];
3243: ps[ii][jj]=ps[jj][ii];
3244: ps[jj][ii]=s1;
3245: }
3246: }
3247: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3248: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3249: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3250: /* } */
3251: /* printf("\n "); */
3252: /* } */
3253: /* printf("\n ");printf("%lf ",cov[2]);*/
3254: /*
3255: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3256: goto end;*/
3257: return ps;
1.217 brouard 3258: }
3259:
3260:
1.126 brouard 3261: /**************** Product of 2 matrices ******************/
3262:
1.145 brouard 3263: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3264: {
3265: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3266: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3267: /* in, b, out are matrice of pointers which should have been initialized
3268: before: only the contents of out is modified. The function returns
3269: a pointer to pointers identical to out */
1.145 brouard 3270: int i, j, k;
1.126 brouard 3271: for(i=nrl; i<= nrh; i++)
1.145 brouard 3272: for(k=ncolol; k<=ncoloh; k++){
3273: out[i][k]=0.;
3274: for(j=ncl; j<=nch; j++)
3275: out[i][k] +=in[i][j]*b[j][k];
3276: }
1.126 brouard 3277: return out;
3278: }
3279:
3280:
3281: /************* Higher Matrix Product ***************/
3282:
1.235 brouard 3283: 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 3284: {
1.218 brouard 3285: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3286: 'nhstepm*hstepm*stepm' months (i.e. until
3287: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3288: nhstepm*hstepm matrices.
3289: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3290: (typically every 2 years instead of every month which is too big
3291: for the memory).
3292: Model is determined by parameters x and covariates have to be
3293: included manually here.
3294:
3295: */
3296:
3297: int i, j, d, h, k;
1.131 brouard 3298: double **out, cov[NCOVMAX+1];
1.126 brouard 3299: double **newm;
1.187 brouard 3300: double agexact;
1.214 brouard 3301: double agebegin, ageend;
1.126 brouard 3302:
3303: /* Hstepm could be zero and should return the unit matrix */
3304: for (i=1;i<=nlstate+ndeath;i++)
3305: for (j=1;j<=nlstate+ndeath;j++){
3306: oldm[i][j]=(i==j ? 1.0 : 0.0);
3307: po[i][j][0]=(i==j ? 1.0 : 0.0);
3308: }
3309: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3310: for(h=1; h <=nhstepm; h++){
3311: for(d=1; d <=hstepm; d++){
3312: newm=savm;
3313: /* Covariates have to be included here again */
3314: cov[1]=1.;
1.214 brouard 3315: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3316: cov[2]=agexact;
3317: if(nagesqr==1)
1.227 brouard 3318: cov[3]= agexact*agexact;
1.235 brouard 3319: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3320: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3321: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3322: /* 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)); */
3323: }
3324: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3325: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3326: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3327: /* 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]); */
3328: }
3329: for (k=1; k<=cptcovage;k++){
3330: if(Dummy[Tvar[Tage[k]]]){
3331: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3332: } else{
3333: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3334: }
3335: /* 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]); */
3336: }
3337: for (k=1; k<=cptcovprod;k++){ /* */
3338: /* 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]); */
3339: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3340: }
3341: /* for (k=1; k<=cptcovn;k++) */
3342: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3343: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3344: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3345: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3346: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3347:
3348:
1.126 brouard 3349: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3350: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3351: /* right multiplication of oldm by the current matrix */
1.126 brouard 3352: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3353: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3354: /* if((int)age == 70){ */
3355: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3356: /* for(i=1; i<=nlstate+ndeath; i++) { */
3357: /* printf("%d pmmij ",i); */
3358: /* for(j=1;j<=nlstate+ndeath;j++) { */
3359: /* printf("%f ",pmmij[i][j]); */
3360: /* } */
3361: /* printf(" oldm "); */
3362: /* for(j=1;j<=nlstate+ndeath;j++) { */
3363: /* printf("%f ",oldm[i][j]); */
3364: /* } */
3365: /* printf("\n"); */
3366: /* } */
3367: /* } */
1.126 brouard 3368: savm=oldm;
3369: oldm=newm;
3370: }
3371: for(i=1; i<=nlstate+ndeath; i++)
3372: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3373: po[i][j][h]=newm[i][j];
3374: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3375: }
1.128 brouard 3376: /*printf("h=%d ",h);*/
1.126 brouard 3377: } /* end h */
1.267 brouard 3378: /* printf("\n H=%d \n",h); */
1.126 brouard 3379: return po;
3380: }
3381:
1.217 brouard 3382: /************* Higher Back Matrix Product ***************/
1.218 brouard 3383: /* 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 3384: 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 3385: {
1.266 brouard 3386: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3387: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3388: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3389: nhstepm*hstepm matrices.
3390: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3391: (typically every 2 years instead of every month which is too big
1.217 brouard 3392: for the memory).
1.218 brouard 3393: Model is determined by parameters x and covariates have to be
1.266 brouard 3394: included manually here. Then we use a call to bmij(x and cov)
3395: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3396: */
1.217 brouard 3397:
3398: int i, j, d, h, k;
1.266 brouard 3399: double **out, cov[NCOVMAX+1], **bmij();
3400: double **newm, ***newmm;
1.217 brouard 3401: double agexact;
3402: double agebegin, ageend;
1.222 brouard 3403: double **oldm, **savm;
1.217 brouard 3404:
1.266 brouard 3405: newmm=po; /* To be saved */
3406: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3407: /* Hstepm could be zero and should return the unit matrix */
3408: for (i=1;i<=nlstate+ndeath;i++)
3409: for (j=1;j<=nlstate+ndeath;j++){
3410: oldm[i][j]=(i==j ? 1.0 : 0.0);
3411: po[i][j][0]=(i==j ? 1.0 : 0.0);
3412: }
3413: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3414: for(h=1; h <=nhstepm; h++){
3415: for(d=1; d <=hstepm; d++){
3416: newm=savm;
3417: /* Covariates have to be included here again */
3418: cov[1]=1.;
1.271 brouard 3419: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3420: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3421: cov[2]=agexact;
3422: if(nagesqr==1)
1.222 brouard 3423: cov[3]= agexact*agexact;
1.266 brouard 3424: for (k=1; k<=cptcovn;k++){
3425: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3426: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3427: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3428: /* 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)); */
3429: }
1.267 brouard 3430: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3431: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3432: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3433: /* 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]); */
3434: }
3435: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3436: if(Dummy[Tvar[Tage[k]]]){
3437: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3438: } else{
3439: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3440: }
3441: /* 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]); */
3442: }
3443: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3444: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3445: }
1.217 brouard 3446: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3447: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3448:
1.218 brouard 3449: /* Careful transposed matrix */
1.266 brouard 3450: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3451: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3452: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3453: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3454: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3455: /* if((int)age == 70){ */
3456: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3457: /* for(i=1; i<=nlstate+ndeath; i++) { */
3458: /* printf("%d pmmij ",i); */
3459: /* for(j=1;j<=nlstate+ndeath;j++) { */
3460: /* printf("%f ",pmmij[i][j]); */
3461: /* } */
3462: /* printf(" oldm "); */
3463: /* for(j=1;j<=nlstate+ndeath;j++) { */
3464: /* printf("%f ",oldm[i][j]); */
3465: /* } */
3466: /* printf("\n"); */
3467: /* } */
3468: /* } */
3469: savm=oldm;
3470: oldm=newm;
3471: }
3472: for(i=1; i<=nlstate+ndeath; i++)
3473: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3474: po[i][j][h]=newm[i][j];
1.268 brouard 3475: /* if(h==nhstepm) */
3476: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3477: }
1.268 brouard 3478: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3479: } /* end h */
1.268 brouard 3480: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3481: return po;
3482: }
3483:
3484:
1.162 brouard 3485: #ifdef NLOPT
3486: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3487: double fret;
3488: double *xt;
3489: int j;
3490: myfunc_data *d2 = (myfunc_data *) pd;
3491: /* xt = (p1-1); */
3492: xt=vector(1,n);
3493: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3494:
3495: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3496: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3497: printf("Function = %.12lf ",fret);
3498: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3499: printf("\n");
3500: free_vector(xt,1,n);
3501: return fret;
3502: }
3503: #endif
1.126 brouard 3504:
3505: /*************** log-likelihood *************/
3506: double func( double *x)
3507: {
1.226 brouard 3508: int i, ii, j, k, mi, d, kk;
3509: int ioffset=0;
3510: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3511: double **out;
3512: double lli; /* Individual log likelihood */
3513: int s1, s2;
1.228 brouard 3514: 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 3515: double bbh, survp;
3516: long ipmx;
3517: double agexact;
3518: /*extern weight */
3519: /* We are differentiating ll according to initial status */
3520: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3521: /*for(i=1;i<imx;i++)
3522: printf(" %d\n",s[4][i]);
3523: */
1.162 brouard 3524:
1.226 brouard 3525: ++countcallfunc;
1.162 brouard 3526:
1.226 brouard 3527: cov[1]=1.;
1.126 brouard 3528:
1.226 brouard 3529: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3530: ioffset=0;
1.226 brouard 3531: if(mle==1){
3532: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3533: /* Computes the values of the ncovmodel covariates of the model
3534: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3535: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3536: to be observed in j being in i according to the model.
3537: */
1.243 brouard 3538: ioffset=2+nagesqr ;
1.233 brouard 3539: /* Fixed */
1.234 brouard 3540: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3541: 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)*/
3542: }
1.226 brouard 3543: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3544: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3545: has been calculated etc */
3546: /* For an individual i, wav[i] gives the number of effective waves */
3547: /* We compute the contribution to Likelihood of each effective transition
3548: mw[mi][i] is real wave of the mi th effectve wave */
3549: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3550: s2=s[mw[mi+1][i]][i];
3551: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3552: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3553: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3554: */
3555: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3556: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3557: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3558: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3559: }
3560: for (ii=1;ii<=nlstate+ndeath;ii++)
3561: for (j=1;j<=nlstate+ndeath;j++){
3562: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3563: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3564: }
3565: for(d=0; d<dh[mi][i]; d++){
3566: newm=savm;
3567: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3568: cov[2]=agexact;
3569: if(nagesqr==1)
3570: cov[3]= agexact*agexact; /* Should be changed here */
3571: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3572: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3573: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3574: else
3575: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3576: }
3577: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3578: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3579: savm=oldm;
3580: oldm=newm;
3581: } /* end mult */
3582:
3583: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3584: /* But now since version 0.9 we anticipate for bias at large stepm.
3585: * If stepm is larger than one month (smallest stepm) and if the exact delay
3586: * (in months) between two waves is not a multiple of stepm, we rounded to
3587: * the nearest (and in case of equal distance, to the lowest) interval but now
3588: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3589: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3590: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3591: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3592: * -stepm/2 to stepm/2 .
3593: * For stepm=1 the results are the same as for previous versions of Imach.
3594: * For stepm > 1 the results are less biased than in previous versions.
3595: */
1.234 brouard 3596: s1=s[mw[mi][i]][i];
3597: s2=s[mw[mi+1][i]][i];
3598: bbh=(double)bh[mi][i]/(double)stepm;
3599: /* bias bh is positive if real duration
3600: * is higher than the multiple of stepm and negative otherwise.
3601: */
3602: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3603: if( s2 > nlstate){
3604: /* i.e. if s2 is a death state and if the date of death is known
3605: then the contribution to the likelihood is the probability to
3606: die between last step unit time and current step unit time,
3607: which is also equal to probability to die before dh
3608: minus probability to die before dh-stepm .
3609: In version up to 0.92 likelihood was computed
3610: as if date of death was unknown. Death was treated as any other
3611: health state: the date of the interview describes the actual state
3612: and not the date of a change in health state. The former idea was
3613: to consider that at each interview the state was recorded
3614: (healthy, disable or death) and IMaCh was corrected; but when we
3615: introduced the exact date of death then we should have modified
3616: the contribution of an exact death to the likelihood. This new
3617: contribution is smaller and very dependent of the step unit
3618: stepm. It is no more the probability to die between last interview
3619: and month of death but the probability to survive from last
3620: interview up to one month before death multiplied by the
3621: probability to die within a month. Thanks to Chris
3622: Jackson for correcting this bug. Former versions increased
3623: mortality artificially. The bad side is that we add another loop
3624: which slows down the processing. The difference can be up to 10%
3625: lower mortality.
3626: */
3627: /* If, at the beginning of the maximization mostly, the
3628: cumulative probability or probability to be dead is
3629: constant (ie = 1) over time d, the difference is equal to
3630: 0. out[s1][3] = savm[s1][3]: probability, being at state
3631: s1 at precedent wave, to be dead a month before current
3632: wave is equal to probability, being at state s1 at
3633: precedent wave, to be dead at mont of the current
3634: wave. Then the observed probability (that this person died)
3635: is null according to current estimated parameter. In fact,
3636: it should be very low but not zero otherwise the log go to
3637: infinity.
3638: */
1.183 brouard 3639: /* #ifdef INFINITYORIGINAL */
3640: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3641: /* #else */
3642: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3643: /* lli=log(mytinydouble); */
3644: /* else */
3645: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3646: /* #endif */
1.226 brouard 3647: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3648:
1.226 brouard 3649: } else if ( s2==-1 ) { /* alive */
3650: for (j=1,survp=0. ; j<=nlstate; j++)
3651: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3652: /*survp += out[s1][j]; */
3653: lli= log(survp);
3654: }
3655: else if (s2==-4) {
3656: for (j=3,survp=0. ; j<=nlstate; j++)
3657: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3658: lli= log(survp);
3659: }
3660: else if (s2==-5) {
3661: for (j=1,survp=0. ; j<=2; j++)
3662: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3663: lli= log(survp);
3664: }
3665: else{
3666: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3667: /* 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 */
3668: }
3669: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3670: /*if(lli ==000.0)*/
3671: /*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); */
3672: ipmx +=1;
3673: sw += weight[i];
3674: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3675: /* if (lli < log(mytinydouble)){ */
3676: /* 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); */
3677: /* 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]); */
3678: /* } */
3679: } /* end of wave */
3680: } /* end of individual */
3681: } else if(mle==2){
3682: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3683: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3684: for(mi=1; mi<= wav[i]-1; mi++){
3685: for (ii=1;ii<=nlstate+ndeath;ii++)
3686: for (j=1;j<=nlstate+ndeath;j++){
3687: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3688: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3689: }
3690: for(d=0; d<=dh[mi][i]; d++){
3691: newm=savm;
3692: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3693: cov[2]=agexact;
3694: if(nagesqr==1)
3695: cov[3]= agexact*agexact;
3696: for (kk=1; kk<=cptcovage;kk++) {
3697: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3698: }
3699: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3700: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3701: savm=oldm;
3702: oldm=newm;
3703: } /* end mult */
3704:
3705: s1=s[mw[mi][i]][i];
3706: s2=s[mw[mi+1][i]][i];
3707: bbh=(double)bh[mi][i]/(double)stepm;
3708: 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 */
3709: ipmx +=1;
3710: sw += weight[i];
3711: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3712: } /* end of wave */
3713: } /* end of individual */
3714: } else if(mle==3){ /* exponential inter-extrapolation */
3715: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3716: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3717: for(mi=1; mi<= wav[i]-1; mi++){
3718: for (ii=1;ii<=nlstate+ndeath;ii++)
3719: for (j=1;j<=nlstate+ndeath;j++){
3720: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3721: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3722: }
3723: for(d=0; d<dh[mi][i]; d++){
3724: newm=savm;
3725: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3726: cov[2]=agexact;
3727: if(nagesqr==1)
3728: cov[3]= agexact*agexact;
3729: for (kk=1; kk<=cptcovage;kk++) {
3730: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3731: }
3732: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3733: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3734: savm=oldm;
3735: oldm=newm;
3736: } /* end mult */
3737:
3738: s1=s[mw[mi][i]][i];
3739: s2=s[mw[mi+1][i]][i];
3740: bbh=(double)bh[mi][i]/(double)stepm;
3741: 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 */
3742: ipmx +=1;
3743: sw += weight[i];
3744: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3745: } /* end of wave */
3746: } /* end of individual */
3747: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3748: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3749: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3750: for(mi=1; mi<= wav[i]-1; mi++){
3751: for (ii=1;ii<=nlstate+ndeath;ii++)
3752: for (j=1;j<=nlstate+ndeath;j++){
3753: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3754: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3755: }
3756: for(d=0; d<dh[mi][i]; d++){
3757: newm=savm;
3758: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3759: cov[2]=agexact;
3760: if(nagesqr==1)
3761: cov[3]= agexact*agexact;
3762: for (kk=1; kk<=cptcovage;kk++) {
3763: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3764: }
1.126 brouard 3765:
1.226 brouard 3766: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3767: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3768: savm=oldm;
3769: oldm=newm;
3770: } /* end mult */
3771:
3772: s1=s[mw[mi][i]][i];
3773: s2=s[mw[mi+1][i]][i];
3774: if( s2 > nlstate){
3775: lli=log(out[s1][s2] - savm[s1][s2]);
3776: } else if ( s2==-1 ) { /* alive */
3777: for (j=1,survp=0. ; j<=nlstate; j++)
3778: survp += out[s1][j];
3779: lli= log(survp);
3780: }else{
3781: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3782: }
3783: ipmx +=1;
3784: sw += weight[i];
3785: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3786: /* 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 3787: } /* end of wave */
3788: } /* end of individual */
3789: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3790: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3791: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3792: for(mi=1; mi<= wav[i]-1; mi++){
3793: for (ii=1;ii<=nlstate+ndeath;ii++)
3794: for (j=1;j<=nlstate+ndeath;j++){
3795: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3796: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3797: }
3798: for(d=0; d<dh[mi][i]; d++){
3799: newm=savm;
3800: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3801: cov[2]=agexact;
3802: if(nagesqr==1)
3803: cov[3]= agexact*agexact;
3804: for (kk=1; kk<=cptcovage;kk++) {
3805: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3806: }
1.126 brouard 3807:
1.226 brouard 3808: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3809: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3810: savm=oldm;
3811: oldm=newm;
3812: } /* end mult */
3813:
3814: s1=s[mw[mi][i]][i];
3815: s2=s[mw[mi+1][i]][i];
3816: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3817: ipmx +=1;
3818: sw += weight[i];
3819: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3820: /*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]);*/
3821: } /* end of wave */
3822: } /* end of individual */
3823: } /* End of if */
3824: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3825: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3826: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3827: return -l;
1.126 brouard 3828: }
3829:
3830: /*************** log-likelihood *************/
3831: double funcone( double *x)
3832: {
1.228 brouard 3833: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3834: int i, ii, j, k, mi, d, kk;
1.228 brouard 3835: int ioffset=0;
1.131 brouard 3836: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3837: double **out;
3838: double lli; /* Individual log likelihood */
3839: double llt;
3840: int s1, s2;
1.228 brouard 3841: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3842:
1.126 brouard 3843: double bbh, survp;
1.187 brouard 3844: double agexact;
1.214 brouard 3845: double agebegin, ageend;
1.126 brouard 3846: /*extern weight */
3847: /* We are differentiating ll according to initial status */
3848: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3849: /*for(i=1;i<imx;i++)
3850: printf(" %d\n",s[4][i]);
3851: */
3852: cov[1]=1.;
3853:
3854: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3855: ioffset=0;
3856: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3857: /* ioffset=2+nagesqr+cptcovage; */
3858: ioffset=2+nagesqr;
1.232 brouard 3859: /* Fixed */
1.224 brouard 3860: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3861: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.311 brouard 3862: 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 3863: 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)*/
3864: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3865: /* cov[2+6]=covar[Tvar[6]][i]; */
3866: /* cov[2+6]=covar[2][i]; V2 */
3867: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3868: /* cov[2+7]=covar[Tvar[7]][i]; */
3869: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3870: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3871: /* cov[2+9]=covar[Tvar[9]][i]; */
3872: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3873: }
1.232 brouard 3874: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3875: /* 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?)*\/ */
3876: /* } */
1.231 brouard 3877: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3878: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3879: /* } */
1.225 brouard 3880:
1.233 brouard 3881:
3882: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3883: /* Wave varying (but not age varying) */
3884: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3885: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3886: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3887: }
1.232 brouard 3888: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3889: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3890: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3891: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3892: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3893: /* 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 3894: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3895: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3896: /* /\* 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]); *\/ */
3897: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3898: /* } */
1.126 brouard 3899: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3900: for (j=1;j<=nlstate+ndeath;j++){
3901: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3902: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3903: }
1.214 brouard 3904:
3905: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3906: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3907: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3908: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3909: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3910: and mw[mi+1][i]. dh depends on stepm.*/
3911: newm=savm;
1.247 brouard 3912: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3913: cov[2]=agexact;
3914: if(nagesqr==1)
3915: cov[3]= agexact*agexact;
3916: for (kk=1; kk<=cptcovage;kk++) {
3917: if(!FixedV[Tvar[Tage[kk]]])
3918: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3919: else
3920: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3921: }
3922: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3923: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3924: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3925: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3926: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3927: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3928: savm=oldm;
3929: oldm=newm;
1.126 brouard 3930: } /* end mult */
3931:
3932: s1=s[mw[mi][i]][i];
3933: s2=s[mw[mi+1][i]][i];
1.217 brouard 3934: /* if(s2==-1){ */
1.268 brouard 3935: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3936: /* /\* exit(1); *\/ */
3937: /* } */
1.126 brouard 3938: bbh=(double)bh[mi][i]/(double)stepm;
3939: /* bias is positive if real duration
3940: * is higher than the multiple of stepm and negative otherwise.
3941: */
3942: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3943: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3944: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3945: for (j=1,survp=0. ; j<=nlstate; j++)
3946: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3947: lli= log(survp);
1.126 brouard 3948: }else if (mle==1){
1.242 brouard 3949: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3950: } else if(mle==2){
1.242 brouard 3951: 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 3952: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3953: 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 3954: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3955: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3956: } else{ /* mle=0 back to 1 */
1.242 brouard 3957: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3958: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3959: } /* End of if */
3960: ipmx +=1;
3961: sw += weight[i];
3962: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3963: /*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 3964: if(globpr){
1.246 brouard 3965: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3966: %11.6f %11.6f %11.6f ", \
1.242 brouard 3967: 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 3968: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3969: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3970: llt +=ll[k]*gipmx/gsw;
3971: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3972: }
3973: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3974: }
1.232 brouard 3975: } /* end of wave */
3976: } /* end of individual */
3977: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3978: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3979: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3980: if(globpr==0){ /* First time we count the contributions and weights */
3981: gipmx=ipmx;
3982: gsw=sw;
3983: }
3984: return -l;
1.126 brouard 3985: }
3986:
3987:
3988: /*************** function likelione ***********/
1.292 brouard 3989: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 3990: {
3991: /* This routine should help understanding what is done with
3992: the selection of individuals/waves and
3993: to check the exact contribution to the likelihood.
3994: Plotting could be done.
3995: */
3996: int k;
3997:
3998: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3999: strcpy(fileresilk,"ILK_");
1.202 brouard 4000: strcat(fileresilk,fileresu);
1.126 brouard 4001: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4002: printf("Problem with resultfile: %s\n", fileresilk);
4003: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4004: }
1.214 brouard 4005: 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");
4006: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4007: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4008: for(k=1; k<=nlstate; k++)
4009: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
4010: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
4011: }
4012:
1.292 brouard 4013: *fretone=(*func)(p);
1.126 brouard 4014: if(*globpri !=0){
4015: fclose(ficresilk);
1.205 brouard 4016: if (mle ==0)
4017: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4018: else if(mle >=1)
4019: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4020: 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 4021: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4022:
4023: for (k=1; k<= nlstate ; k++) {
1.211 brouard 4024: 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 4025: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4026: }
1.207 brouard 4027: 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 4028: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4029: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 4030: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4031: fflush(fichtm);
1.205 brouard 4032: }
1.126 brouard 4033: return;
4034: }
4035:
4036:
4037: /*********** Maximum Likelihood Estimation ***************/
4038:
4039: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4040: {
1.165 brouard 4041: int i,j, iter=0;
1.126 brouard 4042: double **xi;
4043: double fret;
4044: double fretone; /* Only one call to likelihood */
4045: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 4046:
4047: #ifdef NLOPT
4048: int creturn;
4049: nlopt_opt opt;
4050: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4051: double *lb;
4052: double minf; /* the minimum objective value, upon return */
4053: double * p1; /* Shifted parameters from 0 instead of 1 */
4054: myfunc_data dinst, *d = &dinst;
4055: #endif
4056:
4057:
1.126 brouard 4058: xi=matrix(1,npar,1,npar);
4059: for (i=1;i<=npar;i++)
4060: for (j=1;j<=npar;j++)
4061: xi[i][j]=(i==j ? 1.0 : 0.0);
4062: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4063: strcpy(filerespow,"POW_");
1.126 brouard 4064: strcat(filerespow,fileres);
4065: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4066: printf("Problem with resultfile: %s\n", filerespow);
4067: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4068: }
4069: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4070: for (i=1;i<=nlstate;i++)
4071: for(j=1;j<=nlstate+ndeath;j++)
4072: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4073: fprintf(ficrespow,"\n");
1.162 brouard 4074: #ifdef POWELL
1.126 brouard 4075: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 4076: #endif
1.126 brouard 4077:
1.162 brouard 4078: #ifdef NLOPT
4079: #ifdef NEWUOA
4080: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
4081: #else
4082: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
4083: #endif
4084: lb=vector(0,npar-1);
4085: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
4086: nlopt_set_lower_bounds(opt, lb);
4087: nlopt_set_initial_step1(opt, 0.1);
4088:
4089: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
4090: d->function = func;
4091: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
4092: nlopt_set_min_objective(opt, myfunc, d);
4093: nlopt_set_xtol_rel(opt, ftol);
4094: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
4095: printf("nlopt failed! %d\n",creturn);
4096: }
4097: else {
4098: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
4099: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
4100: iter=1; /* not equal */
4101: }
4102: nlopt_destroy(opt);
4103: #endif
1.126 brouard 4104: free_matrix(xi,1,npar,1,npar);
4105: fclose(ficrespow);
1.203 brouard 4106: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4107: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4108: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4109:
4110: }
4111:
4112: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4113: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4114: {
4115: double **a,**y,*x,pd;
1.203 brouard 4116: /* double **hess; */
1.164 brouard 4117: int i, j;
1.126 brouard 4118: int *indx;
4119:
4120: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4121: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4122: void lubksb(double **a, int npar, int *indx, double b[]) ;
4123: void ludcmp(double **a, int npar, int *indx, double *d) ;
4124: double gompertz(double p[]);
1.203 brouard 4125: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4126:
4127: printf("\nCalculation of the hessian matrix. Wait...\n");
4128: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4129: for (i=1;i<=npar;i++){
1.203 brouard 4130: printf("%d-",i);fflush(stdout);
4131: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4132:
4133: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4134:
4135: /* printf(" %f ",p[i]);
4136: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4137: }
4138:
4139: for (i=1;i<=npar;i++) {
4140: for (j=1;j<=npar;j++) {
4141: if (j>i) {
1.203 brouard 4142: printf(".%d-%d",i,j);fflush(stdout);
4143: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4144: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4145:
4146: hess[j][i]=hess[i][j];
4147: /*printf(" %lf ",hess[i][j]);*/
4148: }
4149: }
4150: }
4151: printf("\n");
4152: fprintf(ficlog,"\n");
4153:
4154: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4155: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4156:
4157: a=matrix(1,npar,1,npar);
4158: y=matrix(1,npar,1,npar);
4159: x=vector(1,npar);
4160: indx=ivector(1,npar);
4161: for (i=1;i<=npar;i++)
4162: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4163: ludcmp(a,npar,indx,&pd);
4164:
4165: for (j=1;j<=npar;j++) {
4166: for (i=1;i<=npar;i++) x[i]=0;
4167: x[j]=1;
4168: lubksb(a,npar,indx,x);
4169: for (i=1;i<=npar;i++){
4170: matcov[i][j]=x[i];
4171: }
4172: }
4173:
4174: printf("\n#Hessian matrix#\n");
4175: fprintf(ficlog,"\n#Hessian matrix#\n");
4176: for (i=1;i<=npar;i++) {
4177: for (j=1;j<=npar;j++) {
1.203 brouard 4178: printf("%.6e ",hess[i][j]);
4179: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4180: }
4181: printf("\n");
4182: fprintf(ficlog,"\n");
4183: }
4184:
1.203 brouard 4185: /* printf("\n#Covariance matrix#\n"); */
4186: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4187: /* for (i=1;i<=npar;i++) { */
4188: /* for (j=1;j<=npar;j++) { */
4189: /* printf("%.6e ",matcov[i][j]); */
4190: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4191: /* } */
4192: /* printf("\n"); */
4193: /* fprintf(ficlog,"\n"); */
4194: /* } */
4195:
1.126 brouard 4196: /* Recompute Inverse */
1.203 brouard 4197: /* for (i=1;i<=npar;i++) */
4198: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4199: /* ludcmp(a,npar,indx,&pd); */
4200:
4201: /* printf("\n#Hessian matrix recomputed#\n"); */
4202:
4203: /* for (j=1;j<=npar;j++) { */
4204: /* for (i=1;i<=npar;i++) x[i]=0; */
4205: /* x[j]=1; */
4206: /* lubksb(a,npar,indx,x); */
4207: /* for (i=1;i<=npar;i++){ */
4208: /* y[i][j]=x[i]; */
4209: /* printf("%.3e ",y[i][j]); */
4210: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4211: /* } */
4212: /* printf("\n"); */
4213: /* fprintf(ficlog,"\n"); */
4214: /* } */
4215:
4216: /* Verifying the inverse matrix */
4217: #ifdef DEBUGHESS
4218: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4219:
1.203 brouard 4220: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4221: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4222:
4223: for (j=1;j<=npar;j++) {
4224: for (i=1;i<=npar;i++){
1.203 brouard 4225: printf("%.2f ",y[i][j]);
4226: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4227: }
4228: printf("\n");
4229: fprintf(ficlog,"\n");
4230: }
1.203 brouard 4231: #endif
1.126 brouard 4232:
4233: free_matrix(a,1,npar,1,npar);
4234: free_matrix(y,1,npar,1,npar);
4235: free_vector(x,1,npar);
4236: free_ivector(indx,1,npar);
1.203 brouard 4237: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4238:
4239:
4240: }
4241:
4242: /*************** hessian matrix ****************/
4243: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4244: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4245: int i;
4246: int l=1, lmax=20;
1.203 brouard 4247: double k1,k2, res, fx;
1.132 brouard 4248: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4249: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4250: int k=0,kmax=10;
4251: double l1;
4252:
4253: fx=func(x);
4254: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4255: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4256: l1=pow(10,l);
4257: delts=delt;
4258: for(k=1 ; k <kmax; k=k+1){
4259: delt = delta*(l1*k);
4260: p2[theta]=x[theta] +delt;
1.145 brouard 4261: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4262: p2[theta]=x[theta]-delt;
4263: k2=func(p2)-fx;
4264: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4265: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4266:
1.203 brouard 4267: #ifdef DEBUGHESSII
1.126 brouard 4268: 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);
4269: 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);
4270: #endif
4271: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4272: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4273: k=kmax;
4274: }
4275: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4276: k=kmax; l=lmax*10;
1.126 brouard 4277: }
4278: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4279: delts=delt;
4280: }
1.203 brouard 4281: } /* End loop k */
1.126 brouard 4282: }
4283: delti[theta]=delts;
4284: return res;
4285:
4286: }
4287:
1.203 brouard 4288: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4289: {
4290: int i;
1.164 brouard 4291: int l=1, lmax=20;
1.126 brouard 4292: double k1,k2,k3,k4,res,fx;
1.132 brouard 4293: double p2[MAXPARM+1];
1.203 brouard 4294: int k, kmax=1;
4295: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4296:
4297: int firstime=0;
1.203 brouard 4298:
1.126 brouard 4299: fx=func(x);
1.203 brouard 4300: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4301: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4302: p2[thetai]=x[thetai]+delti[thetai]*k;
4303: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4304: k1=func(p2)-fx;
4305:
1.203 brouard 4306: p2[thetai]=x[thetai]+delti[thetai]*k;
4307: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4308: k2=func(p2)-fx;
4309:
1.203 brouard 4310: p2[thetai]=x[thetai]-delti[thetai]*k;
4311: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4312: k3=func(p2)-fx;
4313:
1.203 brouard 4314: p2[thetai]=x[thetai]-delti[thetai]*k;
4315: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4316: k4=func(p2)-fx;
1.203 brouard 4317: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4318: if(k1*k2*k3*k4 <0.){
1.208 brouard 4319: firstime=1;
1.203 brouard 4320: kmax=kmax+10;
1.208 brouard 4321: }
4322: if(kmax >=10 || firstime ==1){
1.246 brouard 4323: 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);
4324: 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 4325: 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);
4326: 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);
4327: }
4328: #ifdef DEBUGHESSIJ
4329: v1=hess[thetai][thetai];
4330: v2=hess[thetaj][thetaj];
4331: cv12=res;
4332: /* Computing eigen value of Hessian matrix */
4333: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4334: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4335: if ((lc2 <0) || (lc1 <0) ){
4336: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4337: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4338: 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);
4339: 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);
4340: }
1.126 brouard 4341: #endif
4342: }
4343: return res;
4344: }
4345:
1.203 brouard 4346: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4347: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4348: /* { */
4349: /* int i; */
4350: /* int l=1, lmax=20; */
4351: /* double k1,k2,k3,k4,res,fx; */
4352: /* double p2[MAXPARM+1]; */
4353: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4354: /* int k=0,kmax=10; */
4355: /* double l1; */
4356:
4357: /* fx=func(x); */
4358: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4359: /* l1=pow(10,l); */
4360: /* delts=delt; */
4361: /* for(k=1 ; k <kmax; k=k+1){ */
4362: /* delt = delti*(l1*k); */
4363: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4364: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4365: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4366: /* k1=func(p2)-fx; */
4367:
4368: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4369: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4370: /* k2=func(p2)-fx; */
4371:
4372: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4373: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4374: /* k3=func(p2)-fx; */
4375:
4376: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4377: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4378: /* k4=func(p2)-fx; */
4379: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4380: /* #ifdef DEBUGHESSIJ */
4381: /* 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); */
4382: /* 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); */
4383: /* #endif */
4384: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4385: /* k=kmax; */
4386: /* } */
4387: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4388: /* k=kmax; l=lmax*10; */
4389: /* } */
4390: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4391: /* delts=delt; */
4392: /* } */
4393: /* } /\* End loop k *\/ */
4394: /* } */
4395: /* delti[theta]=delts; */
4396: /* return res; */
4397: /* } */
4398:
4399:
1.126 brouard 4400: /************** Inverse of matrix **************/
4401: void ludcmp(double **a, int n, int *indx, double *d)
4402: {
4403: int i,imax,j,k;
4404: double big,dum,sum,temp;
4405: double *vv;
4406:
4407: vv=vector(1,n);
4408: *d=1.0;
4409: for (i=1;i<=n;i++) {
4410: big=0.0;
4411: for (j=1;j<=n;j++)
4412: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4413: if (big == 0.0){
4414: printf(" Singular Hessian matrix at row %d:\n",i);
4415: for (j=1;j<=n;j++) {
4416: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4417: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4418: }
4419: fflush(ficlog);
4420: fclose(ficlog);
4421: nrerror("Singular matrix in routine ludcmp");
4422: }
1.126 brouard 4423: vv[i]=1.0/big;
4424: }
4425: for (j=1;j<=n;j++) {
4426: for (i=1;i<j;i++) {
4427: sum=a[i][j];
4428: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4429: a[i][j]=sum;
4430: }
4431: big=0.0;
4432: for (i=j;i<=n;i++) {
4433: sum=a[i][j];
4434: for (k=1;k<j;k++)
4435: sum -= a[i][k]*a[k][j];
4436: a[i][j]=sum;
4437: if ( (dum=vv[i]*fabs(sum)) >= big) {
4438: big=dum;
4439: imax=i;
4440: }
4441: }
4442: if (j != imax) {
4443: for (k=1;k<=n;k++) {
4444: dum=a[imax][k];
4445: a[imax][k]=a[j][k];
4446: a[j][k]=dum;
4447: }
4448: *d = -(*d);
4449: vv[imax]=vv[j];
4450: }
4451: indx[j]=imax;
4452: if (a[j][j] == 0.0) a[j][j]=TINY;
4453: if (j != n) {
4454: dum=1.0/(a[j][j]);
4455: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4456: }
4457: }
4458: free_vector(vv,1,n); /* Doesn't work */
4459: ;
4460: }
4461:
4462: void lubksb(double **a, int n, int *indx, double b[])
4463: {
4464: int i,ii=0,ip,j;
4465: double sum;
4466:
4467: for (i=1;i<=n;i++) {
4468: ip=indx[i];
4469: sum=b[ip];
4470: b[ip]=b[i];
4471: if (ii)
4472: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4473: else if (sum) ii=i;
4474: b[i]=sum;
4475: }
4476: for (i=n;i>=1;i--) {
4477: sum=b[i];
4478: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4479: b[i]=sum/a[i][i];
4480: }
4481: }
4482:
4483: void pstamp(FILE *fichier)
4484: {
1.196 brouard 4485: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4486: }
4487:
1.297 brouard 4488: void date2dmy(double date,double *day, double *month, double *year){
4489: double yp=0., yp1=0., yp2=0.;
4490:
4491: yp1=modf(date,&yp);/* extracts integral of date in yp and
4492: fractional in yp1 */
4493: *year=yp;
4494: yp2=modf((yp1*12),&yp);
4495: *month=yp;
4496: yp1=modf((yp2*30.5),&yp);
4497: *day=yp;
4498: if(*day==0) *day=1;
4499: if(*month==0) *month=1;
4500: }
4501:
1.253 brouard 4502:
4503:
1.126 brouard 4504: /************ Frequencies ********************/
1.251 brouard 4505: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4506: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4507: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4508: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4509:
1.265 brouard 4510: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4511: int iind=0, iage=0;
4512: int mi; /* Effective wave */
4513: int first;
4514: double ***freq; /* Frequencies */
1.268 brouard 4515: 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 */
4516: 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 4517: double *meanq, *stdq, *idq;
1.226 brouard 4518: double **meanqt;
4519: double *pp, **prop, *posprop, *pospropt;
4520: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4521: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4522: double agebegin, ageend;
4523:
4524: pp=vector(1,nlstate);
1.251 brouard 4525: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4526: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4527: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4528: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4529: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4530: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4531: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4532: meanqt=matrix(1,lastpass,1,nqtveff);
4533: strcpy(fileresp,"P_");
4534: strcat(fileresp,fileresu);
4535: /*strcat(fileresphtm,fileresu);*/
4536: if((ficresp=fopen(fileresp,"w"))==NULL) {
4537: printf("Problem with prevalence resultfile: %s\n", fileresp);
4538: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4539: exit(0);
4540: }
1.240 brouard 4541:
1.226 brouard 4542: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4543: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4544: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4545: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4546: fflush(ficlog);
4547: exit(70);
4548: }
4549: else{
4550: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4551: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4552: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4553: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4554: }
1.237 brouard 4555: fprintf(ficresphtm,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>Frequencies and prevalence by age at begin of transition and dummy covariate value at beginning of transition</h4>\n",fileresphtm, fileresphtm);
1.240 brouard 4556:
1.226 brouard 4557: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4558: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4559: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4560: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4561: fflush(ficlog);
4562: exit(70);
1.240 brouard 4563: } else{
1.226 brouard 4564: fprintf(ficresphtmfr,"<html><head>\n<title>IMaCh PHTM_Frequency table %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4565: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4566: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4567: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4568: }
1.240 brouard 4569: fprintf(ficresphtmfr,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>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);
4570:
1.253 brouard 4571: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4572: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4573: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4574: j1=0;
1.126 brouard 4575:
1.227 brouard 4576: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4577: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4578: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4579:
4580:
1.226 brouard 4581: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4582: reference=low_education V1=0,V2=0
4583: med_educ V1=1 V2=0,
4584: high_educ V1=0 V2=1
4585: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4586: */
1.249 brouard 4587: dateintsum=0;
4588: k2cpt=0;
4589:
1.253 brouard 4590: if(cptcoveff == 0 )
1.265 brouard 4591: nl=1; /* Constant and age model only */
1.253 brouard 4592: else
4593: nl=2;
1.265 brouard 4594:
4595: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4596: /* Loop on nj=1 or 2 if dummy covariates j!=0
4597: * Loop on j1(1 to 2**cptcoveff) covariate combination
4598: * freq[s1][s2][iage] =0.
4599: * Loop on iind
4600: * ++freq[s1][s2][iage] weighted
4601: * end iind
4602: * if covariate and j!0
4603: * headers Variable on one line
4604: * endif cov j!=0
4605: * header of frequency table by age
4606: * Loop on age
4607: * pp[s1]+=freq[s1][s2][iage] weighted
4608: * pos+=freq[s1][s2][iage] weighted
4609: * Loop on s1 initial state
4610: * fprintf(ficresp
4611: * end s1
4612: * end age
4613: * if j!=0 computes starting values
4614: * end compute starting values
4615: * end j1
4616: * end nl
4617: */
1.253 brouard 4618: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4619: if(nj==1)
4620: j=0; /* First pass for the constant */
1.265 brouard 4621: else{
1.253 brouard 4622: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4623: }
1.251 brouard 4624: first=1;
1.265 brouard 4625: 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 4626: posproptt=0.;
4627: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4628: scanf("%d", i);*/
4629: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4630: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4631: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4632: freq[i][s2][m]=0;
1.251 brouard 4633:
4634: for (i=1; i<=nlstate; i++) {
1.240 brouard 4635: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4636: prop[i][m]=0;
4637: posprop[i]=0;
4638: pospropt[i]=0;
4639: }
1.283 brouard 4640: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4641: idq[z1]=0.;
4642: meanq[z1]=0.;
4643: stdq[z1]=0.;
1.283 brouard 4644: }
4645: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4646: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4647: /* meanqt[m][z1]=0.; */
4648: /* } */
4649: /* } */
1.251 brouard 4650: /* dateintsum=0; */
4651: /* k2cpt=0; */
4652:
1.265 brouard 4653: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4654: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4655: bool=1;
4656: if(j !=0){
4657: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4658: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4659: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4660: /* if(Tvaraff[z1] ==-20){ */
4661: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4662: /* }else if(Tvaraff[z1] ==-10){ */
4663: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4664: /* }else */
4665: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4666: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4667: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4668: /* 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",
4669: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4670: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4671: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4672: } /* Onlyf fixed */
4673: } /* end z1 */
4674: } /* cptcovn > 0 */
4675: } /* end any */
4676: }/* end j==0 */
1.265 brouard 4677: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4678: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4679: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4680: m=mw[mi][iind];
4681: if(j!=0){
4682: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4683: for (z1=1; z1<=cptcoveff; z1++) {
4684: if( Fixed[Tmodelind[z1]]==1){
4685: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4686: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4687: value is -1, we don't select. It differs from the
4688: constant and age model which counts them. */
4689: bool=0; /* not selected */
4690: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4691: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4692: bool=0;
4693: }
4694: }
4695: }
4696: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4697: } /* end j==0 */
4698: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4699: if(bool==1){ /*Selected */
1.251 brouard 4700: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4701: and mw[mi+1][iind]. dh depends on stepm. */
4702: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4703: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4704: if(m >=firstpass && m <=lastpass){
4705: k2=anint[m][iind]+(mint[m][iind]/12.);
4706: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4707: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4708: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4709: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4710: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4711: if (m<lastpass) {
4712: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4713: /* 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]); */
4714: if(s[m][iind]==-1)
4715: 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.));
4716: 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 4717: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
4718: if(!isnan(covar[ncovcol+z1][iind])){
4719: idq[z1]=idq[z1]+weight[iind];
4720: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
4721: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
4722: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
4723: }
1.284 brouard 4724: }
1.251 brouard 4725: /* if((int)agev[m][iind] == 55) */
4726: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4727: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4728: 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 4729: }
1.251 brouard 4730: } /* end if between passes */
4731: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4732: dateintsum=dateintsum+k2; /* on all covariates ?*/
4733: k2cpt++;
4734: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4735: }
1.251 brouard 4736: }else{
4737: bool=1;
4738: }/* end bool 2 */
4739: } /* end m */
1.284 brouard 4740: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
4741: /* idq[z1]=idq[z1]+weight[iind]; */
4742: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
4743: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
4744: /* } */
1.251 brouard 4745: } /* end bool */
4746: } /* end iind = 1 to imx */
4747: /* prop[s][age] is feeded for any initial and valid live state as well as
4748: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4749:
4750:
4751: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4752: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4753: pstamp(ficresp);
1.251 brouard 4754: if (cptcoveff>0 && j!=0){
1.265 brouard 4755: pstamp(ficresp);
1.251 brouard 4756: printf( "\n#********** Variable ");
4757: fprintf(ficresp, "\n#********** Variable ");
4758: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4759: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4760: fprintf(ficlog, "\n#********** Variable ");
4761: for (z1=1; z1<=cptcoveff; z1++){
4762: if(!FixedV[Tvaraff[z1]]){
4763: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4764: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4765: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4766: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4767: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4768: }else{
1.251 brouard 4769: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4770: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4771: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4772: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4773: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4774: }
4775: }
4776: printf( "**********\n#");
4777: fprintf(ficresp, "**********\n#");
4778: fprintf(ficresphtm, "**********</h3>\n");
4779: fprintf(ficresphtmfr, "**********</h3>\n");
4780: fprintf(ficlog, "**********\n");
4781: }
1.284 brouard 4782: /*
4783: Printing means of quantitative variables if any
4784: */
4785: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 4786: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 4787: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 4788: if(weightopt==1){
4789: printf(" Weighted mean and standard deviation of");
4790: fprintf(ficlog," Weighted mean and standard deviation of");
4791: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
4792: }
1.311 brouard 4793: /* mu = \frac{w x}{\sum w}
4794: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
4795: */
4796: 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]));
4797: 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]));
4798: 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 4799: }
4800: /* for (z1=1; z1<= nqtveff; z1++) { */
4801: /* for(m=1;m<=lastpass;m++){ */
4802: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
4803: /* } */
4804: /* } */
1.283 brouard 4805:
1.251 brouard 4806: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4807: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4808: fprintf(ficresp, " Age");
4809: 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 4810: for(i=1; i<=nlstate;i++) {
1.265 brouard 4811: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4812: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4813: }
1.265 brouard 4814: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4815: fprintf(ficresphtm, "\n");
4816:
4817: /* Header of frequency table by age */
4818: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4819: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4820: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4821: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4822: if(s2!=0 && m!=0)
4823: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4824: }
1.226 brouard 4825: }
1.251 brouard 4826: fprintf(ficresphtmfr, "\n");
4827:
4828: /* For each age */
4829: for(iage=iagemin; iage <= iagemax+3; iage++){
4830: fprintf(ficresphtm,"<tr>");
4831: if(iage==iagemax+1){
4832: fprintf(ficlog,"1");
4833: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4834: }else if(iage==iagemax+2){
4835: fprintf(ficlog,"0");
4836: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4837: }else if(iage==iagemax+3){
4838: fprintf(ficlog,"Total");
4839: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4840: }else{
1.240 brouard 4841: if(first==1){
1.251 brouard 4842: first=0;
4843: printf("See log file for details...\n");
4844: }
4845: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4846: fprintf(ficlog,"Age %d", iage);
4847: }
1.265 brouard 4848: for(s1=1; s1 <=nlstate ; s1++){
4849: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4850: pp[s1] += freq[s1][m][iage];
1.251 brouard 4851: }
1.265 brouard 4852: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4853: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4854: pos += freq[s1][m][iage];
4855: if(pp[s1]>=1.e-10){
1.251 brouard 4856: if(first==1){
1.265 brouard 4857: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4858: }
1.265 brouard 4859: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4860: }else{
4861: if(first==1)
1.265 brouard 4862: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4863: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4864: }
4865: }
4866:
1.265 brouard 4867: for(s1=1; s1 <=nlstate ; s1++){
4868: /* posprop[s1]=0; */
4869: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4870: pp[s1] += freq[s1][m][iage];
4871: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4872:
4873: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4874: pos += pp[s1]; /* pos is the total number of transitions until this age */
4875: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4876: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4877: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4878: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4879: }
4880:
4881: /* Writing ficresp */
4882: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4883: if( iage <= iagemax){
4884: fprintf(ficresp," %d",iage);
4885: }
4886: }else if( nj==2){
4887: if( iage <= iagemax){
4888: fprintf(ficresp," %d",iage);
4889: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4890: }
1.240 brouard 4891: }
1.265 brouard 4892: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4893: if(pos>=1.e-5){
1.251 brouard 4894: if(first==1)
1.265 brouard 4895: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4896: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4897: }else{
4898: if(first==1)
1.265 brouard 4899: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4900: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4901: }
4902: if( iage <= iagemax){
4903: if(pos>=1.e-5){
1.265 brouard 4904: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4905: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4906: }else if( nj==2){
4907: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4908: }
4909: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4910: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4911: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4912: } else{
4913: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4914: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4915: }
1.240 brouard 4916: }
1.265 brouard 4917: pospropt[s1] +=posprop[s1];
4918: } /* end loop s1 */
1.251 brouard 4919: /* pospropt=0.; */
1.265 brouard 4920: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4921: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4922: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4923: if(first==1){
1.265 brouard 4924: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4925: }
1.265 brouard 4926: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4927: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4928: }
1.265 brouard 4929: if(s1!=0 && m!=0)
4930: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4931: }
1.265 brouard 4932: } /* end loop s1 */
1.251 brouard 4933: posproptt=0.;
1.265 brouard 4934: for(s1=1; s1 <=nlstate; s1++){
4935: posproptt += pospropt[s1];
1.251 brouard 4936: }
4937: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4938: fprintf(ficresphtm,"</tr>\n");
4939: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4940: if(iage <= iagemax)
4941: fprintf(ficresp,"\n");
1.240 brouard 4942: }
1.251 brouard 4943: if(first==1)
4944: printf("Others in log...\n");
4945: fprintf(ficlog,"\n");
4946: } /* end loop age iage */
1.265 brouard 4947:
1.251 brouard 4948: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4949: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4950: if(posproptt < 1.e-5){
1.265 brouard 4951: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4952: }else{
1.265 brouard 4953: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4954: }
1.226 brouard 4955: }
1.251 brouard 4956: fprintf(ficresphtm,"</tr>\n");
4957: fprintf(ficresphtm,"</table>\n");
4958: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4959: if(posproptt < 1.e-5){
1.251 brouard 4960: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4961: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4962: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4963: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4964: invalidvarcomb[j1]=1;
1.226 brouard 4965: }else{
1.251 brouard 4966: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4967: invalidvarcomb[j1]=0;
1.226 brouard 4968: }
1.251 brouard 4969: fprintf(ficresphtmfr,"</table>\n");
4970: fprintf(ficlog,"\n");
4971: if(j!=0){
4972: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4973: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4974: for(k=1; k <=(nlstate+ndeath); k++){
4975: if (k != i) {
1.265 brouard 4976: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4977: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4978: if(j1==1){ /* All dummy covariates to zero */
4979: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4980: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4981: printf("%d%d ",i,k);
4982: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4983: 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]));
4984: 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]));
4985: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4986: }
1.253 brouard 4987: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4988: for(iage=iagemin; iage <= iagemax+3; iage++){
4989: x[iage]= (double)iage;
4990: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4991: /* 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 4992: }
1.268 brouard 4993: /* Some are not finite, but linreg will ignore these ages */
4994: no=0;
1.253 brouard 4995: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4996: pstart[s1]=b;
4997: pstart[s1-1]=a;
1.252 brouard 4998: }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 */
4999: 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]);
5000: 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 5001: 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 5002: printf("%d%d ",i,k);
5003: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5004: 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 5005: }else{ /* Other cases, like quantitative fixed or varying covariates */
5006: ;
5007: }
5008: /* printf("%12.7f )", param[i][jj][k]); */
5009: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5010: s1++;
1.251 brouard 5011: } /* end jj */
5012: } /* end k!= i */
5013: } /* end k */
1.265 brouard 5014: } /* end i, s1 */
1.251 brouard 5015: } /* end j !=0 */
5016: } /* end selected combination of covariate j1 */
5017: if(j==0){ /* We can estimate starting values from the occurences in each case */
5018: printf("#Freqsummary: Starting values for the constants:\n");
5019: fprintf(ficlog,"\n");
1.265 brouard 5020: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5021: for(k=1; k <=(nlstate+ndeath); k++){
5022: if (k != i) {
5023: printf("%d%d ",i,k);
5024: fprintf(ficlog,"%d%d ",i,k);
5025: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 5026: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 5027: if(jj==1){ /* Age has to be done */
1.265 brouard 5028: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
5029: 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]));
5030: 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 5031: }
5032: /* printf("%12.7f )", param[i][jj][k]); */
5033: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5034: s1++;
1.250 brouard 5035: }
1.251 brouard 5036: printf("\n");
5037: fprintf(ficlog,"\n");
1.250 brouard 5038: }
5039: }
1.284 brouard 5040: } /* end of state i */
1.251 brouard 5041: printf("#Freqsummary\n");
5042: fprintf(ficlog,"\n");
1.265 brouard 5043: for(s1=-1; s1 <=nlstate+ndeath; s1++){
5044: for(s2=-1; s2 <=nlstate+ndeath; s2++){
5045: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
5046: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5047: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
5048: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
5049: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
5050: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 5051: /* } */
5052: }
1.265 brouard 5053: } /* end loop s1 */
1.251 brouard 5054:
5055: printf("\n");
5056: fprintf(ficlog,"\n");
5057: } /* end j=0 */
1.249 brouard 5058: } /* end j */
1.252 brouard 5059:
1.253 brouard 5060: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 5061: for(i=1, jk=1; i <=nlstate; i++){
5062: for(j=1; j <=nlstate+ndeath; j++){
5063: if(j!=i){
5064: /*ca[0]= k+'a'-1;ca[1]='\0';*/
5065: printf("%1d%1d",i,j);
5066: fprintf(ficparo,"%1d%1d",i,j);
5067: for(k=1; k<=ncovmodel;k++){
5068: /* printf(" %lf",param[i][j][k]); */
5069: /* fprintf(ficparo," %lf",param[i][j][k]); */
5070: p[jk]=pstart[jk];
5071: printf(" %f ",pstart[jk]);
5072: fprintf(ficparo," %f ",pstart[jk]);
5073: jk++;
5074: }
5075: printf("\n");
5076: fprintf(ficparo,"\n");
5077: }
5078: }
5079: }
5080: } /* end mle=-2 */
1.226 brouard 5081: dateintmean=dateintsum/k2cpt;
1.296 brouard 5082: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 5083:
1.226 brouard 5084: fclose(ficresp);
5085: fclose(ficresphtm);
5086: fclose(ficresphtmfr);
1.283 brouard 5087: free_vector(idq,1,nqfveff);
1.226 brouard 5088: free_vector(meanq,1,nqfveff);
1.284 brouard 5089: free_vector(stdq,1,nqfveff);
1.226 brouard 5090: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 5091: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
5092: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 5093: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5094: free_vector(pospropt,1,nlstate);
5095: free_vector(posprop,1,nlstate);
1.251 brouard 5096: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 5097: free_vector(pp,1,nlstate);
5098: /* End of freqsummary */
5099: }
1.126 brouard 5100:
1.268 brouard 5101: /* Simple linear regression */
5102: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
5103:
5104: /* y=a+bx regression */
5105: double sumx = 0.0; /* sum of x */
5106: double sumx2 = 0.0; /* sum of x**2 */
5107: double sumxy = 0.0; /* sum of x * y */
5108: double sumy = 0.0; /* sum of y */
5109: double sumy2 = 0.0; /* sum of y**2 */
5110: double sume2 = 0.0; /* sum of square or residuals */
5111: double yhat;
5112:
5113: double denom=0;
5114: int i;
5115: int ne=*no;
5116:
5117: for ( i=ifi, ne=0;i<=ila;i++) {
5118: if(!isfinite(x[i]) || !isfinite(y[i])){
5119: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5120: continue;
5121: }
5122: ne=ne+1;
5123: sumx += x[i];
5124: sumx2 += x[i]*x[i];
5125: sumxy += x[i] * y[i];
5126: sumy += y[i];
5127: sumy2 += y[i]*y[i];
5128: denom = (ne * sumx2 - sumx*sumx);
5129: /* 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); */
5130: }
5131:
5132: denom = (ne * sumx2 - sumx*sumx);
5133: if (denom == 0) {
5134: // vertical, slope m is infinity
5135: *b = INFINITY;
5136: *a = 0;
5137: if (r) *r = 0;
5138: return 1;
5139: }
5140:
5141: *b = (ne * sumxy - sumx * sumy) / denom;
5142: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5143: if (r!=NULL) {
5144: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5145: sqrt((sumx2 - sumx*sumx/ne) *
5146: (sumy2 - sumy*sumy/ne));
5147: }
5148: *no=ne;
5149: for ( i=ifi, ne=0;i<=ila;i++) {
5150: if(!isfinite(x[i]) || !isfinite(y[i])){
5151: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5152: continue;
5153: }
5154: ne=ne+1;
5155: yhat = y[i] - *a -*b* x[i];
5156: sume2 += yhat * yhat ;
5157:
5158: denom = (ne * sumx2 - sumx*sumx);
5159: /* 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); */
5160: }
5161: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5162: *sa= *sb * sqrt(sumx2/ne);
5163:
5164: return 0;
5165: }
5166:
1.126 brouard 5167: /************ Prevalence ********************/
1.227 brouard 5168: 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)
5169: {
5170: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5171: in each health status at the date of interview (if between dateprev1 and dateprev2).
5172: We still use firstpass and lastpass as another selection.
5173: */
1.126 brouard 5174:
1.227 brouard 5175: int i, m, jk, j1, bool, z1,j, iv;
5176: int mi; /* Effective wave */
5177: int iage;
5178: double agebegin, ageend;
5179:
5180: double **prop;
5181: double posprop;
5182: double y2; /* in fractional years */
5183: int iagemin, iagemax;
5184: int first; /** to stop verbosity which is redirected to log file */
5185:
5186: iagemin= (int) agemin;
5187: iagemax= (int) agemax;
5188: /*pp=vector(1,nlstate);*/
1.251 brouard 5189: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5190: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5191: j1=0;
1.222 brouard 5192:
1.227 brouard 5193: /*j=cptcoveff;*/
5194: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5195:
1.288 brouard 5196: first=0;
1.227 brouard 5197: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5198: for (i=1; i<=nlstate; i++)
1.251 brouard 5199: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5200: prop[i][iage]=0.0;
5201: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5202: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5203: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5204:
5205: for (i=1; i<=imx; i++) { /* Each individual */
5206: bool=1;
5207: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5208: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5209: m=mw[mi][i];
5210: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5211: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5212: for (z1=1; z1<=cptcoveff; z1++){
5213: if( Fixed[Tmodelind[z1]]==1){
5214: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5215: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5216: bool=0;
5217: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5218: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5219: bool=0;
5220: }
5221: }
5222: if(bool==1){ /* Otherwise we skip that wave/person */
5223: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5224: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5225: if(m >=firstpass && m <=lastpass){
5226: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5227: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5228: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5229: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5230: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5231: 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);
5232: exit(1);
5233: }
5234: if (s[m][i]>0 && s[m][i]<=nlstate) {
5235: /*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]]);*/
5236: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5237: prop[s[m][i]][iagemax+3] += weight[i];
5238: } /* end valid statuses */
5239: } /* end selection of dates */
5240: } /* end selection of waves */
5241: } /* end bool */
5242: } /* end wave */
5243: } /* end individual */
5244: for(i=iagemin; i <= iagemax+3; i++){
5245: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5246: posprop += prop[jk][i];
5247: }
5248:
5249: for(jk=1; jk <=nlstate ; jk++){
5250: if( i <= iagemax){
5251: if(posprop>=1.e-5){
5252: probs[i][jk][j1]= prop[jk][i]/posprop;
5253: } else{
1.288 brouard 5254: if(!first){
5255: first=1;
1.266 brouard 5256: 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]);
5257: }else{
1.288 brouard 5258: 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 5259: }
5260: }
5261: }
5262: }/* end jk */
5263: }/* end i */
1.222 brouard 5264: /*} *//* end i1 */
1.227 brouard 5265: } /* end j1 */
1.222 brouard 5266:
1.227 brouard 5267: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5268: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5269: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5270: } /* End of prevalence */
1.126 brouard 5271:
5272: /************* Waves Concatenation ***************/
5273:
5274: 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)
5275: {
1.298 brouard 5276: /* 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 5277: Death is a valid wave (if date is known).
5278: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5279: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 5280: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 5281: */
1.126 brouard 5282:
1.224 brouard 5283: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5284: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5285: double sum=0., jmean=0.;*/
1.224 brouard 5286: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5287: int j, k=0,jk, ju, jl;
5288: double sum=0.;
5289: first=0;
1.214 brouard 5290: firstwo=0;
1.217 brouard 5291: firsthree=0;
1.218 brouard 5292: firstfour=0;
1.164 brouard 5293: jmin=100000;
1.126 brouard 5294: jmax=-1;
5295: jmean=0.;
1.224 brouard 5296:
5297: /* Treating live states */
1.214 brouard 5298: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5299: mi=0; /* First valid wave */
1.227 brouard 5300: mli=0; /* Last valid wave */
1.309 brouard 5301: m=firstpass; /* Loop on waves */
5302: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 5303: 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 */
5304: mli=m-1;/* mw[++mi][i]=m-1; */
5305: }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 5306: 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 5307: mli=m;
1.224 brouard 5308: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5309: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5310: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5311: }
1.309 brouard 5312: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 5313: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5314: break;
1.224 brouard 5315: #else
1.309 brouard 5316: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){ /* case -2 (vital status unknown is warned later */
1.227 brouard 5317: if(firsthree == 0){
1.302 brouard 5318: 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 5319: firsthree=1;
5320: }
1.302 brouard 5321: 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);
1.309 brouard 5322: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 5323: mli=m;
5324: }
5325: if(s[m][i]==-2){ /* Vital status is really unknown */
5326: nbwarn++;
1.309 brouard 5327: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 5328: 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);
5329: 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);
5330: }
5331: break;
5332: }
5333: break;
1.224 brouard 5334: #endif
1.227 brouard 5335: }/* End m >= lastpass */
1.126 brouard 5336: }/* end while */
1.224 brouard 5337:
1.227 brouard 5338: /* 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 5339: /* After last pass */
1.224 brouard 5340: /* Treating death states */
1.214 brouard 5341: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5342: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5343: /* } */
1.126 brouard 5344: mi++; /* Death is another wave */
5345: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5346: /* Only death is a correct wave */
1.126 brouard 5347: mw[mi][i]=m;
1.257 brouard 5348: } /* else not in a death state */
1.224 brouard 5349: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5350: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5351: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 5352: 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 5353: nbwarn++;
5354: if(firstfiv==0){
1.309 brouard 5355: 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 5356: firstfiv=1;
5357: }else{
1.309 brouard 5358: 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 5359: }
1.309 brouard 5360: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
5361: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 5362: nberr++;
5363: if(firstwo==0){
1.309 brouard 5364: 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 5365: firstwo=1;
5366: }
1.309 brouard 5367: 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 5368: }
1.257 brouard 5369: }else{ /* if date of interview is unknown */
1.227 brouard 5370: /* death is known but not confirmed by death status at any wave */
5371: if(firstfour==0){
1.309 brouard 5372: 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 5373: firstfour=1;
5374: }
1.309 brouard 5375: 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 5376: }
1.224 brouard 5377: } /* end if date of death is known */
5378: #endif
1.309 brouard 5379: wav[i]=mi; /* mi should be the last effective wave (or mli), */
5380: /* wav[i]=mw[mi][i]; */
1.126 brouard 5381: if(mi==0){
5382: nbwarn++;
5383: if(first==0){
1.227 brouard 5384: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5385: first=1;
1.126 brouard 5386: }
5387: if(first==1){
1.227 brouard 5388: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5389: }
5390: } /* end mi==0 */
5391: } /* End individuals */
1.214 brouard 5392: /* wav and mw are no more changed */
1.223 brouard 5393:
1.214 brouard 5394:
1.126 brouard 5395: for(i=1; i<=imx; i++){
5396: for(mi=1; mi<wav[i];mi++){
5397: if (stepm <=0)
1.227 brouard 5398: dh[mi][i]=1;
1.126 brouard 5399: else{
1.260 brouard 5400: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5401: if (agedc[i] < 2*AGESUP) {
5402: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5403: if(j==0) j=1; /* Survives at least one month after exam */
5404: else if(j<0){
5405: nberr++;
5406: 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]);
5407: j=1; /* Temporary Dangerous patch */
5408: 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);
5409: 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]);
5410: 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);
5411: }
5412: k=k+1;
5413: if (j >= jmax){
5414: jmax=j;
5415: ijmax=i;
5416: }
5417: if (j <= jmin){
5418: jmin=j;
5419: ijmin=i;
5420: }
5421: sum=sum+j;
5422: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5423: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5424: }
5425: }
5426: else{
5427: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5428: /* 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 5429:
1.227 brouard 5430: k=k+1;
5431: if (j >= jmax) {
5432: jmax=j;
5433: ijmax=i;
5434: }
5435: else if (j <= jmin){
5436: jmin=j;
5437: ijmin=i;
5438: }
5439: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5440: /*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]);*/
5441: if(j<0){
5442: nberr++;
5443: 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]);
5444: 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]);
5445: }
5446: sum=sum+j;
5447: }
5448: jk= j/stepm;
5449: jl= j -jk*stepm;
5450: ju= j -(jk+1)*stepm;
5451: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5452: if(jl==0){
5453: dh[mi][i]=jk;
5454: bh[mi][i]=0;
5455: }else{ /* We want a negative bias in order to only have interpolation ie
5456: * to avoid the price of an extra matrix product in likelihood */
5457: dh[mi][i]=jk+1;
5458: bh[mi][i]=ju;
5459: }
5460: }else{
5461: if(jl <= -ju){
5462: dh[mi][i]=jk;
5463: bh[mi][i]=jl; /* bias is positive if real duration
5464: * is higher than the multiple of stepm and negative otherwise.
5465: */
5466: }
5467: else{
5468: dh[mi][i]=jk+1;
5469: bh[mi][i]=ju;
5470: }
5471: if(dh[mi][i]==0){
5472: dh[mi][i]=1; /* At least one step */
5473: bh[mi][i]=ju; /* At least one step */
5474: /* 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);*/
5475: }
5476: } /* end if mle */
1.126 brouard 5477: }
5478: } /* end wave */
5479: }
5480: jmean=sum/k;
5481: 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 5482: 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 5483: }
1.126 brouard 5484:
5485: /*********** Tricode ****************************/
1.220 brouard 5486: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5487: {
5488: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5489: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5490: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5491: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5492: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5493: */
1.130 brouard 5494:
1.242 brouard 5495: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5496: int modmaxcovj=0; /* Modality max of covariates j */
5497: int cptcode=0; /* Modality max of covariates j */
5498: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5499:
5500:
1.242 brouard 5501: /* cptcoveff=0; */
5502: /* *cptcov=0; */
1.126 brouard 5503:
1.242 brouard 5504: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5505: for (k=1; k <= maxncov; k++)
5506: for(j=1; j<=2; j++)
5507: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5508:
1.242 brouard 5509: /* Loop on covariates without age and products and no quantitative variable */
5510: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5511: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5512: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5513: switch(Fixed[k]) {
5514: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 5515: modmaxcovj=0;
5516: modmincovj=0;
1.242 brouard 5517: 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*/
5518: ij=(int)(covar[Tvar[k]][i]);
5519: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5520: * If product of Vn*Vm, still boolean *:
5521: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5522: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5523: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5524: modality of the nth covariate of individual i. */
5525: if (ij > modmaxcovj)
5526: modmaxcovj=ij;
5527: else if (ij < modmincovj)
5528: modmincovj=ij;
1.287 brouard 5529: if (ij <0 || ij >1 ){
1.311 brouard 5530: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5531: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
5532: fflush(ficlog);
5533: exit(1);
1.287 brouard 5534: }
5535: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5536: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5537: exit(1);
5538: }else
5539: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5540: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5541: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5542: /* getting the maximum value of the modality of the covariate
5543: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5544: female ies 1, then modmaxcovj=1.
5545: */
5546: } /* end for loop on individuals i */
5547: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5548: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5549: cptcode=modmaxcovj;
5550: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5551: /*for (i=0; i<=cptcode; i++) {*/
5552: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5553: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5554: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5555: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5556: if( j != -1){
5557: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5558: covariate for which somebody answered excluding
5559: undefined. Usually 2: 0 and 1. */
5560: }
5561: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5562: covariate for which somebody answered including
5563: undefined. Usually 3: -1, 0 and 1. */
5564: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5565: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5566: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5567:
1.242 brouard 5568: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5569: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5570: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5571: /* modmincovj=3; modmaxcovj = 7; */
5572: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5573: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5574: /* defining two dummy variables: variables V1_1 and V1_2.*/
5575: /* nbcode[Tvar[j]][ij]=k; */
5576: /* nbcode[Tvar[j]][1]=0; */
5577: /* nbcode[Tvar[j]][2]=1; */
5578: /* nbcode[Tvar[j]][3]=2; */
5579: /* To be continued (not working yet). */
5580: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5581:
5582: /* 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*/
5583: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5584: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5585: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5586: /*, could be restored in the future */
5587: 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 5588: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5589: break;
5590: }
5591: ij++;
1.287 brouard 5592: 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 5593: cptcode = ij; /* New max modality for covar j */
5594: } /* end of loop on modality i=-1 to 1 or more */
5595: break;
5596: case 1: /* Testing on varying covariate, could be simple and
5597: * should look at waves or product of fixed *
5598: * varying. No time to test -1, assuming 0 and 1 only */
5599: ij=0;
5600: for(i=0; i<=1;i++){
5601: nbcode[Tvar[k]][++ij]=i;
5602: }
5603: break;
5604: default:
5605: break;
5606: } /* end switch */
5607: } /* end dummy test */
1.311 brouard 5608: if(Dummy[k]==1 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5609: 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*/
5610: if(isnan(covar[Tvar[k]][i])){
5611: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5612: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
5613: fflush(ficlog);
5614: exit(1);
5615: }
5616: }
5617: }
1.287 brouard 5618: } /* 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 5619:
5620: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5621: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5622: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5623: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5624: 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 */
5625: 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 */
5626: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5627: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5628:
5629: ij=0;
5630: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5631: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5632: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5633: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5634: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5635: /* If product not in single variable we don't print results */
5636: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5637: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5638: 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*/
5639: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5640: 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 */
5641: if(Fixed[k]!=0)
5642: anyvaryingduminmodel=1;
5643: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5644: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5645: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5646: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5647: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5648: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5649: }
5650: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5651: /* ij--; */
5652: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5653: *cptcov=ij; /*Number of total real effective covariates: effective
5654: * because they can be excluded from the model and real
5655: * if in the model but excluded because missing values, but how to get k from ij?*/
5656: for(j=ij+1; j<= cptcovt; j++){
5657: Tvaraff[j]=0;
5658: Tmodelind[j]=0;
5659: }
5660: for(j=ntveff+1; j<= cptcovt; j++){
5661: TmodelInvind[j]=0;
5662: }
5663: /* To be sorted */
5664: ;
5665: }
1.126 brouard 5666:
1.145 brouard 5667:
1.126 brouard 5668: /*********** Health Expectancies ****************/
5669:
1.235 brouard 5670: 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 5671:
5672: {
5673: /* Health expectancies, no variances */
1.164 brouard 5674: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5675: int nhstepma, nstepma; /* Decreasing with age */
5676: double age, agelim, hf;
5677: double ***p3mat;
5678: double eip;
5679:
1.238 brouard 5680: /* pstamp(ficreseij); */
1.126 brouard 5681: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5682: fprintf(ficreseij,"# Age");
5683: for(i=1; i<=nlstate;i++){
5684: for(j=1; j<=nlstate;j++){
5685: fprintf(ficreseij," e%1d%1d ",i,j);
5686: }
5687: fprintf(ficreseij," e%1d. ",i);
5688: }
5689: fprintf(ficreseij,"\n");
5690:
5691:
5692: if(estepm < stepm){
5693: printf ("Problem %d lower than %d\n",estepm, stepm);
5694: }
5695: else hstepm=estepm;
5696: /* We compute the life expectancy from trapezoids spaced every estepm months
5697: * This is mainly to measure the difference between two models: for example
5698: * if stepm=24 months pijx are given only every 2 years and by summing them
5699: * we are calculating an estimate of the Life Expectancy assuming a linear
5700: * progression in between and thus overestimating or underestimating according
5701: * to the curvature of the survival function. If, for the same date, we
5702: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5703: * to compare the new estimate of Life expectancy with the same linear
5704: * hypothesis. A more precise result, taking into account a more precise
5705: * curvature will be obtained if estepm is as small as stepm. */
5706:
5707: /* For example we decided to compute the life expectancy with the smallest unit */
5708: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5709: nhstepm is the number of hstepm from age to agelim
5710: nstepm is the number of stepm from age to agelin.
1.270 brouard 5711: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5712: and note for a fixed period like estepm months */
5713: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5714: survival function given by stepm (the optimization length). Unfortunately it
5715: means that if the survival funtion is printed only each two years of age and if
5716: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5717: results. So we changed our mind and took the option of the best precision.
5718: */
5719: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5720:
5721: agelim=AGESUP;
5722: /* If stepm=6 months */
5723: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5724: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5725:
5726: /* nhstepm age range expressed in number of stepm */
5727: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5728: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5729: /* if (stepm >= YEARM) hstepm=1;*/
5730: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5731: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5732:
5733: for (age=bage; age<=fage; age ++){
5734: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5735: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5736: /* if (stepm >= YEARM) hstepm=1;*/
5737: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5738:
5739: /* If stepm=6 months */
5740: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5741: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5742:
1.235 brouard 5743: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5744:
5745: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5746:
5747: printf("%d|",(int)age);fflush(stdout);
5748: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5749:
5750: /* Computing expectancies */
5751: for(i=1; i<=nlstate;i++)
5752: for(j=1; j<=nlstate;j++)
5753: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5754: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5755:
5756: /* 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]);*/
5757:
5758: }
5759:
5760: fprintf(ficreseij,"%3.0f",age );
5761: for(i=1; i<=nlstate;i++){
5762: eip=0;
5763: for(j=1; j<=nlstate;j++){
5764: eip +=eij[i][j][(int)age];
5765: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5766: }
5767: fprintf(ficreseij,"%9.4f", eip );
5768: }
5769: fprintf(ficreseij,"\n");
5770:
5771: }
5772: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5773: printf("\n");
5774: fprintf(ficlog,"\n");
5775:
5776: }
5777:
1.235 brouard 5778: 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 5779:
5780: {
5781: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5782: to initial status i, ei. .
1.126 brouard 5783: */
5784: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5785: int nhstepma, nstepma; /* Decreasing with age */
5786: double age, agelim, hf;
5787: double ***p3matp, ***p3matm, ***varhe;
5788: double **dnewm,**doldm;
5789: double *xp, *xm;
5790: double **gp, **gm;
5791: double ***gradg, ***trgradg;
5792: int theta;
5793:
5794: double eip, vip;
5795:
5796: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5797: xp=vector(1,npar);
5798: xm=vector(1,npar);
5799: dnewm=matrix(1,nlstate*nlstate,1,npar);
5800: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5801:
5802: pstamp(ficresstdeij);
5803: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5804: fprintf(ficresstdeij,"# Age");
5805: for(i=1; i<=nlstate;i++){
5806: for(j=1; j<=nlstate;j++)
5807: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5808: fprintf(ficresstdeij," e%1d. ",i);
5809: }
5810: fprintf(ficresstdeij,"\n");
5811:
5812: pstamp(ficrescveij);
5813: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5814: fprintf(ficrescveij,"# Age");
5815: for(i=1; i<=nlstate;i++)
5816: for(j=1; j<=nlstate;j++){
5817: cptj= (j-1)*nlstate+i;
5818: for(i2=1; i2<=nlstate;i2++)
5819: for(j2=1; j2<=nlstate;j2++){
5820: cptj2= (j2-1)*nlstate+i2;
5821: if(cptj2 <= cptj)
5822: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5823: }
5824: }
5825: fprintf(ficrescveij,"\n");
5826:
5827: if(estepm < stepm){
5828: printf ("Problem %d lower than %d\n",estepm, stepm);
5829: }
5830: else hstepm=estepm;
5831: /* We compute the life expectancy from trapezoids spaced every estepm months
5832: * This is mainly to measure the difference between two models: for example
5833: * if stepm=24 months pijx are given only every 2 years and by summing them
5834: * we are calculating an estimate of the Life Expectancy assuming a linear
5835: * progression in between and thus overestimating or underestimating according
5836: * to the curvature of the survival function. If, for the same date, we
5837: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5838: * to compare the new estimate of Life expectancy with the same linear
5839: * hypothesis. A more precise result, taking into account a more precise
5840: * curvature will be obtained if estepm is as small as stepm. */
5841:
5842: /* For example we decided to compute the life expectancy with the smallest unit */
5843: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5844: nhstepm is the number of hstepm from age to agelim
5845: nstepm is the number of stepm from age to agelin.
5846: Look at hpijx to understand the reason of that which relies in memory size
5847: and note for a fixed period like estepm months */
5848: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5849: survival function given by stepm (the optimization length). Unfortunately it
5850: means that if the survival funtion is printed only each two years of age and if
5851: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5852: results. So we changed our mind and took the option of the best precision.
5853: */
5854: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5855:
5856: /* If stepm=6 months */
5857: /* nhstepm age range expressed in number of stepm */
5858: agelim=AGESUP;
5859: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5860: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5861: /* if (stepm >= YEARM) hstepm=1;*/
5862: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5863:
5864: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5865: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5866: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5867: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5868: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5869: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5870:
5871: for (age=bage; age<=fage; age ++){
5872: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5873: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5874: /* if (stepm >= YEARM) hstepm=1;*/
5875: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5876:
1.126 brouard 5877: /* If stepm=6 months */
5878: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5879: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5880:
5881: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5882:
1.126 brouard 5883: /* Computing Variances of health expectancies */
5884: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5885: decrease memory allocation */
5886: for(theta=1; theta <=npar; theta++){
5887: for(i=1; i<=npar; i++){
1.222 brouard 5888: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5889: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5890: }
1.235 brouard 5891: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5892: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5893:
1.126 brouard 5894: for(j=1; j<= nlstate; j++){
1.222 brouard 5895: for(i=1; i<=nlstate; i++){
5896: for(h=0; h<=nhstepm-1; h++){
5897: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5898: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5899: }
5900: }
1.126 brouard 5901: }
1.218 brouard 5902:
1.126 brouard 5903: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5904: for(h=0; h<=nhstepm-1; h++){
5905: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5906: }
1.126 brouard 5907: }/* End theta */
5908:
5909:
5910: for(h=0; h<=nhstepm-1; h++)
5911: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5912: for(theta=1; theta <=npar; theta++)
5913: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5914:
1.218 brouard 5915:
1.222 brouard 5916: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5917: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5918: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5919:
1.222 brouard 5920: printf("%d|",(int)age);fflush(stdout);
5921: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5922: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5923: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5924: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5925: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5926: for(ij=1;ij<=nlstate*nlstate;ij++)
5927: for(ji=1;ji<=nlstate*nlstate;ji++)
5928: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5929: }
5930: }
1.218 brouard 5931:
1.126 brouard 5932: /* Computing expectancies */
1.235 brouard 5933: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5934: for(i=1; i<=nlstate;i++)
5935: for(j=1; j<=nlstate;j++)
1.222 brouard 5936: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5937: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5938:
1.222 brouard 5939: /* 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 5940:
1.222 brouard 5941: }
1.269 brouard 5942:
5943: /* Standard deviation of expectancies ij */
1.126 brouard 5944: fprintf(ficresstdeij,"%3.0f",age );
5945: for(i=1; i<=nlstate;i++){
5946: eip=0.;
5947: vip=0.;
5948: for(j=1; j<=nlstate;j++){
1.222 brouard 5949: eip += eij[i][j][(int)age];
5950: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5951: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5952: 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 5953: }
5954: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5955: }
5956: fprintf(ficresstdeij,"\n");
1.218 brouard 5957:
1.269 brouard 5958: /* Variance of expectancies ij */
1.126 brouard 5959: fprintf(ficrescveij,"%3.0f",age );
5960: for(i=1; i<=nlstate;i++)
5961: for(j=1; j<=nlstate;j++){
1.222 brouard 5962: cptj= (j-1)*nlstate+i;
5963: for(i2=1; i2<=nlstate;i2++)
5964: for(j2=1; j2<=nlstate;j2++){
5965: cptj2= (j2-1)*nlstate+i2;
5966: if(cptj2 <= cptj)
5967: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5968: }
1.126 brouard 5969: }
5970: fprintf(ficrescveij,"\n");
1.218 brouard 5971:
1.126 brouard 5972: }
5973: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5974: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5975: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5976: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5977: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5978: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5979: printf("\n");
5980: fprintf(ficlog,"\n");
1.218 brouard 5981:
1.126 brouard 5982: free_vector(xm,1,npar);
5983: free_vector(xp,1,npar);
5984: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5985: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5986: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5987: }
1.218 brouard 5988:
1.126 brouard 5989: /************ Variance ******************/
1.235 brouard 5990: 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 5991: {
1.279 brouard 5992: /** Variance of health expectancies
5993: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
5994: * double **newm;
5995: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
5996: */
1.218 brouard 5997:
5998: /* int movingaverage(); */
5999: double **dnewm,**doldm;
6000: double **dnewmp,**doldmp;
6001: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 6002: int first=0;
1.218 brouard 6003: int k;
6004: double *xp;
1.279 brouard 6005: double **gp, **gm; /**< for var eij */
6006: double ***gradg, ***trgradg; /**< for var eij */
6007: double **gradgp, **trgradgp; /**< for var p point j */
6008: double *gpp, *gmp; /**< for var p point j */
6009: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 6010: double ***p3mat;
6011: double age,agelim, hf;
6012: /* double ***mobaverage; */
6013: int theta;
6014: char digit[4];
6015: char digitp[25];
6016:
6017: char fileresprobmorprev[FILENAMELENGTH];
6018:
6019: if(popbased==1){
6020: if(mobilav!=0)
6021: strcpy(digitp,"-POPULBASED-MOBILAV_");
6022: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
6023: }
6024: else
6025: strcpy(digitp,"-STABLBASED_");
1.126 brouard 6026:
1.218 brouard 6027: /* if (mobilav!=0) { */
6028: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6029: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
6030: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
6031: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
6032: /* } */
6033: /* } */
6034:
6035: strcpy(fileresprobmorprev,"PRMORPREV-");
6036: sprintf(digit,"%-d",ij);
6037: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
6038: strcat(fileresprobmorprev,digit); /* Tvar to be done */
6039: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
6040: strcat(fileresprobmorprev,fileresu);
6041: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
6042: printf("Problem with resultfile: %s\n", fileresprobmorprev);
6043: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
6044: }
6045: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6046: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
6047: pstamp(ficresprobmorprev);
6048: 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 6049: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
6050: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
6051: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
6052: }
6053: for(j=1;j<=cptcoveff;j++)
6054: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
6055: fprintf(ficresprobmorprev,"\n");
6056:
1.218 brouard 6057: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
6058: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6059: fprintf(ficresprobmorprev," p.%-d SE",j);
6060: for(i=1; i<=nlstate;i++)
6061: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
6062: }
6063: fprintf(ficresprobmorprev,"\n");
6064:
6065: fprintf(ficgp,"\n# Routine varevsij");
6066: fprintf(ficgp,"\nunset title \n");
6067: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
6068: 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");
6069: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 6070:
1.218 brouard 6071: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6072: pstamp(ficresvij);
6073: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
6074: if(popbased==1)
6075: 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);
6076: else
6077: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
6078: fprintf(ficresvij,"# Age");
6079: for(i=1; i<=nlstate;i++)
6080: for(j=1; j<=nlstate;j++)
6081: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
6082: fprintf(ficresvij,"\n");
6083:
6084: xp=vector(1,npar);
6085: dnewm=matrix(1,nlstate,1,npar);
6086: doldm=matrix(1,nlstate,1,nlstate);
6087: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
6088: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6089:
6090: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
6091: gpp=vector(nlstate+1,nlstate+ndeath);
6092: gmp=vector(nlstate+1,nlstate+ndeath);
6093: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 6094:
1.218 brouard 6095: if(estepm < stepm){
6096: printf ("Problem %d lower than %d\n",estepm, stepm);
6097: }
6098: else hstepm=estepm;
6099: /* For example we decided to compute the life expectancy with the smallest unit */
6100: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6101: nhstepm is the number of hstepm from age to agelim
6102: nstepm is the number of stepm from age to agelim.
6103: Look at function hpijx to understand why because of memory size limitations,
6104: we decided (b) to get a life expectancy respecting the most precise curvature of the
6105: survival function given by stepm (the optimization length). Unfortunately it
6106: means that if the survival funtion is printed every two years of age and if
6107: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6108: results. So we changed our mind and took the option of the best precision.
6109: */
6110: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6111: agelim = AGESUP;
6112: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6113: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6114: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6115: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6116: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
6117: gp=matrix(0,nhstepm,1,nlstate);
6118: gm=matrix(0,nhstepm,1,nlstate);
6119:
6120:
6121: for(theta=1; theta <=npar; theta++){
6122: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
6123: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6124: }
1.279 brouard 6125: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
6126: * returns into prlim .
1.288 brouard 6127: */
1.242 brouard 6128: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 6129:
6130: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 6131: if (popbased==1) {
6132: if(mobilav ==0){
6133: for(i=1; i<=nlstate;i++)
6134: prlim[i][i]=probs[(int)age][i][ij];
6135: }else{ /* mobilav */
6136: for(i=1; i<=nlstate;i++)
6137: prlim[i][i]=mobaverage[(int)age][i][ij];
6138: }
6139: }
1.295 brouard 6140: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 6141: */
6142: 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 6143: /**< 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 6144: * at horizon h in state j including mortality.
6145: */
1.218 brouard 6146: for(j=1; j<= nlstate; j++){
6147: for(h=0; h<=nhstepm; h++){
6148: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6149: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6150: }
6151: }
1.279 brouard 6152: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6153: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6154: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6155: */
6156: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6157: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6158: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6159: }
6160:
6161: /* Again with minus shift */
1.218 brouard 6162:
6163: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6164: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6165:
1.242 brouard 6166: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6167:
6168: if (popbased==1) {
6169: if(mobilav ==0){
6170: for(i=1; i<=nlstate;i++)
6171: prlim[i][i]=probs[(int)age][i][ij];
6172: }else{ /* mobilav */
6173: for(i=1; i<=nlstate;i++)
6174: prlim[i][i]=mobaverage[(int)age][i][ij];
6175: }
6176: }
6177:
1.235 brouard 6178: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6179:
6180: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6181: for(h=0; h<=nhstepm; h++){
6182: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6183: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6184: }
6185: }
6186: /* This for computing probability of death (h=1 means
6187: computed over hstepm matrices product = hstepm*stepm months)
6188: as a weighted average of prlim.
6189: */
6190: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6191: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6192: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6193: }
1.279 brouard 6194: /* end shifting computations */
6195:
6196: /**< Computing gradient matrix at horizon h
6197: */
1.218 brouard 6198: for(j=1; j<= nlstate; j++) /* vareij */
6199: for(h=0; h<=nhstepm; h++){
6200: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6201: }
1.279 brouard 6202: /**< Gradient of overall mortality p.3 (or p.j)
6203: */
6204: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6205: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6206: }
6207:
6208: } /* End theta */
1.279 brouard 6209:
6210: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6211: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6212:
6213: for(h=0; h<=nhstepm; h++) /* veij */
6214: for(j=1; j<=nlstate;j++)
6215: for(theta=1; theta <=npar; theta++)
6216: trgradg[h][j][theta]=gradg[h][theta][j];
6217:
6218: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6219: for(theta=1; theta <=npar; theta++)
6220: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6221: /**< as well as its transposed matrix
6222: */
1.218 brouard 6223:
6224: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6225: for(i=1;i<=nlstate;i++)
6226: for(j=1;j<=nlstate;j++)
6227: vareij[i][j][(int)age] =0.;
1.279 brouard 6228:
6229: /* Computing trgradg by matcov by gradg at age and summing over h
6230: * and k (nhstepm) formula 15 of article
6231: * Lievre-Brouard-Heathcote
6232: */
6233:
1.218 brouard 6234: for(h=0;h<=nhstepm;h++){
6235: for(k=0;k<=nhstepm;k++){
6236: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6237: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6238: for(i=1;i<=nlstate;i++)
6239: for(j=1;j<=nlstate;j++)
6240: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6241: }
6242: }
6243:
1.279 brouard 6244: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6245: * p.j overall mortality formula 49 but computed directly because
6246: * we compute the grad (wix pijx) instead of grad (pijx),even if
6247: * wix is independent of theta.
6248: */
1.218 brouard 6249: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6250: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6251: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6252: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6253: varppt[j][i]=doldmp[j][i];
6254: /* end ppptj */
6255: /* x centered again */
6256:
1.242 brouard 6257: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6258:
6259: if (popbased==1) {
6260: if(mobilav ==0){
6261: for(i=1; i<=nlstate;i++)
6262: prlim[i][i]=probs[(int)age][i][ij];
6263: }else{ /* mobilav */
6264: for(i=1; i<=nlstate;i++)
6265: prlim[i][i]=mobaverage[(int)age][i][ij];
6266: }
6267: }
6268:
6269: /* This for computing probability of death (h=1 means
6270: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6271: as a weighted average of prlim.
6272: */
1.235 brouard 6273: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6274: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6275: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6276: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6277: }
6278: /* end probability of death */
6279:
6280: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6281: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6282: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6283: for(i=1; i<=nlstate;i++){
6284: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6285: }
6286: }
6287: fprintf(ficresprobmorprev,"\n");
6288:
6289: fprintf(ficresvij,"%.0f ",age );
6290: for(i=1; i<=nlstate;i++)
6291: for(j=1; j<=nlstate;j++){
6292: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6293: }
6294: fprintf(ficresvij,"\n");
6295: free_matrix(gp,0,nhstepm,1,nlstate);
6296: free_matrix(gm,0,nhstepm,1,nlstate);
6297: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6298: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6299: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6300: } /* End age */
6301: free_vector(gpp,nlstate+1,nlstate+ndeath);
6302: free_vector(gmp,nlstate+1,nlstate+ndeath);
6303: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6304: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6305: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6306: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6307: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6308: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6309: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6310: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6311: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6312: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6313: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6314: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6315: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6316: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6317: 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);
6318: /* 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 6319: */
1.218 brouard 6320: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6321: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6322:
1.218 brouard 6323: free_vector(xp,1,npar);
6324: free_matrix(doldm,1,nlstate,1,nlstate);
6325: free_matrix(dnewm,1,nlstate,1,npar);
6326: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6327: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6328: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6329: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6330: fclose(ficresprobmorprev);
6331: fflush(ficgp);
6332: fflush(fichtm);
6333: } /* end varevsij */
1.126 brouard 6334:
6335: /************ Variance of prevlim ******************/
1.269 brouard 6336: 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 6337: {
1.205 brouard 6338: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6339: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6340:
1.268 brouard 6341: double **dnewmpar,**doldm;
1.126 brouard 6342: int i, j, nhstepm, hstepm;
6343: double *xp;
6344: double *gp, *gm;
6345: double **gradg, **trgradg;
1.208 brouard 6346: double **mgm, **mgp;
1.126 brouard 6347: double age,agelim;
6348: int theta;
6349:
6350: pstamp(ficresvpl);
1.288 brouard 6351: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6352: fprintf(ficresvpl,"# Age ");
6353: if(nresult >=1)
6354: fprintf(ficresvpl," Result# ");
1.126 brouard 6355: for(i=1; i<=nlstate;i++)
6356: fprintf(ficresvpl," %1d-%1d",i,i);
6357: fprintf(ficresvpl,"\n");
6358:
6359: xp=vector(1,npar);
1.268 brouard 6360: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6361: doldm=matrix(1,nlstate,1,nlstate);
6362:
6363: hstepm=1*YEARM; /* Every year of age */
6364: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6365: agelim = AGESUP;
6366: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6367: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6368: if (stepm >= YEARM) hstepm=1;
6369: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6370: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6371: mgp=matrix(1,npar,1,nlstate);
6372: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6373: gp=vector(1,nlstate);
6374: gm=vector(1,nlstate);
6375:
6376: for(theta=1; theta <=npar; theta++){
6377: for(i=1; i<=npar; i++){ /* Computes gradient */
6378: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6379: }
1.288 brouard 6380: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6381: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6382: /* else */
6383: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6384: for(i=1;i<=nlstate;i++){
1.126 brouard 6385: gp[i] = prlim[i][i];
1.208 brouard 6386: mgp[theta][i] = prlim[i][i];
6387: }
1.126 brouard 6388: for(i=1; i<=npar; i++) /* Computes gradient */
6389: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6390: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6391: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6392: /* else */
6393: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6394: for(i=1;i<=nlstate;i++){
1.126 brouard 6395: gm[i] = prlim[i][i];
1.208 brouard 6396: mgm[theta][i] = prlim[i][i];
6397: }
1.126 brouard 6398: for(i=1;i<=nlstate;i++)
6399: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6400: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6401: } /* End theta */
6402:
6403: trgradg =matrix(1,nlstate,1,npar);
6404:
6405: for(j=1; j<=nlstate;j++)
6406: for(theta=1; theta <=npar; theta++)
6407: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6408: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6409: /* printf("\nmgm mgp %d ",(int)age); */
6410: /* for(j=1; j<=nlstate;j++){ */
6411: /* printf(" %d ",j); */
6412: /* for(theta=1; theta <=npar; theta++) */
6413: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6414: /* printf("\n "); */
6415: /* } */
6416: /* } */
6417: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6418: /* printf("\n gradg %d ",(int)age); */
6419: /* for(j=1; j<=nlstate;j++){ */
6420: /* printf("%d ",j); */
6421: /* for(theta=1; theta <=npar; theta++) */
6422: /* printf("%d %lf ",theta,gradg[theta][j]); */
6423: /* printf("\n "); */
6424: /* } */
6425: /* } */
1.126 brouard 6426:
6427: for(i=1;i<=nlstate;i++)
6428: varpl[i][(int)age] =0.;
1.209 brouard 6429: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6430: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6431: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6432: }else{
1.268 brouard 6433: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6434: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6435: }
1.126 brouard 6436: for(i=1;i<=nlstate;i++)
6437: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6438:
6439: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6440: if(nresult >=1)
6441: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6442: for(i=1; i<=nlstate;i++){
1.126 brouard 6443: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6444: /* for(j=1;j<=nlstate;j++) */
6445: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6446: }
1.126 brouard 6447: fprintf(ficresvpl,"\n");
6448: free_vector(gp,1,nlstate);
6449: free_vector(gm,1,nlstate);
1.208 brouard 6450: free_matrix(mgm,1,npar,1,nlstate);
6451: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6452: free_matrix(gradg,1,npar,1,nlstate);
6453: free_matrix(trgradg,1,nlstate,1,npar);
6454: } /* End age */
6455:
6456: free_vector(xp,1,npar);
6457: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6458: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6459:
6460: }
6461:
6462:
6463: /************ Variance of backprevalence limit ******************/
1.269 brouard 6464: 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 6465: {
6466: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6467: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6468:
6469: double **dnewmpar,**doldm;
6470: int i, j, nhstepm, hstepm;
6471: double *xp;
6472: double *gp, *gm;
6473: double **gradg, **trgradg;
6474: double **mgm, **mgp;
6475: double age,agelim;
6476: int theta;
6477:
6478: pstamp(ficresvbl);
6479: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6480: fprintf(ficresvbl,"# Age ");
6481: if(nresult >=1)
6482: fprintf(ficresvbl," Result# ");
6483: for(i=1; i<=nlstate;i++)
6484: fprintf(ficresvbl," %1d-%1d",i,i);
6485: fprintf(ficresvbl,"\n");
6486:
6487: xp=vector(1,npar);
6488: dnewmpar=matrix(1,nlstate,1,npar);
6489: doldm=matrix(1,nlstate,1,nlstate);
6490:
6491: hstepm=1*YEARM; /* Every year of age */
6492: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6493: agelim = AGEINF;
6494: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6495: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6496: if (stepm >= YEARM) hstepm=1;
6497: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6498: gradg=matrix(1,npar,1,nlstate);
6499: mgp=matrix(1,npar,1,nlstate);
6500: mgm=matrix(1,npar,1,nlstate);
6501: gp=vector(1,nlstate);
6502: gm=vector(1,nlstate);
6503:
6504: for(theta=1; theta <=npar; theta++){
6505: for(i=1; i<=npar; i++){ /* Computes gradient */
6506: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6507: }
6508: if(mobilavproj > 0 )
6509: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6510: else
6511: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6512: for(i=1;i<=nlstate;i++){
6513: gp[i] = bprlim[i][i];
6514: mgp[theta][i] = bprlim[i][i];
6515: }
6516: for(i=1; i<=npar; i++) /* Computes gradient */
6517: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6518: if(mobilavproj > 0 )
6519: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6520: else
6521: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6522: for(i=1;i<=nlstate;i++){
6523: gm[i] = bprlim[i][i];
6524: mgm[theta][i] = bprlim[i][i];
6525: }
6526: for(i=1;i<=nlstate;i++)
6527: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6528: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6529: } /* End theta */
6530:
6531: trgradg =matrix(1,nlstate,1,npar);
6532:
6533: for(j=1; j<=nlstate;j++)
6534: for(theta=1; theta <=npar; theta++)
6535: trgradg[j][theta]=gradg[theta][j];
6536: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6537: /* printf("\nmgm mgp %d ",(int)age); */
6538: /* for(j=1; j<=nlstate;j++){ */
6539: /* printf(" %d ",j); */
6540: /* for(theta=1; theta <=npar; theta++) */
6541: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6542: /* printf("\n "); */
6543: /* } */
6544: /* } */
6545: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6546: /* printf("\n gradg %d ",(int)age); */
6547: /* for(j=1; j<=nlstate;j++){ */
6548: /* printf("%d ",j); */
6549: /* for(theta=1; theta <=npar; theta++) */
6550: /* printf("%d %lf ",theta,gradg[theta][j]); */
6551: /* printf("\n "); */
6552: /* } */
6553: /* } */
6554:
6555: for(i=1;i<=nlstate;i++)
6556: varbpl[i][(int)age] =0.;
6557: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6558: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6559: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6560: }else{
6561: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6562: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6563: }
6564: for(i=1;i<=nlstate;i++)
6565: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6566:
6567: fprintf(ficresvbl,"%.0f ",age );
6568: if(nresult >=1)
6569: fprintf(ficresvbl,"%d ",nres );
6570: for(i=1; i<=nlstate;i++)
6571: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6572: fprintf(ficresvbl,"\n");
6573: free_vector(gp,1,nlstate);
6574: free_vector(gm,1,nlstate);
6575: free_matrix(mgm,1,npar,1,nlstate);
6576: free_matrix(mgp,1,npar,1,nlstate);
6577: free_matrix(gradg,1,npar,1,nlstate);
6578: free_matrix(trgradg,1,nlstate,1,npar);
6579: } /* End age */
6580:
6581: free_vector(xp,1,npar);
6582: free_matrix(doldm,1,nlstate,1,npar);
6583: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6584:
6585: }
6586:
6587: /************ Variance of one-step probabilities ******************/
6588: 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 6589: {
6590: int i, j=0, k1, l1, tj;
6591: int k2, l2, j1, z1;
6592: int k=0, l;
6593: int first=1, first1, first2;
6594: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6595: double **dnewm,**doldm;
6596: double *xp;
6597: double *gp, *gm;
6598: double **gradg, **trgradg;
6599: double **mu;
6600: double age, cov[NCOVMAX+1];
6601: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6602: int theta;
6603: char fileresprob[FILENAMELENGTH];
6604: char fileresprobcov[FILENAMELENGTH];
6605: char fileresprobcor[FILENAMELENGTH];
6606: double ***varpij;
6607:
6608: strcpy(fileresprob,"PROB_");
6609: strcat(fileresprob,fileres);
6610: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6611: printf("Problem with resultfile: %s\n", fileresprob);
6612: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6613: }
6614: strcpy(fileresprobcov,"PROBCOV_");
6615: strcat(fileresprobcov,fileresu);
6616: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6617: printf("Problem with resultfile: %s\n", fileresprobcov);
6618: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6619: }
6620: strcpy(fileresprobcor,"PROBCOR_");
6621: strcat(fileresprobcor,fileresu);
6622: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6623: printf("Problem with resultfile: %s\n", fileresprobcor);
6624: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6625: }
6626: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6627: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6628: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6629: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6630: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6631: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6632: pstamp(ficresprob);
6633: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6634: fprintf(ficresprob,"# Age");
6635: pstamp(ficresprobcov);
6636: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6637: fprintf(ficresprobcov,"# Age");
6638: pstamp(ficresprobcor);
6639: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6640: fprintf(ficresprobcor,"# Age");
1.126 brouard 6641:
6642:
1.222 brouard 6643: for(i=1; i<=nlstate;i++)
6644: for(j=1; j<=(nlstate+ndeath);j++){
6645: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6646: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6647: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6648: }
6649: /* fprintf(ficresprob,"\n");
6650: fprintf(ficresprobcov,"\n");
6651: fprintf(ficresprobcor,"\n");
6652: */
6653: xp=vector(1,npar);
6654: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6655: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6656: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6657: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6658: first=1;
6659: fprintf(ficgp,"\n# Routine varprob");
6660: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6661: fprintf(fichtm,"\n");
6662:
1.288 brouard 6663: 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 6664: 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);
6665: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6666: and drawn. It helps understanding how is the covariance between two incidences.\
6667: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6668: 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 6669: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6670: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6671: standard deviations wide on each axis. <br>\
6672: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6673: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6674: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6675:
1.222 brouard 6676: cov[1]=1;
6677: /* tj=cptcoveff; */
1.225 brouard 6678: tj = (int) pow(2,cptcoveff);
1.222 brouard 6679: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6680: j1=0;
1.224 brouard 6681: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6682: if (cptcovn>0) {
6683: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6684: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6685: fprintf(ficresprob, "**********\n#\n");
6686: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6687: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6688: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6689:
1.222 brouard 6690: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6691: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6692: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6693:
6694:
1.222 brouard 6695: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6696: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6697: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6698:
1.222 brouard 6699: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6700: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6701: fprintf(ficresprobcor, "**********\n#");
6702: if(invalidvarcomb[j1]){
6703: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6704: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6705: continue;
6706: }
6707: }
6708: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6709: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6710: gp=vector(1,(nlstate)*(nlstate+ndeath));
6711: gm=vector(1,(nlstate)*(nlstate+ndeath));
6712: for (age=bage; age<=fage; age ++){
6713: cov[2]=age;
6714: if(nagesqr==1)
6715: cov[3]= age*age;
6716: for (k=1; k<=cptcovn;k++) {
6717: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6718: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6719: * 1 1 1 1 1
6720: * 2 2 1 1 1
6721: * 3 1 2 1 1
6722: */
6723: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6724: }
6725: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6726: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6727: for (k=1; k<=cptcovprod;k++)
6728: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6729:
6730:
1.222 brouard 6731: for(theta=1; theta <=npar; theta++){
6732: for(i=1; i<=npar; i++)
6733: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6734:
1.222 brouard 6735: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6736:
1.222 brouard 6737: k=0;
6738: for(i=1; i<= (nlstate); i++){
6739: for(j=1; j<=(nlstate+ndeath);j++){
6740: k=k+1;
6741: gp[k]=pmmij[i][j];
6742: }
6743: }
1.220 brouard 6744:
1.222 brouard 6745: for(i=1; i<=npar; i++)
6746: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6747:
1.222 brouard 6748: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6749: k=0;
6750: for(i=1; i<=(nlstate); i++){
6751: for(j=1; j<=(nlstate+ndeath);j++){
6752: k=k+1;
6753: gm[k]=pmmij[i][j];
6754: }
6755: }
1.220 brouard 6756:
1.222 brouard 6757: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6758: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6759: }
1.126 brouard 6760:
1.222 brouard 6761: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6762: for(theta=1; theta <=npar; theta++)
6763: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6764:
1.222 brouard 6765: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6766: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6767:
1.222 brouard 6768: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6769:
1.222 brouard 6770: k=0;
6771: for(i=1; i<=(nlstate); i++){
6772: for(j=1; j<=(nlstate+ndeath);j++){
6773: k=k+1;
6774: mu[k][(int) age]=pmmij[i][j];
6775: }
6776: }
6777: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6778: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6779: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6780:
1.222 brouard 6781: /*printf("\n%d ",(int)age);
6782: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6783: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6784: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6785: }*/
1.220 brouard 6786:
1.222 brouard 6787: fprintf(ficresprob,"\n%d ",(int)age);
6788: fprintf(ficresprobcov,"\n%d ",(int)age);
6789: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6790:
1.222 brouard 6791: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6792: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6793: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6794: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6795: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6796: }
6797: i=0;
6798: for (k=1; k<=(nlstate);k++){
6799: for (l=1; l<=(nlstate+ndeath);l++){
6800: i++;
6801: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6802: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6803: for (j=1; j<=i;j++){
6804: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6805: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6806: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6807: }
6808: }
6809: }/* end of loop for state */
6810: } /* end of loop for age */
6811: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6812: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6813: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6814: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6815:
6816: /* Confidence intervalle of pij */
6817: /*
6818: fprintf(ficgp,"\nunset parametric;unset label");
6819: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6820: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6821: 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);
6822: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6823: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6824: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6825: */
6826:
6827: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6828: first1=1;first2=2;
6829: for (k2=1; k2<=(nlstate);k2++){
6830: for (l2=1; l2<=(nlstate+ndeath);l2++){
6831: if(l2==k2) continue;
6832: j=(k2-1)*(nlstate+ndeath)+l2;
6833: for (k1=1; k1<=(nlstate);k1++){
6834: for (l1=1; l1<=(nlstate+ndeath);l1++){
6835: if(l1==k1) continue;
6836: i=(k1-1)*(nlstate+ndeath)+l1;
6837: if(i<=j) continue;
6838: for (age=bage; age<=fage; age ++){
6839: if ((int)age %5==0){
6840: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6841: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6842: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6843: mu1=mu[i][(int) age]/stepm*YEARM ;
6844: mu2=mu[j][(int) age]/stepm*YEARM;
6845: c12=cv12/sqrt(v1*v2);
6846: /* Computing eigen value of matrix of covariance */
6847: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6848: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6849: if ((lc2 <0) || (lc1 <0) ){
6850: if(first2==1){
6851: first1=0;
6852: 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);
6853: }
6854: 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);
6855: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6856: /* lc2=fabs(lc2); */
6857: }
1.220 brouard 6858:
1.222 brouard 6859: /* Eigen vectors */
1.280 brouard 6860: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
6861: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6862: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6863: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
6864: }else
6865: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 6866: /*v21=sqrt(1.-v11*v11); *//* error */
6867: v21=(lc1-v1)/cv12*v11;
6868: v12=-v21;
6869: v22=v11;
6870: tnalp=v21/v11;
6871: if(first1==1){
6872: first1=0;
6873: 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);
6874: }
6875: 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);
6876: /*printf(fignu*/
6877: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6878: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6879: if(first==1){
6880: first=0;
6881: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6882: fprintf(ficgp,"\nset parametric;unset label");
6883: 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);
6884: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6885: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6886: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6887: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6888: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6889: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6890: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6891: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6892: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6893: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6894: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6895: 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 6896: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
6897: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6898: }else{
6899: first=0;
6900: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6901: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6902: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6903: 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 6904: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6905: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6906: }/* if first */
6907: } /* age mod 5 */
6908: } /* end loop age */
6909: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6910: first=1;
6911: } /*l12 */
6912: } /* k12 */
6913: } /*l1 */
6914: }/* k1 */
6915: } /* loop on combination of covariates j1 */
6916: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6917: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6918: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6919: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6920: free_vector(xp,1,npar);
6921: fclose(ficresprob);
6922: fclose(ficresprobcov);
6923: fclose(ficresprobcor);
6924: fflush(ficgp);
6925: fflush(fichtmcov);
6926: }
1.126 brouard 6927:
6928:
6929: /******************* Printing html file ***********/
1.201 brouard 6930: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6931: int lastpass, int stepm, int weightopt, char model[],\
6932: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 6933: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
6934: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
6935: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 6936: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6937:
6938: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6939: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6940: </ul>");
1.237 brouard 6941: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6942: </ul>", model);
1.214 brouard 6943: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6944: 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",
6945: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6946: 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 6947: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6948: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6949: fprintf(fichtm,"\
6950: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6951: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6952: fprintf(fichtm,"\
1.217 brouard 6953: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6954: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6955: fprintf(fichtm,"\
1.288 brouard 6956: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6957: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6958: fprintf(fichtm,"\
1.288 brouard 6959: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 6960: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6961: fprintf(fichtm,"\
1.211 brouard 6962: - (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 6963: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6964: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6965: if(prevfcast==1){
6966: fprintf(fichtm,"\
6967: - Prevalence projections by age and states: \
1.201 brouard 6968: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6969: }
1.126 brouard 6970:
6971:
1.225 brouard 6972: m=pow(2,cptcoveff);
1.222 brouard 6973: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6974:
1.264 brouard 6975: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6976:
6977: jj1=0;
6978:
6979: fprintf(fichtm," \n<ul>");
6980: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6981: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6982: if(m != 1 && TKresult[nres]!= k1)
6983: continue;
6984: jj1++;
6985: if (cptcovn > 0) {
6986: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6987: for (cpt=1; cpt<=cptcoveff;cpt++){
6988: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6989: }
6990: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6991: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6992: }
6993: fprintf(fichtm,"\">");
6994:
6995: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6996: fprintf(fichtm,"************ Results for covariates");
6997: for (cpt=1; cpt<=cptcoveff;cpt++){
6998: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6999: }
7000: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7001: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7002: }
7003: if(invalidvarcomb[k1]){
7004: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
7005: continue;
7006: }
7007: fprintf(fichtm,"</a></li>");
7008: } /* cptcovn >0 */
7009: }
7010: fprintf(fichtm," \n</ul>");
7011:
1.222 brouard 7012: jj1=0;
1.237 brouard 7013:
7014: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 7015: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 7016: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7017: continue;
1.220 brouard 7018:
1.222 brouard 7019: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7020: jj1++;
7021: if (cptcovn > 0) {
1.264 brouard 7022: fprintf(fichtm,"\n<p><a name=\"rescov");
7023: for (cpt=1; cpt<=cptcoveff;cpt++){
7024: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7025: }
7026: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7027: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
7028: }
7029: fprintf(fichtm,"\"</a>");
7030:
1.222 brouard 7031: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7032: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 7033: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
7034: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
7035: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7036: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 7037: }
1.237 brouard 7038: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7039: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7040: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
7041: }
7042:
1.230 brouard 7043: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 7044: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
7045: if(invalidvarcomb[k1]){
7046: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
7047: printf("\nCombination (%d) ignored because no cases \n",k1);
7048: continue;
7049: }
7050: }
7051: /* aij, bij */
1.259 brouard 7052: 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 7053: <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 7054: /* Pij */
1.241 brouard 7055: 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> \
7056: <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 7057: /* Quasi-incidences */
7058: 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 7059: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 7060: 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 7061: 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> \
7062: <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 7063: /* Survival functions (period) in state j */
7064: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7065: 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 7066: <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 7067: }
7068: /* State specific survival functions (period) */
7069: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 7070: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
7071: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.283 brouard 7072: <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 7073: }
1.288 brouard 7074: /* Period (forward stable) prevalence in each health state */
1.222 brouard 7075: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7076: 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> \
7077: <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 7078: }
1.296 brouard 7079: if(prevbcast==1){
1.288 brouard 7080: /* Backward prevalence in each health state */
1.222 brouard 7081: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 7082: 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 7083: <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 7084: }
1.217 brouard 7085: }
1.222 brouard 7086: if(prevfcast==1){
1.288 brouard 7087: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 7088: for(cpt=1; cpt<=nlstate;cpt++){
1.288 brouard 7089: 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><br> \
1.296 brouard 7090: <img src=\"%s_%d-%d-%d.svg\">", dateprev1, dateprev2, mobilavproj, dateprojd, dateprojf, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 7091: }
7092: }
1.296 brouard 7093: if(prevbcast==1){
1.268 brouard 7094: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
7095: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 7096: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
7097: 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 \
7098: 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) \
7099: with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
7100: <img src=\"%s_%d-%d-%d.svg\">", dateprev1, dateprev2, mobilavproj, dateback1, dateback2, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 7101: }
7102: }
1.220 brouard 7103:
1.222 brouard 7104: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 7105: 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> <br> \
7106: <img src=\"%s_%d-%d-%d.svg\">",cpt,nlstate,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.222 brouard 7107: }
7108: /* } /\* end i1 *\/ */
7109: }/* End k1 */
7110: fprintf(fichtm,"</ul>");
1.126 brouard 7111:
1.222 brouard 7112: fprintf(fichtm,"\
1.126 brouard 7113: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 7114: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 7115: - 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 7116: But because parameters are usually highly correlated (a higher incidence of disability \
7117: and a higher incidence of recovery can give very close observed transition) it might \
7118: be very useful to look not only at linear confidence intervals estimated from the \
7119: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
7120: (parameters) of the logistic regression, it might be more meaningful to visualize the \
7121: covariance matrix of the one-step probabilities. \
7122: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 7123:
1.222 brouard 7124: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
7125: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
7126: fprintf(fichtm,"\
1.126 brouard 7127: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7128: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 7129:
1.222 brouard 7130: fprintf(fichtm,"\
1.126 brouard 7131: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 7132: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
7133: fprintf(fichtm,"\
1.126 brouard 7134: - 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): \
7135: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7136: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 7137: fprintf(fichtm,"\
1.126 brouard 7138: - (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): \
7139: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7140: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7141: fprintf(fichtm,"\
1.288 brouard 7142: - 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 7143: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7144: fprintf(fichtm,"\
1.128 brouard 7145: - 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 7146: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7147: fprintf(fichtm,"\
1.288 brouard 7148: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7149: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7150:
7151: /* if(popforecast==1) fprintf(fichtm,"\n */
7152: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7153: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7154: /* <br>",fileres,fileres,fileres,fileres); */
7155: /* else */
7156: /* 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 7157: fflush(fichtm);
7158: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 7159:
1.225 brouard 7160: m=pow(2,cptcoveff);
1.222 brouard 7161: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7162:
1.222 brouard 7163: jj1=0;
1.237 brouard 7164:
1.241 brouard 7165: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7166: for(k1=1; k1<=m;k1++){
1.253 brouard 7167: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7168: continue;
1.222 brouard 7169: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7170: jj1++;
1.126 brouard 7171: if (cptcovn > 0) {
7172: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7173: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 7174: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
7175: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7176: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7177: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7178: }
7179:
1.126 brouard 7180: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 7181:
1.222 brouard 7182: if(invalidvarcomb[k1]){
7183: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7184: continue;
7185: }
1.126 brouard 7186: }
7187: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7188: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 7189: prevalence (with 95%% confidence interval) in state (%d): <a href=\"%s_%d-%d-%d.svg\"> %s_%d-%d-%d.svg</a>\n <br>\
1.258 brouard 7190: <img src=\"%s_%d-%d-%d.svg\">",mobilav,cpt,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
1.126 brouard 7191: }
7192: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 7193: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
7194: true period expectancies (those weighted with period prevalences are also\
7195: drawn in addition to the population based expectancies computed using\
1.241 brouard 7196: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
7197: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7198: /* } /\* end i1 *\/ */
7199: }/* End k1 */
1.241 brouard 7200: }/* End nres */
1.222 brouard 7201: fprintf(fichtm,"</ul>");
7202: fflush(fichtm);
1.126 brouard 7203: }
7204:
7205: /******************* Gnuplot file **************/
1.296 brouard 7206: 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 7207:
7208: char dirfileres[132],optfileres[132];
1.264 brouard 7209: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7210: 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 7211: int lv=0, vlv=0, kl=0;
1.130 brouard 7212: int ng=0;
1.201 brouard 7213: int vpopbased;
1.223 brouard 7214: int ioffset; /* variable offset for columns */
1.270 brouard 7215: int iyearc=1; /* variable column for year of projection */
7216: int iagec=1; /* variable column for age of projection */
1.235 brouard 7217: int nres=0; /* Index of resultline */
1.266 brouard 7218: int istart=1; /* For starting graphs in projections */
1.219 brouard 7219:
1.126 brouard 7220: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7221: /* printf("Problem with file %s",optionfilegnuplot); */
7222: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7223: /* } */
7224:
7225: /*#ifdef windows */
7226: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7227: /*#endif */
1.225 brouard 7228: m=pow(2,cptcoveff);
1.126 brouard 7229:
1.274 brouard 7230: /* diagram of the model */
7231: fprintf(ficgp,"\n#Diagram of the model \n");
7232: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7233: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7234: 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);
7235:
7236: 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);
7237: fprintf(ficgp,"\n#show arrow\nunset label\n");
7238: 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);
7239: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7240: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7241: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7242: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7243:
1.202 brouard 7244: /* Contribution to likelihood */
7245: /* Plot the probability implied in the likelihood */
1.223 brouard 7246: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7247: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7248: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7249: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7250: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7251: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7252: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7253: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7254: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7255: 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));
7256: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7257: 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));
7258: for (i=1; i<= nlstate ; i ++) {
7259: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7260: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7261: 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);
7262: for (j=2; j<= nlstate+ndeath ; j ++) {
7263: 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);
7264: }
7265: fprintf(ficgp,";\nset out; unset ylabel;\n");
7266: }
7267: /* 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 */
7268: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7269: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7270: fprintf(ficgp,"\nset out;unset log\n");
7271: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7272:
1.126 brouard 7273: strcpy(dirfileres,optionfilefiname);
7274: strcpy(optfileres,"vpl");
1.223 brouard 7275: /* 1eme*/
1.238 brouard 7276: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7277: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7278: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7279: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7280: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7281: continue;
7282: /* We are interested in selected combination by the resultline */
1.246 brouard 7283: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7284: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7285: strcpy(gplotlabel,"(");
1.238 brouard 7286: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7287: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7288: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7289: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7290: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7291: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7292: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7293: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7294: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7295: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7296: }
7297: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7298: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7299: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7300: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7301: }
7302: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7303: /* printf("\n#\n"); */
1.238 brouard 7304: fprintf(ficgp,"\n#\n");
7305: if(invalidvarcomb[k1]){
1.260 brouard 7306: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7307: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7308: continue;
7309: }
1.235 brouard 7310:
1.241 brouard 7311: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7312: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7313: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
7314: fprintf(ficgp,"set title \"Alive state %d %s\" font \"Helvetica,12\"\n",cpt,gplotlabel);
1.260 brouard 7315: 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);
7316: /* 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); */
7317: /* k1-1 error should be nres-1*/
1.238 brouard 7318: for (i=1; i<= nlstate ; i ++) {
7319: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7320: else fprintf(ficgp," %%*lf (%%*lf)");
7321: }
1.288 brouard 7322: 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 7323: for (i=1; i<= nlstate ; i ++) {
7324: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7325: else fprintf(ficgp," %%*lf (%%*lf)");
7326: }
1.260 brouard 7327: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7328: for (i=1; i<= nlstate ; i ++) {
7329: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7330: else fprintf(ficgp," %%*lf (%%*lf)");
7331: }
1.265 brouard 7332: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7333:
7334: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7335: if(cptcoveff ==0){
1.271 brouard 7336: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7337: }else{
7338: kl=0;
7339: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7340: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7341: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7342: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7343: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7344: vlv= nbcode[Tvaraff[k]][lv];
7345: kl++;
7346: /* 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 *\/ */
7347: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7348: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7349: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7350: if(k==cptcoveff){
7351: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7352: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7353: }else{
7354: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7355: kl++;
7356: }
7357: } /* end covariate */
7358: } /* end if no covariate */
7359:
1.296 brouard 7360: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 7361: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7362: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7363: if(cptcoveff ==0){
1.245 brouard 7364: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7365: }else{
7366: kl=0;
7367: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7368: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7369: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7370: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7371: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7372: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7373: kl++;
1.238 brouard 7374: /* 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 *\/ */
7375: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7376: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7377: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7378: if(k==cptcoveff){
1.245 brouard 7379: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7380: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7381: }else{
7382: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7383: kl++;
7384: }
7385: } /* end covariate */
7386: } /* end if no covariate */
1.296 brouard 7387: if(prevbcast == 1){
1.268 brouard 7388: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7389: /* k1-1 error should be nres-1*/
7390: for (i=1; i<= nlstate ; i ++) {
7391: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7392: else fprintf(ficgp," %%*lf (%%*lf)");
7393: }
1.271 brouard 7394: 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 7395: for (i=1; i<= nlstate ; i ++) {
7396: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7397: else fprintf(ficgp," %%*lf (%%*lf)");
7398: }
1.276 brouard 7399: 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 7400: for (i=1; i<= nlstate ; i ++) {
7401: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7402: else fprintf(ficgp," %%*lf (%%*lf)");
7403: }
1.274 brouard 7404: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7405: } /* end if backprojcast */
1.296 brouard 7406: } /* end if prevbcast */
1.276 brouard 7407: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7408: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7409: } /* nres */
1.201 brouard 7410: } /* k1 */
7411: } /* cpt */
1.235 brouard 7412:
7413:
1.126 brouard 7414: /*2 eme*/
1.238 brouard 7415: for (k1=1; k1<= m ; k1 ++){
7416: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7417: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7418: continue;
7419: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7420: strcpy(gplotlabel,"(");
1.238 brouard 7421: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7422: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7423: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7424: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7425: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7426: vlv= nbcode[Tvaraff[k]][lv];
7427: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7428: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7429: }
1.237 brouard 7430: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7431: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7432: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7433: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7434: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7435: }
1.264 brouard 7436: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7437: fprintf(ficgp,"\n#\n");
1.223 brouard 7438: if(invalidvarcomb[k1]){
7439: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7440: continue;
7441: }
1.219 brouard 7442:
1.241 brouard 7443: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7444: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7445: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7446: if(vpopbased==0){
1.238 brouard 7447: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7448: }else
1.238 brouard 7449: fprintf(ficgp,"\nreplot ");
7450: for (i=1; i<= nlstate+1 ; i ++) {
7451: k=2*i;
1.261 brouard 7452: 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 7453: for (j=1; j<= nlstate+1 ; j ++) {
7454: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7455: else fprintf(ficgp," %%*lf (%%*lf)");
7456: }
7457: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7458: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7459: 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 7460: for (j=1; j<= nlstate+1 ; j ++) {
7461: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7462: else fprintf(ficgp," %%*lf (%%*lf)");
7463: }
7464: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7465: 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 7466: for (j=1; j<= nlstate+1 ; j ++) {
7467: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7468: else fprintf(ficgp," %%*lf (%%*lf)");
7469: }
7470: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7471: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7472: } /* state */
7473: } /* vpopbased */
1.264 brouard 7474: 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 7475: } /* end nres */
7476: } /* k1 end 2 eme*/
7477:
7478:
7479: /*3eme*/
7480: for (k1=1; k1<= m ; k1 ++){
7481: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7482: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7483: continue;
7484:
7485: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7486: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7487: strcpy(gplotlabel,"(");
1.238 brouard 7488: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7489: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7490: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7491: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7492: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7493: vlv= nbcode[Tvaraff[k]][lv];
7494: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7495: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7496: }
7497: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7498: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7499: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7500: }
1.264 brouard 7501: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7502: fprintf(ficgp,"\n#\n");
7503: if(invalidvarcomb[k1]){
7504: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7505: continue;
7506: }
7507:
7508: /* k=2+nlstate*(2*cpt-2); */
7509: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7510: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7511: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7512: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7513: 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 7514: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7515: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7516: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7517: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7518: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7519: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7520:
1.238 brouard 7521: */
7522: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7523: 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 7524: /* 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 7525:
1.238 brouard 7526: }
1.261 brouard 7527: 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 7528: }
1.264 brouard 7529: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7530: } /* end nres */
7531: } /* end kl 3eme */
1.126 brouard 7532:
1.223 brouard 7533: /* 4eme */
1.201 brouard 7534: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7535: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7536: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7537: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7538: continue;
1.238 brouard 7539: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7540: strcpy(gplotlabel,"(");
1.238 brouard 7541: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7542: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7543: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7544: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7545: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7546: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7547: vlv= nbcode[Tvaraff[k]][lv];
7548: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7549: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7550: }
7551: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7552: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7553: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7554: }
1.264 brouard 7555: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7556: fprintf(ficgp,"\n#\n");
7557: if(invalidvarcomb[k1]){
7558: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7559: continue;
1.223 brouard 7560: }
1.238 brouard 7561:
1.241 brouard 7562: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7563: 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 7564: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7565: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7566: k=3;
7567: for (i=1; i<= nlstate ; i ++){
7568: if(i==1){
7569: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7570: }else{
7571: fprintf(ficgp,", '' ");
7572: }
7573: l=(nlstate+ndeath)*(i-1)+1;
7574: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7575: for (j=2; j<= nlstate+ndeath ; j ++)
7576: fprintf(ficgp,"+$%d",k+l+j-1);
7577: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7578: } /* nlstate */
1.264 brouard 7579: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7580: } /* end cpt state*/
7581: } /* end nres */
7582: } /* end covariate k1 */
7583:
1.220 brouard 7584: /* 5eme */
1.201 brouard 7585: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7586: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7587: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7588: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7589: continue;
1.238 brouard 7590: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7591: strcpy(gplotlabel,"(");
1.238 brouard 7592: 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);
7593: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7594: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7595: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7596: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7597: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7598: vlv= nbcode[Tvaraff[k]][lv];
7599: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7600: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7601: }
7602: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7603: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7604: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7605: }
1.264 brouard 7606: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7607: fprintf(ficgp,"\n#\n");
7608: if(invalidvarcomb[k1]){
7609: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7610: continue;
7611: }
1.227 brouard 7612:
1.241 brouard 7613: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7614: 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 7615: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7616: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7617: k=3;
7618: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7619: if(j==1)
7620: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7621: else
7622: fprintf(ficgp,", '' ");
7623: l=(nlstate+ndeath)*(cpt-1) +j;
7624: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7625: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7626: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7627: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7628: } /* nlstate */
7629: fprintf(ficgp,", '' ");
7630: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7631: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7632: l=(nlstate+ndeath)*(cpt-1) +j;
7633: if(j < nlstate)
7634: fprintf(ficgp,"$%d +",k+l);
7635: else
7636: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7637: }
1.264 brouard 7638: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7639: } /* end cpt state*/
7640: } /* end covariate */
7641: } /* end nres */
1.227 brouard 7642:
1.220 brouard 7643: /* 6eme */
1.202 brouard 7644: /* CV preval stable (period) for each covariate */
1.237 brouard 7645: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7646: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7647: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7648: continue;
1.255 brouard 7649: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7650: strcpy(gplotlabel,"(");
1.288 brouard 7651: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7652: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7653: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7654: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7655: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7656: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7657: vlv= nbcode[Tvaraff[k]][lv];
7658: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7659: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7660: }
1.237 brouard 7661: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7662: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7663: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7664: }
1.264 brouard 7665: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7666: fprintf(ficgp,"\n#\n");
1.223 brouard 7667: if(invalidvarcomb[k1]){
1.227 brouard 7668: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7669: continue;
1.223 brouard 7670: }
1.227 brouard 7671:
1.241 brouard 7672: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7673: 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 7674: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7675: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7676: k=3; /* Offset */
1.255 brouard 7677: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7678: if(i==1)
7679: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7680: else
7681: fprintf(ficgp,", '' ");
1.255 brouard 7682: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7683: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7684: for (j=2; j<= nlstate ; j ++)
7685: fprintf(ficgp,"+$%d",k+l+j-1);
7686: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7687: } /* nlstate */
1.264 brouard 7688: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7689: } /* end cpt state*/
7690: } /* end covariate */
1.227 brouard 7691:
7692:
1.220 brouard 7693: /* 7eme */
1.296 brouard 7694: if(prevbcast == 1){
1.288 brouard 7695: /* CV backward prevalence for each covariate */
1.237 brouard 7696: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7697: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7698: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7699: continue;
1.268 brouard 7700: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7701: strcpy(gplotlabel,"(");
1.288 brouard 7702: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7703: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7704: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7705: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7706: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7707: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7708: vlv= nbcode[Tvaraff[k]][lv];
7709: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7710: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7711: }
1.237 brouard 7712: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7713: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7714: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7715: }
1.264 brouard 7716: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7717: fprintf(ficgp,"\n#\n");
7718: if(invalidvarcomb[k1]){
7719: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7720: continue;
7721: }
7722:
1.241 brouard 7723: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7724: 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 7725: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7726: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7727: k=3; /* Offset */
1.268 brouard 7728: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7729: if(i==1)
7730: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7731: else
7732: fprintf(ficgp,", '' ");
7733: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7734: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7735: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7736: /* 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 7737: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7738: /* for (j=2; j<= nlstate ; j ++) */
7739: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7740: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7741: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7742: } /* nlstate */
1.264 brouard 7743: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7744: } /* end cpt state*/
7745: } /* end covariate */
1.296 brouard 7746: } /* End if prevbcast */
1.218 brouard 7747:
1.223 brouard 7748: /* 8eme */
1.218 brouard 7749: if(prevfcast==1){
1.288 brouard 7750: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 7751:
1.237 brouard 7752: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7753: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7754: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7755: continue;
1.211 brouard 7756: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7757: strcpy(gplotlabel,"(");
1.288 brouard 7758: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7759: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7760: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7761: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7762: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7763: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7764: vlv= nbcode[Tvaraff[k]][lv];
7765: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7766: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7767: }
1.237 brouard 7768: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7769: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7770: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7771: }
1.264 brouard 7772: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7773: fprintf(ficgp,"\n#\n");
7774: if(invalidvarcomb[k1]){
7775: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7776: continue;
7777: }
7778:
7779: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7780: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7781: 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 7782: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7783: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7784:
7785: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7786: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7787: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7788: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7789: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7790: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7791: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7792: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7793: if(i==istart){
1.227 brouard 7794: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7795: }else{
7796: fprintf(ficgp,",\\\n '' ");
7797: }
7798: if(cptcoveff ==0){ /* No covariate */
7799: ioffset=2; /* Age is in 2 */
7800: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7801: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7802: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7803: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7804: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7805: if(i==nlstate+1){
1.270 brouard 7806: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 7807: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7808: fprintf(ficgp,",\\\n '' ");
7809: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7810: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 7811: offyear, \
1.268 brouard 7812: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7813: }else
1.227 brouard 7814: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7815: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7816: }else{ /* more than 2 covariates */
1.270 brouard 7817: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7818: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7819: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7820: iyearc=ioffset-1;
7821: iagec=ioffset;
1.227 brouard 7822: fprintf(ficgp," u %d:(",ioffset);
7823: kl=0;
7824: strcpy(gplotcondition,"(");
7825: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7826: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7827: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7828: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7829: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7830: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7831: kl++;
7832: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7833: kl++;
7834: if(k <cptcoveff && cptcoveff>1)
7835: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7836: }
7837: strcpy(gplotcondition+strlen(gplotcondition),")");
7838: /* 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 *\/ */
7839: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7840: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7841: /* '' 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*/
7842: if(i==nlstate+1){
1.270 brouard 7843: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
7844: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 7845: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7846: fprintf(ficgp," u %d:(",iagec);
7847: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
7848: iyearc, iagec, offyear, \
7849: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 7850: /* '' 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 7851: }else{
7852: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7853: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7854: }
7855: } /* end if covariate */
7856: } /* nlstate */
1.264 brouard 7857: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7858: } /* end cpt state*/
7859: } /* end covariate */
7860: } /* End if prevfcast */
1.227 brouard 7861:
1.296 brouard 7862: if(prevbcast==1){
1.268 brouard 7863: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7864:
7865: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7866: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7867: if(m != 1 && TKresult[nres]!= k1)
7868: continue;
7869: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7870: strcpy(gplotlabel,"(");
7871: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7872: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7873: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7874: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7875: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7876: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7877: vlv= nbcode[Tvaraff[k]][lv];
7878: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7879: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7880: }
7881: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7882: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7883: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7884: }
7885: strcpy(gplotlabel+strlen(gplotlabel),")");
7886: fprintf(ficgp,"\n#\n");
7887: if(invalidvarcomb[k1]){
7888: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7889: continue;
7890: }
7891:
7892: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7893: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7894: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7895: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7896: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7897:
7898: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7899: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7900: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7901: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7902: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7903: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7904: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7905: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7906: if(i==istart){
7907: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
7908: }else{
7909: fprintf(ficgp,",\\\n '' ");
7910: }
7911: if(cptcoveff ==0){ /* No covariate */
7912: ioffset=2; /* Age is in 2 */
7913: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7914: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7915: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7916: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7917: fprintf(ficgp," u %d:(", ioffset);
7918: if(i==nlstate+1){
1.270 brouard 7919: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 7920: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7921: fprintf(ficgp,",\\\n '' ");
7922: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7923: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 7924: offbyear, \
7925: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7926: }else
7927: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
7928: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
7929: }else{ /* more than 2 covariates */
1.270 brouard 7930: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7931: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7932: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7933: iyearc=ioffset-1;
7934: iagec=ioffset;
1.268 brouard 7935: fprintf(ficgp," u %d:(",ioffset);
7936: kl=0;
7937: strcpy(gplotcondition,"(");
7938: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7939: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7940: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7941: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7942: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7943: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7944: kl++;
7945: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7946: kl++;
7947: if(k <cptcoveff && cptcoveff>1)
7948: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7949: }
7950: strcpy(gplotcondition+strlen(gplotcondition),")");
7951: /* 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 *\/ */
7952: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7953: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7954: /* '' 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*/
7955: if(i==nlstate+1){
1.270 brouard 7956: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
7957: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 7958: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7959: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 7960: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 7961: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
7962: iyearc,iagec,offbyear, \
7963: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 7964: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
7965: }else{
7966: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
7967: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
7968: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
7969: }
7970: } /* end if covariate */
7971: } /* nlstate */
7972: fprintf(ficgp,"\nset out; unset label;\n");
7973: } /* end cpt state*/
7974: } /* end covariate */
1.296 brouard 7975: } /* End if prevbcast */
1.268 brouard 7976:
1.227 brouard 7977:
1.238 brouard 7978: /* 9eme writing MLE parameters */
7979: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7980: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7981: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7982: for(k=1; k <=(nlstate+ndeath); k++){
7983: if (k != i) {
1.227 brouard 7984: fprintf(ficgp,"# current state %d\n",k);
7985: for(j=1; j <=ncovmodel; j++){
7986: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7987: jk++;
7988: }
7989: fprintf(ficgp,"\n");
1.126 brouard 7990: }
7991: }
1.223 brouard 7992: }
1.187 brouard 7993: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7994:
1.145 brouard 7995: /*goto avoid;*/
1.238 brouard 7996: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7997: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7998: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7999: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
8000: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
8001: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
8002: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8003: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8004: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8005: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
8006: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
8007: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
8008: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
8009: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
8010: fprintf(ficgp,"#\n");
1.223 brouard 8011: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 8012: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 8013: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 8014: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 8015: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
8016: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 8017: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 8018: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 8019: continue;
1.264 brouard 8020: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
8021: strcpy(gplotlabel,"(");
1.276 brouard 8022: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 8023: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
8024: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
8025: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8026: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8027: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8028: vlv= nbcode[Tvaraff[k]][lv];
8029: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
8030: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
8031: }
1.237 brouard 8032: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8033: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 8034: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 8035: }
1.264 brouard 8036: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 8037: fprintf(ficgp,"\n#\n");
1.264 brouard 8038: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 8039: fprintf(ficgp,"\nset key outside ");
8040: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
8041: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 8042: fprintf(ficgp,"\nset ter svg size 640, 480 ");
8043: if (ng==1){
8044: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
8045: fprintf(ficgp,"\nunset log y");
8046: }else if (ng==2){
8047: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
8048: fprintf(ficgp,"\nset log y");
8049: }else if (ng==3){
8050: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
8051: fprintf(ficgp,"\nset log y");
8052: }else
8053: fprintf(ficgp,"\nunset title ");
8054: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
8055: i=1;
8056: for(k2=1; k2<=nlstate; k2++) {
8057: k3=i;
8058: for(k=1; k<=(nlstate+ndeath); k++) {
8059: if (k != k2){
8060: switch( ng) {
8061: case 1:
8062: if(nagesqr==0)
8063: fprintf(ficgp," p%d+p%d*x",i,i+1);
8064: else /* nagesqr =1 */
8065: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8066: break;
8067: case 2: /* ng=2 */
8068: if(nagesqr==0)
8069: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
8070: else /* nagesqr =1 */
8071: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
8072: break;
8073: case 3:
8074: if(nagesqr==0)
8075: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
8076: else /* nagesqr =1 */
8077: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
8078: break;
8079: }
8080: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 8081: ijp=1; /* product no age */
8082: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
8083: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 8084: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 8085: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8086: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
8087: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
8088: if(DummyV[j]==0){
8089: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
8090: }else{ /* quantitative */
8091: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
8092: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8093: }
8094: ij++;
1.237 brouard 8095: }
1.268 brouard 8096: }
8097: }else if(cptcovprod >0){
8098: if(j==Tprod[ijp]) { /* */
8099: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
8100: if(ijp <=cptcovprod) { /* Product */
8101: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
8102: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
8103: /* 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)]); */
8104: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
8105: }else{ /* Vn is dummy and Vm is quanti */
8106: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
8107: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8108: }
8109: }else{ /* Vn*Vm Vn is quanti */
8110: if(DummyV[Tvard[ijp][2]]==0){
8111: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
8112: }else{ /* Both quanti */
8113: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
8114: }
1.237 brouard 8115: }
1.268 brouard 8116: ijp++;
1.237 brouard 8117: }
1.268 brouard 8118: } /* end Tprod */
1.237 brouard 8119: } else{ /* simple covariate */
1.264 brouard 8120: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 8121: if(Dummy[j]==0){
8122: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
8123: }else{ /* quantitative */
8124: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 8125: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 8126: }
1.237 brouard 8127: } /* end simple */
8128: } /* end j */
1.223 brouard 8129: }else{
8130: i=i-ncovmodel;
8131: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
8132: fprintf(ficgp," (1.");
8133: }
1.227 brouard 8134:
1.223 brouard 8135: if(ng != 1){
8136: fprintf(ficgp,")/(1");
1.227 brouard 8137:
1.264 brouard 8138: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8139: if(nagesqr==0)
1.264 brouard 8140: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8141: else /* nagesqr =1 */
1.264 brouard 8142: 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 8143:
1.223 brouard 8144: ij=1;
8145: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 8146: if(cptcovage >0){
8147: if((j-2)==Tage[ij]) { /* Bug valgrind */
8148: if(ij <=cptcovage) { /* Bug valgrind */
8149: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
8150: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8151: ij++;
8152: }
8153: }
8154: }else
8155: 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 8156: }
8157: fprintf(ficgp,")");
8158: }
8159: fprintf(ficgp,")");
8160: if(ng ==2)
1.276 brouard 8161: 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 8162: else /* ng= 3 */
1.276 brouard 8163: 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 8164: }else{ /* end ng <> 1 */
8165: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8166: 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 8167: }
8168: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8169: fprintf(ficgp,",");
8170: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8171: fprintf(ficgp,",");
8172: i=i+ncovmodel;
8173: } /* end k */
8174: } /* end k2 */
1.276 brouard 8175: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8176: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8177: } /* end k1 */
1.223 brouard 8178: } /* end ng */
8179: /* avoid: */
8180: fflush(ficgp);
1.126 brouard 8181: } /* end gnuplot */
8182:
8183:
8184: /*************** Moving average **************/
1.219 brouard 8185: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8186: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8187:
1.222 brouard 8188: int i, cpt, cptcod;
8189: int modcovmax =1;
8190: int mobilavrange, mob;
8191: int iage=0;
1.288 brouard 8192: int firstA1=0, firstA2=0;
1.222 brouard 8193:
1.266 brouard 8194: double sum=0., sumr=0.;
1.222 brouard 8195: double age;
1.266 brouard 8196: double *sumnewp, *sumnewm, *sumnewmr;
8197: double *agemingood, *agemaxgood;
8198: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8199:
8200:
1.278 brouard 8201: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8202: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8203:
8204: sumnewp = vector(1,ncovcombmax);
8205: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8206: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8207: agemingood = vector(1,ncovcombmax);
1.266 brouard 8208: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8209: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8210: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8211:
8212: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8213: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8214: sumnewp[cptcod]=0.;
1.266 brouard 8215: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8216: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8217: }
8218: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8219:
1.266 brouard 8220: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8221: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8222: else mobilavrange=mobilav;
8223: for (age=bage; age<=fage; age++)
8224: for (i=1; i<=nlstate;i++)
8225: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8226: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8227: /* We keep the original values on the extreme ages bage, fage and for
8228: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8229: we use a 5 terms etc. until the borders are no more concerned.
8230: */
8231: for (mob=3;mob <=mobilavrange;mob=mob+2){
8232: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8233: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8234: sumnewm[cptcod]=0.;
8235: for (i=1; i<=nlstate;i++){
1.222 brouard 8236: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8237: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8238: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8239: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8240: }
8241: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8242: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8243: } /* end i */
8244: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8245: } /* end cptcod */
1.222 brouard 8246: }/* end age */
8247: }/* end mob */
1.266 brouard 8248: }else{
8249: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8250: return -1;
1.266 brouard 8251: }
8252:
8253: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8254: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8255: if(invalidvarcomb[cptcod]){
8256: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8257: continue;
8258: }
1.219 brouard 8259:
1.266 brouard 8260: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8261: sumnewm[cptcod]=0.;
8262: sumnewmr[cptcod]=0.;
8263: for (i=1; i<=nlstate;i++){
8264: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8265: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8266: }
8267: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8268: agemingoodr[cptcod]=age;
8269: }
8270: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8271: agemingood[cptcod]=age;
8272: }
8273: } /* age */
8274: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8275: sumnewm[cptcod]=0.;
1.266 brouard 8276: sumnewmr[cptcod]=0.;
1.222 brouard 8277: for (i=1; i<=nlstate;i++){
8278: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8279: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8280: }
8281: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8282: agemaxgoodr[cptcod]=age;
1.222 brouard 8283: }
8284: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8285: agemaxgood[cptcod]=age;
8286: }
8287: } /* age */
8288: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8289: /* but they will change */
1.288 brouard 8290: firstA1=0;firstA2=0;
1.266 brouard 8291: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8292: sumnewm[cptcod]=0.;
8293: sumnewmr[cptcod]=0.;
8294: for (i=1; i<=nlstate;i++){
8295: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8296: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8297: }
8298: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8299: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8300: agemaxgoodr[cptcod]=age; /* age min */
8301: for (i=1; i<=nlstate;i++)
8302: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8303: }else{ /* bad we change the value with the values of good ages */
8304: for (i=1; i<=nlstate;i++){
8305: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8306: } /* i */
8307: } /* end bad */
8308: }else{
8309: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8310: agemaxgood[cptcod]=age;
8311: }else{ /* bad we change the value with the values of good ages */
8312: for (i=1; i<=nlstate;i++){
8313: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8314: } /* i */
8315: } /* end bad */
8316: }/* end else */
8317: sum=0.;sumr=0.;
8318: for (i=1; i<=nlstate;i++){
8319: sum+=mobaverage[(int)age][i][cptcod];
8320: sumr+=probs[(int)age][i][cptcod];
8321: }
8322: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8323: if(!firstA1){
8324: firstA1=1;
8325: 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);
8326: }
8327: 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 8328: } /* end bad */
8329: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8330: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 8331: if(!firstA2){
8332: firstA2=1;
8333: 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);
8334: }
8335: 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 8336: } /* end bad */
8337: }/* age */
1.266 brouard 8338:
8339: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8340: sumnewm[cptcod]=0.;
1.266 brouard 8341: sumnewmr[cptcod]=0.;
1.222 brouard 8342: for (i=1; i<=nlstate;i++){
8343: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8344: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8345: }
8346: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8347: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8348: agemingoodr[cptcod]=age;
8349: for (i=1; i<=nlstate;i++)
8350: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8351: }else{ /* bad we change the value with the values of good ages */
8352: for (i=1; i<=nlstate;i++){
8353: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8354: } /* i */
8355: } /* end bad */
8356: }else{
8357: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8358: agemingood[cptcod]=age;
8359: }else{ /* bad */
8360: for (i=1; i<=nlstate;i++){
8361: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8362: } /* i */
8363: } /* end bad */
8364: }/* end else */
8365: sum=0.;sumr=0.;
8366: for (i=1; i<=nlstate;i++){
8367: sum+=mobaverage[(int)age][i][cptcod];
8368: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8369: }
1.266 brouard 8370: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8371: 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 8372: } /* end bad */
8373: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8374: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8375: 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 8376: } /* end bad */
8377: }/* age */
1.266 brouard 8378:
1.222 brouard 8379:
8380: for (age=bage; age<=fage; age++){
1.235 brouard 8381: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8382: sumnewp[cptcod]=0.;
8383: sumnewm[cptcod]=0.;
8384: for (i=1; i<=nlstate;i++){
8385: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8386: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8387: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8388: }
8389: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8390: }
8391: /* printf("\n"); */
8392: /* } */
1.266 brouard 8393:
1.222 brouard 8394: /* brutal averaging */
1.266 brouard 8395: /* for (i=1; i<=nlstate;i++){ */
8396: /* for (age=1; age<=bage; age++){ */
8397: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8398: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8399: /* } */
8400: /* for (age=fage; age<=AGESUP; age++){ */
8401: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8402: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8403: /* } */
8404: /* } /\* end i status *\/ */
8405: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8406: /* for (age=1; age<=AGESUP; age++){ */
8407: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8408: /* mobaverage[(int)age][i][cptcod]=0.; */
8409: /* } */
8410: /* } */
1.222 brouard 8411: }/* end cptcod */
1.266 brouard 8412: free_vector(agemaxgoodr,1, ncovcombmax);
8413: free_vector(agemaxgood,1, ncovcombmax);
8414: free_vector(agemingood,1, ncovcombmax);
8415: free_vector(agemingoodr,1, ncovcombmax);
8416: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8417: free_vector(sumnewm,1, ncovcombmax);
8418: free_vector(sumnewp,1, ncovcombmax);
8419: return 0;
8420: }/* End movingaverage */
1.218 brouard 8421:
1.126 brouard 8422:
1.296 brouard 8423:
1.126 brouard 8424: /************** Forecasting ******************/
1.296 brouard 8425: /* 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)*/
8426: 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){
8427: /* dateintemean, mean date of interviews
8428: dateprojd, year, month, day of starting projection
8429: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 8430: agemin, agemax range of age
8431: dateprev1 dateprev2 range of dates during which prevalence is computed
8432: */
1.296 brouard 8433: /* double anprojd, mprojd, jprojd; */
8434: /* double anprojf, mprojf, jprojf; */
1.267 brouard 8435: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8436: double agec; /* generic age */
1.296 brouard 8437: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 8438: double *popeffectif,*popcount;
8439: double ***p3mat;
1.218 brouard 8440: /* double ***mobaverage; */
1.126 brouard 8441: char fileresf[FILENAMELENGTH];
8442:
8443: agelim=AGESUP;
1.211 brouard 8444: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8445: in each health status at the date of interview (if between dateprev1 and dateprev2).
8446: We still use firstpass and lastpass as another selection.
8447: */
1.214 brouard 8448: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8449: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8450:
1.201 brouard 8451: strcpy(fileresf,"F_");
8452: strcat(fileresf,fileresu);
1.126 brouard 8453: if((ficresf=fopen(fileresf,"w"))==NULL) {
8454: printf("Problem with forecast resultfile: %s\n", fileresf);
8455: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8456: }
1.235 brouard 8457: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8458: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8459:
1.225 brouard 8460: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8461:
8462:
8463: stepsize=(int) (stepm+YEARM-1)/YEARM;
8464: if (stepm<=12) stepsize=1;
8465: if(estepm < stepm){
8466: printf ("Problem %d lower than %d\n",estepm, stepm);
8467: }
1.270 brouard 8468: else{
8469: hstepm=estepm;
8470: }
8471: if(estepm > stepm){ /* Yes every two year */
8472: stepsize=2;
8473: }
1.296 brouard 8474: hstepm=hstepm/stepm;
1.126 brouard 8475:
1.296 brouard 8476:
8477: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8478: /* fractional in yp1 *\/ */
8479: /* aintmean=yp; */
8480: /* yp2=modf((yp1*12),&yp); */
8481: /* mintmean=yp; */
8482: /* yp1=modf((yp2*30.5),&yp); */
8483: /* jintmean=yp; */
8484: /* if(jintmean==0) jintmean=1; */
8485: /* if(mintmean==0) mintmean=1; */
1.126 brouard 8486:
1.296 brouard 8487:
8488: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
8489: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
8490: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.227 brouard 8491: i1=pow(2,cptcoveff);
1.126 brouard 8492: if (cptcovn < 1){i1=1;}
8493:
1.296 brouard 8494: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 8495:
8496: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8497:
1.126 brouard 8498: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8499: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8500: for(k=1; k<=i1;k++){
1.253 brouard 8501: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8502: continue;
1.227 brouard 8503: if(invalidvarcomb[k]){
8504: printf("\nCombination (%d) projection ignored because no cases \n",k);
8505: continue;
8506: }
8507: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8508: for(j=1;j<=cptcoveff;j++) {
8509: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8510: }
1.235 brouard 8511: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8512: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8513: }
1.227 brouard 8514: fprintf(ficresf," yearproj age");
8515: for(j=1; j<=nlstate+ndeath;j++){
8516: for(i=1; i<=nlstate;i++)
8517: fprintf(ficresf," p%d%d",i,j);
8518: fprintf(ficresf," wp.%d",j);
8519: }
1.296 brouard 8520: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 8521: fprintf(ficresf,"\n");
1.296 brouard 8522: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 8523: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8524: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8525: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8526: nhstepm = nhstepm/hstepm;
8527: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8528: oldm=oldms;savm=savms;
1.268 brouard 8529: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8530: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8531: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8532: for (h=0; h<=nhstepm; h++){
8533: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8534: break;
8535: }
8536: }
8537: fprintf(ficresf,"\n");
8538: for(j=1;j<=cptcoveff;j++)
8539: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 8540: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 8541:
8542: for(j=1; j<=nlstate+ndeath;j++) {
8543: ppij=0.;
8544: for(i=1; i<=nlstate;i++) {
1.278 brouard 8545: if (mobilav>=1)
8546: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8547: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8548: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8549: }
1.268 brouard 8550: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8551: } /* end i */
8552: fprintf(ficresf," %.3f", ppij);
8553: }/* end j */
1.227 brouard 8554: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8555: } /* end agec */
1.266 brouard 8556: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8557: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8558: } /* end yearp */
8559: } /* end k */
1.219 brouard 8560:
1.126 brouard 8561: fclose(ficresf);
1.215 brouard 8562: printf("End of Computing forecasting \n");
8563: fprintf(ficlog,"End of Computing forecasting\n");
8564:
1.126 brouard 8565: }
8566:
1.269 brouard 8567: /************** Back Forecasting ******************/
1.296 brouard 8568: /* 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){ */
8569: 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){
8570: /* back1, year, month, day of starting backprojection
1.267 brouard 8571: agemin, agemax range of age
8572: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8573: anback2 year of end of backprojection (same day and month as back1).
8574: prevacurrent and prev are prevalences.
1.267 brouard 8575: */
8576: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8577: double agec; /* generic age */
1.302 brouard 8578: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 8579: double *popeffectif,*popcount;
8580: double ***p3mat;
8581: /* double ***mobaverage; */
8582: char fileresfb[FILENAMELENGTH];
8583:
1.268 brouard 8584: agelim=AGEINF;
1.267 brouard 8585: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8586: in each health status at the date of interview (if between dateprev1 and dateprev2).
8587: We still use firstpass and lastpass as another selection.
8588: */
8589: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8590: /* firstpass, lastpass, stepm, weightopt, model); */
8591:
8592: /*Do we need to compute prevalence again?*/
8593:
8594: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8595:
8596: strcpy(fileresfb,"FB_");
8597: strcat(fileresfb,fileresu);
8598: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8599: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8600: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8601: }
8602: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8603: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8604:
8605: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8606:
8607:
8608: stepsize=(int) (stepm+YEARM-1)/YEARM;
8609: if (stepm<=12) stepsize=1;
8610: if(estepm < stepm){
8611: printf ("Problem %d lower than %d\n",estepm, stepm);
8612: }
1.270 brouard 8613: else{
8614: hstepm=estepm;
8615: }
8616: if(estepm >= stepm){ /* Yes every two year */
8617: stepsize=2;
8618: }
1.267 brouard 8619:
8620: hstepm=hstepm/stepm;
1.296 brouard 8621: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
8622: /* fractional in yp1 *\/ */
8623: /* aintmean=yp; */
8624: /* yp2=modf((yp1*12),&yp); */
8625: /* mintmean=yp; */
8626: /* yp1=modf((yp2*30.5),&yp); */
8627: /* jintmean=yp; */
8628: /* if(jintmean==0) jintmean=1; */
8629: /* if(mintmean==0) jintmean=1; */
1.267 brouard 8630:
8631: i1=pow(2,cptcoveff);
8632: if (cptcovn < 1){i1=1;}
8633:
1.296 brouard 8634: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
8635: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8636:
8637: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8638:
8639: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8640: for(k=1; k<=i1;k++){
8641: if(i1 != 1 && TKresult[nres]!= k)
8642: continue;
8643: if(invalidvarcomb[k]){
8644: printf("\nCombination (%d) projection ignored because no cases \n",k);
8645: continue;
8646: }
1.268 brouard 8647: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8648: for(j=1;j<=cptcoveff;j++) {
8649: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8650: }
8651: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8652: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8653: }
8654: fprintf(ficresfb," yearbproj age");
8655: for(j=1; j<=nlstate+ndeath;j++){
8656: for(i=1; i<=nlstate;i++)
1.268 brouard 8657: fprintf(ficresfb," b%d%d",i,j);
8658: fprintf(ficresfb," b.%d",j);
1.267 brouard 8659: }
1.296 brouard 8660: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 8661: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8662: fprintf(ficresfb,"\n");
1.296 brouard 8663: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 8664: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8665: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8666: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8667: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8668: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8669: nhstepm = nhstepm/hstepm;
8670: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8671: oldm=oldms;savm=savms;
1.268 brouard 8672: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8673: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8674: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8675: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8676: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8677: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8678: for (h=0; h<=nhstepm; h++){
1.268 brouard 8679: if (h*hstepm/YEARM*stepm ==-yearp) {
8680: break;
8681: }
8682: }
8683: fprintf(ficresfb,"\n");
8684: for(j=1;j<=cptcoveff;j++)
8685: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.296 brouard 8686: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 8687: for(i=1; i<=nlstate+ndeath;i++) {
8688: ppij=0.;ppi=0.;
8689: for(j=1; j<=nlstate;j++) {
8690: /* if (mobilav==1) */
1.269 brouard 8691: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8692: ppi=ppi+prevacurrent[(int)agec][j][k];
8693: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8694: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8695: /* else { */
8696: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8697: /* } */
1.268 brouard 8698: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8699: } /* end j */
8700: if(ppi <0.99){
8701: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8702: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8703: }
8704: fprintf(ficresfb," %.3f", ppij);
8705: }/* end j */
1.267 brouard 8706: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8707: } /* end agec */
8708: } /* end yearp */
8709: } /* end k */
1.217 brouard 8710:
1.267 brouard 8711: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8712:
1.267 brouard 8713: fclose(ficresfb);
8714: printf("End of Computing Back forecasting \n");
8715: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8716:
1.267 brouard 8717: }
1.217 brouard 8718:
1.269 brouard 8719: /* Variance of prevalence limit: varprlim */
8720: 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 8721: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 8722:
8723: char fileresvpl[FILENAMELENGTH];
8724: FILE *ficresvpl;
8725: double **oldm, **savm;
8726: double **varpl; /* Variances of prevalence limits by age */
8727: int i1, k, nres, j ;
8728:
8729: strcpy(fileresvpl,"VPL_");
8730: strcat(fileresvpl,fileresu);
8731: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 8732: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 8733: exit(0);
8734: }
1.288 brouard 8735: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8736: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 8737:
8738: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8739: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8740:
8741: i1=pow(2,cptcoveff);
8742: if (cptcovn < 1){i1=1;}
8743:
8744: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8745: for(k=1; k<=i1;k++){
8746: if(i1 != 1 && TKresult[nres]!= k)
8747: continue;
8748: fprintf(ficresvpl,"\n#****** ");
8749: printf("\n#****** ");
8750: fprintf(ficlog,"\n#****** ");
8751: for(j=1;j<=cptcoveff;j++) {
8752: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8753: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8754: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8755: }
8756: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8757: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8758: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8759: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8760: }
8761: fprintf(ficresvpl,"******\n");
8762: printf("******\n");
8763: fprintf(ficlog,"******\n");
8764:
8765: varpl=matrix(1,nlstate,(int) bage, (int) fage);
8766: oldm=oldms;savm=savms;
8767: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
8768: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
8769: /*}*/
8770: }
8771:
8772: fclose(ficresvpl);
1.288 brouard 8773: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
8774: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 8775:
8776: }
8777: /* Variance of back prevalence: varbprlim */
8778: 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){
8779: /*------- Variance of back (stable) prevalence------*/
8780:
8781: char fileresvbl[FILENAMELENGTH];
8782: FILE *ficresvbl;
8783:
8784: double **oldm, **savm;
8785: double **varbpl; /* Variances of back prevalence limits by age */
8786: int i1, k, nres, j ;
8787:
8788: strcpy(fileresvbl,"VBL_");
8789: strcat(fileresvbl,fileresu);
8790: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
8791: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
8792: exit(0);
8793: }
8794: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
8795: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
8796:
8797:
8798: i1=pow(2,cptcoveff);
8799: if (cptcovn < 1){i1=1;}
8800:
8801: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8802: for(k=1; k<=i1;k++){
8803: if(i1 != 1 && TKresult[nres]!= k)
8804: continue;
8805: fprintf(ficresvbl,"\n#****** ");
8806: printf("\n#****** ");
8807: fprintf(ficlog,"\n#****** ");
8808: for(j=1;j<=cptcoveff;j++) {
8809: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8810: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8811: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8812: }
8813: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8814: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8815: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8816: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8817: }
8818: fprintf(ficresvbl,"******\n");
8819: printf("******\n");
8820: fprintf(ficlog,"******\n");
8821:
8822: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
8823: oldm=oldms;savm=savms;
8824:
8825: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
8826: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
8827: /*}*/
8828: }
8829:
8830: fclose(ficresvbl);
8831: printf("done variance-covariance of back prevalence\n");fflush(stdout);
8832: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
8833:
8834: } /* End of varbprlim */
8835:
1.126 brouard 8836: /************** Forecasting *****not tested NB*************/
1.227 brouard 8837: /* 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 8838:
1.227 brouard 8839: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8840: /* int *popage; */
8841: /* double calagedatem, agelim, kk1, kk2; */
8842: /* double *popeffectif,*popcount; */
8843: /* double ***p3mat,***tabpop,***tabpopprev; */
8844: /* /\* double ***mobaverage; *\/ */
8845: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8846:
1.227 brouard 8847: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8848: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8849: /* agelim=AGESUP; */
8850: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8851:
1.227 brouard 8852: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8853:
8854:
1.227 brouard 8855: /* strcpy(filerespop,"POP_"); */
8856: /* strcat(filerespop,fileresu); */
8857: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8858: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8859: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8860: /* } */
8861: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8862: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8863:
1.227 brouard 8864: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8865:
1.227 brouard 8866: /* /\* if (mobilav!=0) { *\/ */
8867: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8868: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8869: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8870: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8871: /* /\* } *\/ */
8872: /* /\* } *\/ */
1.126 brouard 8873:
1.227 brouard 8874: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8875: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8876:
1.227 brouard 8877: /* agelim=AGESUP; */
1.126 brouard 8878:
1.227 brouard 8879: /* hstepm=1; */
8880: /* hstepm=hstepm/stepm; */
1.218 brouard 8881:
1.227 brouard 8882: /* if (popforecast==1) { */
8883: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8884: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8885: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8886: /* } */
8887: /* popage=ivector(0,AGESUP); */
8888: /* popeffectif=vector(0,AGESUP); */
8889: /* popcount=vector(0,AGESUP); */
1.126 brouard 8890:
1.227 brouard 8891: /* i=1; */
8892: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8893:
1.227 brouard 8894: /* imx=i; */
8895: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8896: /* } */
1.218 brouard 8897:
1.227 brouard 8898: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8899: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8900: /* k=k+1; */
8901: /* fprintf(ficrespop,"\n#******"); */
8902: /* for(j=1;j<=cptcoveff;j++) { */
8903: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8904: /* } */
8905: /* fprintf(ficrespop,"******\n"); */
8906: /* fprintf(ficrespop,"# Age"); */
8907: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8908: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8909:
1.227 brouard 8910: /* for (cpt=0; cpt<=0;cpt++) { */
8911: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8912:
1.227 brouard 8913: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8914: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8915: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8916:
1.227 brouard 8917: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8918: /* oldm=oldms;savm=savms; */
8919: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8920:
1.227 brouard 8921: /* for (h=0; h<=nhstepm; h++){ */
8922: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8923: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8924: /* } */
8925: /* for(j=1; j<=nlstate+ndeath;j++) { */
8926: /* kk1=0.;kk2=0; */
8927: /* for(i=1; i<=nlstate;i++) { */
8928: /* if (mobilav==1) */
8929: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8930: /* else { */
8931: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8932: /* } */
8933: /* } */
8934: /* if (h==(int)(calagedatem+12*cpt)){ */
8935: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8936: /* /\*fprintf(ficrespop," %.3f", kk1); */
8937: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8938: /* } */
8939: /* } */
8940: /* for(i=1; i<=nlstate;i++){ */
8941: /* kk1=0.; */
8942: /* for(j=1; j<=nlstate;j++){ */
8943: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8944: /* } */
8945: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8946: /* } */
1.218 brouard 8947:
1.227 brouard 8948: /* if (h==(int)(calagedatem+12*cpt)) */
8949: /* for(j=1; j<=nlstate;j++) */
8950: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8951: /* } */
8952: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8953: /* } */
8954: /* } */
1.218 brouard 8955:
1.227 brouard 8956: /* /\******\/ */
1.218 brouard 8957:
1.227 brouard 8958: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8959: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8960: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8961: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8962: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8963:
1.227 brouard 8964: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8965: /* oldm=oldms;savm=savms; */
8966: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8967: /* for (h=0; h<=nhstepm; h++){ */
8968: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8969: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8970: /* } */
8971: /* for(j=1; j<=nlstate+ndeath;j++) { */
8972: /* kk1=0.;kk2=0; */
8973: /* for(i=1; i<=nlstate;i++) { */
8974: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8975: /* } */
8976: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8977: /* } */
8978: /* } */
8979: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8980: /* } */
8981: /* } */
8982: /* } */
8983: /* } */
1.218 brouard 8984:
1.227 brouard 8985: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8986:
1.227 brouard 8987: /* if (popforecast==1) { */
8988: /* free_ivector(popage,0,AGESUP); */
8989: /* free_vector(popeffectif,0,AGESUP); */
8990: /* free_vector(popcount,0,AGESUP); */
8991: /* } */
8992: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8993: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8994: /* fclose(ficrespop); */
8995: /* } /\* End of popforecast *\/ */
1.218 brouard 8996:
1.126 brouard 8997: int fileappend(FILE *fichier, char *optionfich)
8998: {
8999: if((fichier=fopen(optionfich,"a"))==NULL) {
9000: printf("Problem with file: %s\n", optionfich);
9001: fprintf(ficlog,"Problem with file: %s\n", optionfich);
9002: return (0);
9003: }
9004: fflush(fichier);
9005: return (1);
9006: }
9007:
9008:
9009: /**************** function prwizard **********************/
9010: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
9011: {
9012:
9013: /* Wizard to print covariance matrix template */
9014:
1.164 brouard 9015: char ca[32], cb[32];
9016: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 9017: int numlinepar;
9018:
9019: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9020: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
9021: for(i=1; i <=nlstate; i++){
9022: jj=0;
9023: for(j=1; j <=nlstate+ndeath; j++){
9024: if(j==i) continue;
9025: jj++;
9026: /*ca[0]= k+'a'-1;ca[1]='\0';*/
9027: printf("%1d%1d",i,j);
9028: fprintf(ficparo,"%1d%1d",i,j);
9029: for(k=1; k<=ncovmodel;k++){
9030: /* printf(" %lf",param[i][j][k]); */
9031: /* fprintf(ficparo," %lf",param[i][j][k]); */
9032: printf(" 0.");
9033: fprintf(ficparo," 0.");
9034: }
9035: printf("\n");
9036: fprintf(ficparo,"\n");
9037: }
9038: }
9039: printf("# Scales (for hessian or gradient estimation)\n");
9040: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
9041: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
9042: for(i=1; i <=nlstate; i++){
9043: jj=0;
9044: for(j=1; j <=nlstate+ndeath; j++){
9045: if(j==i) continue;
9046: jj++;
9047: fprintf(ficparo,"%1d%1d",i,j);
9048: printf("%1d%1d",i,j);
9049: fflush(stdout);
9050: for(k=1; k<=ncovmodel;k++){
9051: /* printf(" %le",delti3[i][j][k]); */
9052: /* fprintf(ficparo," %le",delti3[i][j][k]); */
9053: printf(" 0.");
9054: fprintf(ficparo," 0.");
9055: }
9056: numlinepar++;
9057: printf("\n");
9058: fprintf(ficparo,"\n");
9059: }
9060: }
9061: printf("# Covariance matrix\n");
9062: /* # 121 Var(a12)\n\ */
9063: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9064: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
9065: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
9066: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
9067: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
9068: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
9069: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9070: fflush(stdout);
9071: fprintf(ficparo,"# Covariance matrix\n");
9072: /* # 121 Var(a12)\n\ */
9073: /* # 122 Cov(b12,a12) Var(b12)\n\ */
9074: /* # ...\n\ */
9075: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
9076:
9077: for(itimes=1;itimes<=2;itimes++){
9078: jj=0;
9079: for(i=1; i <=nlstate; i++){
9080: for(j=1; j <=nlstate+ndeath; j++){
9081: if(j==i) continue;
9082: for(k=1; k<=ncovmodel;k++){
9083: jj++;
9084: ca[0]= k+'a'-1;ca[1]='\0';
9085: if(itimes==1){
9086: printf("#%1d%1d%d",i,j,k);
9087: fprintf(ficparo,"#%1d%1d%d",i,j,k);
9088: }else{
9089: printf("%1d%1d%d",i,j,k);
9090: fprintf(ficparo,"%1d%1d%d",i,j,k);
9091: /* printf(" %.5le",matcov[i][j]); */
9092: }
9093: ll=0;
9094: for(li=1;li <=nlstate; li++){
9095: for(lj=1;lj <=nlstate+ndeath; lj++){
9096: if(lj==li) continue;
9097: for(lk=1;lk<=ncovmodel;lk++){
9098: ll++;
9099: if(ll<=jj){
9100: cb[0]= lk +'a'-1;cb[1]='\0';
9101: if(ll<jj){
9102: if(itimes==1){
9103: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9104: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
9105: }else{
9106: printf(" 0.");
9107: fprintf(ficparo," 0.");
9108: }
9109: }else{
9110: if(itimes==1){
9111: printf(" Var(%s%1d%1d)",ca,i,j);
9112: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
9113: }else{
9114: printf(" 0.");
9115: fprintf(ficparo," 0.");
9116: }
9117: }
9118: }
9119: } /* end lk */
9120: } /* end lj */
9121: } /* end li */
9122: printf("\n");
9123: fprintf(ficparo,"\n");
9124: numlinepar++;
9125: } /* end k*/
9126: } /*end j */
9127: } /* end i */
9128: } /* end itimes */
9129:
9130: } /* end of prwizard */
9131: /******************* Gompertz Likelihood ******************************/
9132: double gompertz(double x[])
9133: {
1.302 brouard 9134: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 9135: int i,n=0; /* n is the size of the sample */
9136:
1.220 brouard 9137: for (i=1;i<=imx ; i++) {
1.126 brouard 9138: sump=sump+weight[i];
9139: /* sump=sump+1;*/
9140: num=num+1;
9141: }
1.302 brouard 9142: L=0.0;
9143: /* agegomp=AGEGOMP; */
1.126 brouard 9144: /* for (i=0; i<=imx; i++)
9145: 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]);*/
9146:
1.302 brouard 9147: for (i=1;i<=imx ; i++) {
9148: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
9149: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
9150: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
9151: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
9152: * +
9153: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
9154: */
9155: if (wav[i] > 1 || agedc[i] < AGESUP) {
9156: if (cens[i] == 1){
9157: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9158: } else if (cens[i] == 0){
1.126 brouard 9159: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 9160: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
9161: } else
9162: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 9163: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 9164: L=L+A*weight[i];
1.126 brouard 9165: /* 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 9166: }
9167: }
1.126 brouard 9168:
1.302 brouard 9169: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 9170:
9171: return -2*L*num/sump;
9172: }
9173:
1.136 brouard 9174: #ifdef GSL
9175: /******************* Gompertz_f Likelihood ******************************/
9176: double gompertz_f(const gsl_vector *v, void *params)
9177: {
1.302 brouard 9178: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 9179: double *x= (double *) v->data;
9180: int i,n=0; /* n is the size of the sample */
9181:
9182: for (i=0;i<=imx-1 ; i++) {
9183: sump=sump+weight[i];
9184: /* sump=sump+1;*/
9185: num=num+1;
9186: }
9187:
9188:
9189: /* for (i=0; i<=imx; i++)
9190: 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]);*/
9191: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9192: for (i=1;i<=imx ; i++)
9193: {
9194: if (cens[i] == 1 && wav[i]>1)
9195: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9196:
9197: if (cens[i] == 0 && wav[i]>1)
9198: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9199: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9200:
9201: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9202: if (wav[i] > 1 ) { /* ??? */
9203: LL=LL+A*weight[i];
9204: /* 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]);*/
9205: }
9206: }
9207:
9208: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9209: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9210:
9211: return -2*LL*num/sump;
9212: }
9213: #endif
9214:
1.126 brouard 9215: /******************* Printing html file ***********/
1.201 brouard 9216: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9217: int lastpass, int stepm, int weightopt, char model[],\
9218: int imx, double p[],double **matcov,double agemortsup){
9219: int i,k;
9220:
9221: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9222: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9223: for (i=1;i<=2;i++)
9224: 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 9225: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9226: fprintf(fichtm,"</ul>");
9227:
9228: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9229:
9230: 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>");
9231:
9232: for (k=agegomp;k<(agemortsup-2);k++)
9233: 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]);
9234:
9235:
9236: fflush(fichtm);
9237: }
9238:
9239: /******************* Gnuplot file **************/
1.201 brouard 9240: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9241:
9242: char dirfileres[132],optfileres[132];
1.164 brouard 9243:
1.126 brouard 9244: int ng;
9245:
9246:
9247: /*#ifdef windows */
9248: fprintf(ficgp,"cd \"%s\" \n",pathc);
9249: /*#endif */
9250:
9251:
9252: strcpy(dirfileres,optionfilefiname);
9253: strcpy(optfileres,"vpl");
1.199 brouard 9254: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9255: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9256: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9257: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9258: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9259:
9260: }
9261:
1.136 brouard 9262: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9263: {
1.126 brouard 9264:
1.136 brouard 9265: /*-------- data file ----------*/
9266: FILE *fic;
9267: char dummy[]=" ";
1.240 brouard 9268: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9269: int lstra;
1.136 brouard 9270: int linei, month, year,iout;
1.302 brouard 9271: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 9272: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9273: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9274: char *stratrunc;
1.223 brouard 9275:
1.240 brouard 9276: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9277: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9278:
1.240 brouard 9279: for(v=1; v <=ncovcol;v++){
9280: DummyV[v]=0;
9281: FixedV[v]=0;
9282: }
9283: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9284: DummyV[v]=1;
9285: FixedV[v]=0;
9286: }
9287: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9288: DummyV[v]=0;
9289: FixedV[v]=1;
9290: }
9291: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9292: DummyV[v]=1;
9293: FixedV[v]=1;
9294: }
9295: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9296: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9297: 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]);
9298: }
1.126 brouard 9299:
1.136 brouard 9300: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9301: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9302: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9303: }
1.126 brouard 9304:
1.302 brouard 9305: /* Is it a BOM UTF-8 Windows file? */
9306: /* First data line */
9307: linei=0;
9308: while(fgets(line, MAXLINE, fic)) {
9309: noffset=0;
9310: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
9311: {
9312: noffset=noffset+3;
9313: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
9314: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
9315: fflush(ficlog); return 1;
9316: }
9317: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
9318: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
9319: {
9320: noffset=noffset+2;
1.304 brouard 9321: 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);
9322: 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 9323: fflush(ficlog); return 1;
9324: }
9325: else if( line[0] == 0 && line[1] == 0)
9326: {
9327: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
9328: noffset=noffset+4;
1.304 brouard 9329: 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);
9330: 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 9331: fflush(ficlog); return 1;
9332: }
9333: } else{
9334: ;/*printf(" Not a BOM file\n");*/
9335: }
9336: /* If line starts with a # it is a comment */
9337: if (line[noffset] == '#') {
9338: linei=linei+1;
9339: break;
9340: }else{
9341: break;
9342: }
9343: }
9344: fclose(fic);
9345: if((fic=fopen(datafile,"r"))==NULL) {
9346: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9347: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
9348: }
9349: /* Not a Bom file */
9350:
1.136 brouard 9351: i=1;
9352: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9353: linei=linei+1;
9354: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9355: if(line[j] == '\t')
9356: line[j] = ' ';
9357: }
9358: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9359: ;
9360: };
9361: line[j+1]=0; /* Trims blanks at end of line */
9362: if(line[0]=='#'){
9363: fprintf(ficlog,"Comment line\n%s\n",line);
9364: printf("Comment line\n%s\n",line);
9365: continue;
9366: }
9367: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9368: strcpy(line, linetmp);
1.223 brouard 9369:
9370: /* Loops on waves */
9371: for (j=maxwav;j>=1;j--){
9372: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9373: cutv(stra, strb, line, ' ');
9374: if(strb[0]=='.') { /* Missing value */
9375: lval=-1;
9376: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9377: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9378: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9379: 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);
9380: 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);
9381: return 1;
9382: }
9383: }else{
9384: errno=0;
9385: /* what_kind_of_number(strb); */
9386: dval=strtod(strb,&endptr);
9387: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9388: /* if(strb != endptr && *endptr == '\0') */
9389: /* dval=dlval; */
9390: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9391: if( strb[0]=='\0' || (*endptr != '\0')){
9392: 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);
9393: 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);
9394: return 1;
9395: }
9396: cotqvar[j][iv][i]=dval;
9397: cotvar[j][ntv+iv][i]=dval;
9398: }
9399: strcpy(line,stra);
1.223 brouard 9400: }/* end loop ntqv */
1.225 brouard 9401:
1.223 brouard 9402: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9403: cutv(stra, strb, line, ' ');
9404: if(strb[0]=='.') { /* Missing value */
9405: lval=-1;
9406: }else{
9407: errno=0;
9408: lval=strtol(strb,&endptr,10);
9409: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9410: if( strb[0]=='\0' || (*endptr != '\0')){
9411: 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);
9412: 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);
9413: return 1;
9414: }
9415: }
9416: if(lval <-1 || lval >1){
9417: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9418: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9419: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9420: For example, for multinomial values like 1, 2 and 3,\n \
9421: build V1=0 V2=0 for the reference value (1),\n \
9422: V1=1 V2=0 for (2) \n \
1.223 brouard 9423: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9424: output of IMaCh is often meaningless.\n \
1.223 brouard 9425: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9426: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9427: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9428: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9429: For example, for multinomial values like 1, 2 and 3,\n \
9430: build V1=0 V2=0 for the reference value (1),\n \
9431: V1=1 V2=0 for (2) \n \
1.223 brouard 9432: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9433: output of IMaCh is often meaningless.\n \
1.223 brouard 9434: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 9435: return 1;
9436: }
9437: cotvar[j][iv][i]=(double)(lval);
9438: strcpy(line,stra);
1.223 brouard 9439: }/* end loop ntv */
1.225 brouard 9440:
1.223 brouard 9441: /* Statuses at wave */
1.137 brouard 9442: cutv(stra, strb, line, ' ');
1.223 brouard 9443: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9444: lval=-1;
1.136 brouard 9445: }else{
1.238 brouard 9446: errno=0;
9447: lval=strtol(strb,&endptr,10);
9448: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9449: if( strb[0]=='\0' || (*endptr != '\0')){
9450: 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);
9451: 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);
9452: return 1;
9453: }
1.136 brouard 9454: }
1.225 brouard 9455:
1.136 brouard 9456: s[j][i]=lval;
1.225 brouard 9457:
1.223 brouard 9458: /* Date of Interview */
1.136 brouard 9459: strcpy(line,stra);
9460: cutv(stra, strb,line,' ');
1.169 brouard 9461: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9462: }
1.169 brouard 9463: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9464: month=99;
9465: year=9999;
1.136 brouard 9466: }else{
1.225 brouard 9467: 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);
9468: 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);
9469: return 1;
1.136 brouard 9470: }
9471: anint[j][i]= (double) year;
1.302 brouard 9472: mint[j][i]= (double)month;
9473: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
9474: /* 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]); */
9475: /* 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]); */
9476: /* } */
1.136 brouard 9477: strcpy(line,stra);
1.223 brouard 9478: } /* End loop on waves */
1.225 brouard 9479:
1.223 brouard 9480: /* Date of death */
1.136 brouard 9481: cutv(stra, strb,line,' ');
1.169 brouard 9482: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9483: }
1.169 brouard 9484: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9485: month=99;
9486: year=9999;
9487: }else{
1.141 brouard 9488: 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 9489: 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);
9490: return 1;
1.136 brouard 9491: }
9492: andc[i]=(double) year;
9493: moisdc[i]=(double) month;
9494: strcpy(line,stra);
9495:
1.223 brouard 9496: /* Date of birth */
1.136 brouard 9497: cutv(stra, strb,line,' ');
1.169 brouard 9498: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9499: }
1.169 brouard 9500: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9501: month=99;
9502: year=9999;
9503: }else{
1.141 brouard 9504: 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);
9505: 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 9506: return 1;
1.136 brouard 9507: }
9508: if (year==9999) {
1.141 brouard 9509: 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);
9510: 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 9511: return 1;
9512:
1.136 brouard 9513: }
9514: annais[i]=(double)(year);
1.302 brouard 9515: moisnais[i]=(double)(month);
9516: for (j=1;j<=maxwav;j++){
9517: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
9518: 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]);
9519: 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]);
9520: }
9521: }
9522:
1.136 brouard 9523: strcpy(line,stra);
1.225 brouard 9524:
1.223 brouard 9525: /* Sample weight */
1.136 brouard 9526: cutv(stra, strb,line,' ');
9527: errno=0;
9528: dval=strtod(strb,&endptr);
9529: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9530: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9531: 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 9532: fflush(ficlog);
9533: return 1;
9534: }
9535: weight[i]=dval;
9536: strcpy(line,stra);
1.225 brouard 9537:
1.223 brouard 9538: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9539: cutv(stra, strb, line, ' ');
9540: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9541: lval=-1;
1.311 brouard 9542: coqvar[iv][i]=NAN;
9543: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 9544: }else{
1.225 brouard 9545: errno=0;
9546: /* what_kind_of_number(strb); */
9547: dval=strtod(strb,&endptr);
9548: /* if(strb != endptr && *endptr == '\0') */
9549: /* dval=dlval; */
9550: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9551: if( strb[0]=='\0' || (*endptr != '\0')){
9552: 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);
9553: 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);
9554: return 1;
9555: }
9556: coqvar[iv][i]=dval;
1.226 brouard 9557: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9558: }
9559: strcpy(line,stra);
9560: }/* end loop nqv */
1.136 brouard 9561:
1.223 brouard 9562: /* Covariate values */
1.136 brouard 9563: for (j=ncovcol;j>=1;j--){
9564: cutv(stra, strb,line,' ');
1.223 brouard 9565: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9566: lval=-1;
1.136 brouard 9567: }else{
1.225 brouard 9568: errno=0;
9569: lval=strtol(strb,&endptr,10);
9570: if( strb[0]=='\0' || (*endptr != '\0')){
9571: 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);
9572: 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);
9573: return 1;
9574: }
1.136 brouard 9575: }
9576: if(lval <-1 || lval >1){
1.225 brouard 9577: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9578: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9579: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9580: For example, for multinomial values like 1, 2 and 3,\n \
9581: build V1=0 V2=0 for the reference value (1),\n \
9582: V1=1 V2=0 for (2) \n \
1.136 brouard 9583: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9584: output of IMaCh is often meaningless.\n \
1.136 brouard 9585: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9586: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9587: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9588: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9589: For example, for multinomial values like 1, 2 and 3,\n \
9590: build V1=0 V2=0 for the reference value (1),\n \
9591: V1=1 V2=0 for (2) \n \
1.136 brouard 9592: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9593: output of IMaCh is often meaningless.\n \
1.136 brouard 9594: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9595: return 1;
1.136 brouard 9596: }
9597: covar[j][i]=(double)(lval);
9598: strcpy(line,stra);
9599: }
9600: lstra=strlen(stra);
1.225 brouard 9601:
1.136 brouard 9602: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9603: stratrunc = &(stra[lstra-9]);
9604: num[i]=atol(stratrunc);
9605: }
9606: else
9607: num[i]=atol(stra);
9608: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9609: 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;}*/
9610:
9611: i=i+1;
9612: } /* End loop reading data */
1.225 brouard 9613:
1.136 brouard 9614: *imax=i-1; /* Number of individuals */
9615: fclose(fic);
1.225 brouard 9616:
1.136 brouard 9617: return (0);
1.164 brouard 9618: /* endread: */
1.225 brouard 9619: printf("Exiting readdata: ");
9620: fclose(fic);
9621: return (1);
1.223 brouard 9622: }
1.126 brouard 9623:
1.234 brouard 9624: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9625: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9626: while (*p2 == ' ')
1.234 brouard 9627: p2++;
9628: /* while ((*p1++ = *p2++) !=0) */
9629: /* ; */
9630: /* do */
9631: /* while (*p2 == ' ') */
9632: /* p2++; */
9633: /* while (*p1++ == *p2++); */
9634: *stri=p2;
1.145 brouard 9635: }
9636:
1.235 brouard 9637: int decoderesult ( char resultline[], int nres)
1.230 brouard 9638: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9639: {
1.235 brouard 9640: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9641: char resultsav[MAXLINE];
1.234 brouard 9642: int resultmodel[MAXLINE];
9643: int modelresult[MAXLINE];
1.230 brouard 9644: char stra[80], strb[80], strc[80], strd[80],stre[80];
9645:
1.234 brouard 9646: removefirstspace(&resultline);
1.230 brouard 9647:
9648: if (strstr(resultline,"v") !=0){
9649: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9650: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9651: return 1;
9652: }
9653: trimbb(resultsav, resultline);
9654: if (strlen(resultsav) >1){
9655: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9656: }
1.253 brouard 9657: if(j == 0){ /* Resultline but no = */
9658: TKresult[nres]=0; /* Combination for the nresult and the model */
9659: return (0);
9660: }
1.234 brouard 9661: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.310 brouard 9662: printf("ERROR: the number of variables in the resultline, %d, differs from the number of variables used in the model line, %d.\n",j, cptcovs);
9663: 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 9664: }
9665: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9666: if(nbocc(resultsav,'=') >1){
9667: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
1.310 brouard 9668: resultsav= V4=1 V5=25.1 V3=0 stra= V5=25.1 V3=0 strb= V4=1 */
1.234 brouard 9669: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9670: }else
9671: cutl(strc,strd,resultsav,'=');
1.230 brouard 9672: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9673:
1.230 brouard 9674: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9675: Tvarsel[k]=atoi(strc);
9676: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9677: /* cptcovsel++; */
9678: if (nbocc(stra,'=') >0)
9679: strcpy(resultsav,stra); /* and analyzes it */
9680: }
1.235 brouard 9681: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9682: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9683: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9684: match=0;
1.236 brouard 9685: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9686: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9687: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9688: match=1;
9689: break;
9690: }
9691: }
9692: if(match == 0){
1.310 brouard 9693: printf("Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model);
9694: fprintf(ficlog,"Error in result line: V%d is missing in result: %s according to model=%s\n",k1, resultline, model);
9695: return 1;
1.234 brouard 9696: }
9697: }
9698: }
1.235 brouard 9699: /* Checking for missing or useless values in comparison of current model needs */
9700: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9701: match=0;
1.235 brouard 9702: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9703: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9704: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9705: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9706: ++match;
9707: }
9708: }
9709: }
9710: if(match == 0){
9711: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
1.310 brouard 9712: fprintf(ficlog,"Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9713: return 1;
1.234 brouard 9714: }else if(match > 1){
9715: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
1.310 brouard 9716: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9717: return 1;
1.234 brouard 9718: }
9719: }
1.235 brouard 9720:
1.234 brouard 9721: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9722: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9723: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9724: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9725: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9726: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9727: /* 1 0 0 0 */
9728: /* 2 1 0 0 */
9729: /* 3 0 1 0 */
9730: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9731: /* 5 0 0 1 */
9732: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9733: /* 7 0 1 1 */
9734: /* 8 1 1 1 */
1.237 brouard 9735: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9736: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9737: /* V5*age V5 known which value for nres? */
9738: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9739: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9740: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9741: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9742: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9743: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9744: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9745: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9746: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9747: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9748: k4++;;
9749: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9750: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9751: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9752: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9753: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9754: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9755: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9756: k4q++;;
9757: }
9758: }
1.234 brouard 9759:
1.235 brouard 9760: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9761: return (0);
9762: }
1.235 brouard 9763:
1.230 brouard 9764: int decodemodel( char model[], int lastobs)
9765: /**< This routine decodes the model and returns:
1.224 brouard 9766: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9767: * - nagesqr = 1 if age*age in the model, otherwise 0.
9768: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9769: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9770: * - cptcovage number of covariates with age*products =2
9771: * - cptcovs number of simple covariates
9772: * - 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
9773: * which is a new column after the 9 (ncovcol) variables.
9774: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9775: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9776: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9777: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9778: */
1.136 brouard 9779: {
1.238 brouard 9780: int i, j, k, ks, v;
1.227 brouard 9781: int j1, k1, k2, k3, k4;
1.136 brouard 9782: char modelsav[80];
1.145 brouard 9783: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9784: char *strpt;
1.136 brouard 9785:
1.145 brouard 9786: /*removespace(model);*/
1.136 brouard 9787: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9788: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9789: if (strstr(model,"AGE") !=0){
1.192 brouard 9790: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9791: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9792: return 1;
9793: }
1.141 brouard 9794: if (strstr(model,"v") !=0){
9795: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9796: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9797: return 1;
9798: }
1.187 brouard 9799: strcpy(modelsav,model);
9800: if ((strpt=strstr(model,"age*age")) !=0){
9801: printf(" strpt=%s, model=%s\n",strpt, model);
9802: if(strpt != model){
1.234 brouard 9803: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9804: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9805: corresponding column of parameters.\n",model);
1.234 brouard 9806: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9807: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9808: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9809: return 1;
1.225 brouard 9810: }
1.187 brouard 9811: nagesqr=1;
9812: if (strstr(model,"+age*age") !=0)
1.234 brouard 9813: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9814: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9815: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9816: else
1.234 brouard 9817: substrchaine(modelsav, model, "age*age");
1.187 brouard 9818: }else
9819: nagesqr=0;
9820: if (strlen(modelsav) >1){
9821: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9822: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9823: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9824: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9825: * cst, age and age*age
9826: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9827: /* including age products which are counted in cptcovage.
9828: * but the covariates which are products must be treated
9829: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9830: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9831: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9832:
9833:
1.187 brouard 9834: /* Design
9835: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9836: * < ncovcol=8 >
9837: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9838: * k= 1 2 3 4 5 6 7 8
9839: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9840: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9841: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9842: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9843: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9844: * Tage[++cptcovage]=k
9845: * if products, new covar are created after ncovcol with k1
9846: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9847: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9848: * 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
9849: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9850: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9851: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9852: * < ncovcol=8 >
9853: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9854: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9855: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9856: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9857: * p Tprod[1]@2={ 6, 5}
9858: *p Tvard[1][1]@4= {7, 8, 5, 6}
9859: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9860: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9861: *How to reorganize?
9862: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9863: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9864: * {2, 1, 4, 8, 5, 6, 3, 7}
9865: * Struct []
9866: */
1.225 brouard 9867:
1.187 brouard 9868: /* This loop fills the array Tvar from the string 'model'.*/
9869: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9870: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9871: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9872: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9873: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9874: /* k=1 Tvar[1]=2 (from V2) */
9875: /* k=5 Tvar[5] */
9876: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9877: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9878: /* } */
1.198 brouard 9879: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9880: /*
9881: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9882: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9883: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9884: }
1.187 brouard 9885: cptcovage=0;
9886: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9887: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9888: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9889: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9890: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9891: /*scanf("%d",i);*/
9892: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9893: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9894: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9895: /* covar is not filled and then is empty */
9896: cptcovprod--;
9897: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9898: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9899: Typevar[k]=1; /* 1 for age product */
9900: cptcovage++; /* Sums the number of covariates which include age as a product */
9901: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9902: /*printf("stre=%s ", stre);*/
9903: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9904: cptcovprod--;
9905: cutl(stre,strb,strc,'V');
9906: Tvar[k]=atoi(stre);
9907: Typevar[k]=1; /* 1 for age product */
9908: cptcovage++;
9909: Tage[cptcovage]=k;
9910: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9911: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9912: cptcovn++;
9913: cptcovprodnoage++;k1++;
9914: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9915: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9916: because this model-covariate is a construction we invent a new column
9917: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9918: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9919: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9920: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9921: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9922: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9923: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9924: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9925: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9926: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9927: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9928: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9929: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9930: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9931: for (i=1; i<=lastobs;i++){
9932: /* Computes the new covariate which is a product of
9933: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9934: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9935: }
9936: } /* End age is not in the model */
9937: } /* End if model includes a product */
9938: else { /* no more sum */
9939: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9940: /* scanf("%d",i);*/
9941: cutl(strd,strc,strb,'V');
9942: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9943: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9944: Tvar[k]=atoi(strd);
9945: Typevar[k]=0; /* 0 for simple covariates */
9946: }
9947: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9948: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9949: scanf("%d",i);*/
1.187 brouard 9950: } /* end of loop + on total covariates */
9951: } /* end if strlen(modelsave == 0) age*age might exist */
9952: } /* end if strlen(model == 0) */
1.136 brouard 9953:
9954: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9955: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9956:
1.136 brouard 9957: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9958: printf("cptcovprod=%d ", cptcovprod);
9959: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9960: scanf("%d ",i);*/
9961:
9962:
1.230 brouard 9963: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9964: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9965: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9966: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9967: k = 1 2 3 4 5 6 7 8 9
9968: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9969: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9970: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9971: Dummy[k] 1 0 0 0 3 1 1 2 3
9972: Tmodelind[combination of covar]=k;
1.225 brouard 9973: */
9974: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9975: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9976: /* 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 9977: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9978: printf("Model=%s\n\
9979: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9980: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9981: 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);
9982: fprintf(ficlog,"Model=%s\n\
9983: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9984: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9985: 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 9986: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9987: 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 */
9988: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9989: Fixed[k]= 0;
9990: Dummy[k]= 0;
1.225 brouard 9991: ncoveff++;
1.232 brouard 9992: ncovf++;
1.234 brouard 9993: nsd++;
9994: modell[k].maintype= FTYPE;
9995: TvarsD[nsd]=Tvar[k];
9996: TvarsDind[nsd]=k;
9997: TvarF[ncovf]=Tvar[k];
9998: TvarFind[ncovf]=k;
9999: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10000: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
10001: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
10002: Fixed[k]= 0;
10003: Dummy[k]= 0;
10004: ncoveff++;
10005: ncovf++;
10006: modell[k].maintype= FTYPE;
10007: TvarF[ncovf]=Tvar[k];
10008: TvarFind[ncovf]=k;
1.230 brouard 10009: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 10010: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 10011: }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 10012: Fixed[k]= 0;
10013: Dummy[k]= 1;
1.230 brouard 10014: nqfveff++;
1.234 brouard 10015: modell[k].maintype= FTYPE;
10016: modell[k].subtype= FQ;
10017: nsq++;
10018: TvarsQ[nsq]=Tvar[k];
10019: TvarsQind[nsq]=k;
1.232 brouard 10020: ncovf++;
1.234 brouard 10021: TvarF[ncovf]=Tvar[k];
10022: TvarFind[ncovf]=k;
1.231 brouard 10023: 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 10024: 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 10025: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 10026: Fixed[k]= 1;
10027: Dummy[k]= 0;
1.225 brouard 10028: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 10029: modell[k].maintype= VTYPE;
10030: modell[k].subtype= VD;
10031: nsd++;
10032: TvarsD[nsd]=Tvar[k];
10033: TvarsDind[nsd]=k;
10034: ncovv++; /* Only simple time varying variables */
10035: TvarV[ncovv]=Tvar[k];
1.242 brouard 10036: 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 10037: 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 */
10038: 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 10039: 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);
10040: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 10041: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 10042: Fixed[k]= 1;
10043: Dummy[k]= 1;
10044: nqtveff++;
10045: modell[k].maintype= VTYPE;
10046: modell[k].subtype= VQ;
10047: ncovv++; /* Only simple time varying variables */
10048: nsq++;
10049: TvarsQ[nsq]=Tvar[k];
10050: TvarsQind[nsq]=k;
10051: TvarV[ncovv]=Tvar[k];
1.242 brouard 10052: 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 10053: 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 */
10054: 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 10055: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
10056: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
10057: 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 10058: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 10059: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 10060: ncova++;
10061: TvarA[ncova]=Tvar[k];
10062: TvarAind[ncova]=k;
1.231 brouard 10063: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 10064: Fixed[k]= 2;
10065: Dummy[k]= 2;
10066: modell[k].maintype= ATYPE;
10067: modell[k].subtype= APFD;
10068: /* ncoveff++; */
1.227 brouard 10069: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 10070: Fixed[k]= 2;
10071: Dummy[k]= 3;
10072: modell[k].maintype= ATYPE;
10073: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
10074: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 10075: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 10076: Fixed[k]= 3;
10077: Dummy[k]= 2;
10078: modell[k].maintype= ATYPE;
10079: modell[k].subtype= APVD; /* Product age * varying dummy */
10080: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 10081: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10082: Fixed[k]= 3;
10083: Dummy[k]= 3;
10084: modell[k].maintype= ATYPE;
10085: modell[k].subtype= APVQ; /* Product age * varying quantitative */
10086: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 10087: }
10088: }else if (Typevar[k] == 2) { /* product without age */
10089: k1=Tposprod[k];
10090: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 10091: if(Tvard[k1][2] <=ncovcol){
10092: Fixed[k]= 1;
10093: Dummy[k]= 0;
10094: modell[k].maintype= FTYPE;
10095: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
10096: ncovf++; /* Fixed variables without age */
10097: TvarF[ncovf]=Tvar[k];
10098: TvarFind[ncovf]=k;
10099: }else if(Tvard[k1][2] <=ncovcol+nqv){
10100: Fixed[k]= 0; /* or 2 ?*/
10101: Dummy[k]= 1;
10102: modell[k].maintype= FTYPE;
10103: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
10104: ncovf++; /* Varying variables without age */
10105: TvarF[ncovf]=Tvar[k];
10106: TvarFind[ncovf]=k;
10107: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10108: Fixed[k]= 1;
10109: Dummy[k]= 0;
10110: modell[k].maintype= VTYPE;
10111: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
10112: ncovv++; /* Varying variables without age */
10113: TvarV[ncovv]=Tvar[k];
10114: TvarVind[ncovv]=k;
10115: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10116: Fixed[k]= 1;
10117: Dummy[k]= 1;
10118: modell[k].maintype= VTYPE;
10119: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
10120: ncovv++; /* Varying variables without age */
10121: TvarV[ncovv]=Tvar[k];
10122: TvarVind[ncovv]=k;
10123: }
1.227 brouard 10124: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 10125: if(Tvard[k1][2] <=ncovcol){
10126: Fixed[k]= 0; /* or 2 ?*/
10127: Dummy[k]= 1;
10128: modell[k].maintype= FTYPE;
10129: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
10130: ncovf++; /* Fixed variables without age */
10131: TvarF[ncovf]=Tvar[k];
10132: TvarFind[ncovf]=k;
10133: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10134: Fixed[k]= 1;
10135: Dummy[k]= 1;
10136: modell[k].maintype= VTYPE;
10137: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
10138: ncovv++; /* Varying variables without age */
10139: TvarV[ncovv]=Tvar[k];
10140: TvarVind[ncovv]=k;
10141: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10142: Fixed[k]= 1;
10143: Dummy[k]= 1;
10144: modell[k].maintype= VTYPE;
10145: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
10146: ncovv++; /* Varying variables without age */
10147: TvarV[ncovv]=Tvar[k];
10148: TvarVind[ncovv]=k;
10149: ncovv++; /* Varying variables without age */
10150: TvarV[ncovv]=Tvar[k];
10151: TvarVind[ncovv]=k;
10152: }
1.227 brouard 10153: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 10154: if(Tvard[k1][2] <=ncovcol){
10155: Fixed[k]= 1;
10156: Dummy[k]= 1;
10157: modell[k].maintype= VTYPE;
10158: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
10159: ncovv++; /* Varying variables without age */
10160: TvarV[ncovv]=Tvar[k];
10161: TvarVind[ncovv]=k;
10162: }else if(Tvard[k1][2] <=ncovcol+nqv){
10163: Fixed[k]= 1;
10164: Dummy[k]= 1;
10165: modell[k].maintype= VTYPE;
10166: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
10167: ncovv++; /* Varying variables without age */
10168: TvarV[ncovv]=Tvar[k];
10169: TvarVind[ncovv]=k;
10170: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10171: Fixed[k]= 1;
10172: Dummy[k]= 0;
10173: modell[k].maintype= VTYPE;
10174: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
10175: ncovv++; /* Varying variables without age */
10176: TvarV[ncovv]=Tvar[k];
10177: TvarVind[ncovv]=k;
10178: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10179: Fixed[k]= 1;
10180: Dummy[k]= 1;
10181: modell[k].maintype= VTYPE;
10182: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
10183: ncovv++; /* Varying variables without age */
10184: TvarV[ncovv]=Tvar[k];
10185: TvarVind[ncovv]=k;
10186: }
1.227 brouard 10187: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 10188: if(Tvard[k1][2] <=ncovcol){
10189: Fixed[k]= 1;
10190: Dummy[k]= 1;
10191: modell[k].maintype= VTYPE;
10192: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
10193: ncovv++; /* Varying variables without age */
10194: TvarV[ncovv]=Tvar[k];
10195: TvarVind[ncovv]=k;
10196: }else if(Tvard[k1][2] <=ncovcol+nqv){
10197: Fixed[k]= 1;
10198: Dummy[k]= 1;
10199: modell[k].maintype= VTYPE;
10200: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
10201: ncovv++; /* Varying variables without age */
10202: TvarV[ncovv]=Tvar[k];
10203: TvarVind[ncovv]=k;
10204: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
10205: Fixed[k]= 1;
10206: Dummy[k]= 1;
10207: modell[k].maintype= VTYPE;
10208: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
10209: ncovv++; /* Varying variables without age */
10210: TvarV[ncovv]=Tvar[k];
10211: TvarVind[ncovv]=k;
10212: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
10213: Fixed[k]= 1;
10214: Dummy[k]= 1;
10215: modell[k].maintype= VTYPE;
10216: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
10217: ncovv++; /* Varying variables without age */
10218: TvarV[ncovv]=Tvar[k];
10219: TvarVind[ncovv]=k;
10220: }
1.227 brouard 10221: }else{
1.240 brouard 10222: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10223: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10224: } /*end k1*/
1.225 brouard 10225: }else{
1.226 brouard 10226: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10227: 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 10228: }
1.227 brouard 10229: 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 10230: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10231: 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]);
10232: }
10233: /* Searching for doublons in the model */
10234: for(k1=1; k1<= cptcovt;k1++){
10235: for(k2=1; k2 <k1;k2++){
1.285 brouard 10236: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10237: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10238: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10239: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10240: 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]);
10241: 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 10242: return(1);
10243: }
10244: }else if (Typevar[k1] ==2){
10245: k3=Tposprod[k1];
10246: k4=Tposprod[k2];
10247: 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])) ){
10248: 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]]);
10249: 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);
10250: return(1);
10251: }
10252: }
1.227 brouard 10253: }
10254: }
1.225 brouard 10255: }
10256: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10257: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10258: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10259: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10260: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10261: /*endread:*/
1.225 brouard 10262: printf("Exiting decodemodel: ");
10263: return (1);
1.136 brouard 10264: }
10265:
1.169 brouard 10266: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10267: {/* Check ages at death */
1.136 brouard 10268: int i, m;
1.218 brouard 10269: int firstone=0;
10270:
1.136 brouard 10271: for (i=1; i<=imx; i++) {
10272: for(m=2; (m<= maxwav); m++) {
10273: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10274: anint[m][i]=9999;
1.216 brouard 10275: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10276: s[m][i]=-1;
1.136 brouard 10277: }
10278: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10279: *nberr = *nberr + 1;
1.218 brouard 10280: if(firstone == 0){
10281: firstone=1;
1.260 brouard 10282: 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 10283: }
1.262 brouard 10284: 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 10285: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10286: }
10287: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10288: (*nberr)++;
1.259 brouard 10289: 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 10290: 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 10291: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10292: }
10293: }
10294: }
10295:
10296: for (i=1; i<=imx; i++) {
10297: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10298: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10299: 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 10300: if (s[m][i] >= nlstate+1) {
1.169 brouard 10301: if(agedc[i]>0){
10302: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10303: agev[m][i]=agedc[i];
1.214 brouard 10304: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10305: }else {
1.136 brouard 10306: if ((int)andc[i]!=9999){
10307: nbwarn++;
10308: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10309: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10310: agev[m][i]=-1;
10311: }
10312: }
1.169 brouard 10313: } /* agedc > 0 */
1.214 brouard 10314: } /* end if */
1.136 brouard 10315: else if(s[m][i] !=9){ /* Standard case, age in fractional
10316: years but with the precision of a month */
10317: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10318: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10319: agev[m][i]=1;
10320: else if(agev[m][i] < *agemin){
10321: *agemin=agev[m][i];
10322: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10323: }
10324: else if(agev[m][i] >*agemax){
10325: *agemax=agev[m][i];
1.156 brouard 10326: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10327: }
10328: /*agev[m][i]=anint[m][i]-annais[i];*/
10329: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10330: } /* en if 9*/
1.136 brouard 10331: else { /* =9 */
1.214 brouard 10332: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10333: agev[m][i]=1;
10334: s[m][i]=-1;
10335: }
10336: }
1.214 brouard 10337: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10338: agev[m][i]=1;
1.214 brouard 10339: else{
10340: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10341: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10342: agev[m][i]=0;
10343: }
10344: } /* End for lastpass */
10345: }
1.136 brouard 10346:
10347: for (i=1; i<=imx; i++) {
10348: for(m=firstpass; (m<=lastpass); m++){
10349: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10350: (*nberr)++;
1.136 brouard 10351: 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);
10352: 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);
10353: return 1;
10354: }
10355: }
10356: }
10357:
10358: /*for (i=1; i<=imx; i++){
10359: for (m=firstpass; (m<lastpass); m++){
10360: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10361: }
10362:
10363: }*/
10364:
10365:
1.139 brouard 10366: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10367: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10368:
10369: return (0);
1.164 brouard 10370: /* endread:*/
1.136 brouard 10371: printf("Exiting calandcheckages: ");
10372: return (1);
10373: }
10374:
1.172 brouard 10375: #if defined(_MSC_VER)
10376: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10377: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10378: //#include "stdafx.h"
10379: //#include <stdio.h>
10380: //#include <tchar.h>
10381: //#include <windows.h>
10382: //#include <iostream>
10383: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10384:
10385: LPFN_ISWOW64PROCESS fnIsWow64Process;
10386:
10387: BOOL IsWow64()
10388: {
10389: BOOL bIsWow64 = FALSE;
10390:
10391: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10392: // (HANDLE, PBOOL);
10393:
10394: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10395:
10396: HMODULE module = GetModuleHandle(_T("kernel32"));
10397: const char funcName[] = "IsWow64Process";
10398: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10399: GetProcAddress(module, funcName);
10400:
10401: if (NULL != fnIsWow64Process)
10402: {
10403: if (!fnIsWow64Process(GetCurrentProcess(),
10404: &bIsWow64))
10405: //throw std::exception("Unknown error");
10406: printf("Unknown error\n");
10407: }
10408: return bIsWow64 != FALSE;
10409: }
10410: #endif
1.177 brouard 10411:
1.191 brouard 10412: void syscompilerinfo(int logged)
1.292 brouard 10413: {
10414: #include <stdint.h>
10415:
10416: /* #include "syscompilerinfo.h"*/
1.185 brouard 10417: /* command line Intel compiler 32bit windows, XP compatible:*/
10418: /* /GS /W3 /Gy
10419: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10420: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10421: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10422: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10423: */
10424: /* 64 bits */
1.185 brouard 10425: /*
10426: /GS /W3 /Gy
10427: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10428: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10429: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10430: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10431: /* Optimization are useless and O3 is slower than O2 */
10432: /*
10433: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10434: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10435: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10436: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10437: */
1.186 brouard 10438: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10439: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10440: /PDB:"visual studio
10441: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10442: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10443: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10444: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10445: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10446: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10447: uiAccess='false'"
10448: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10449: /NOLOGO /TLBID:1
10450: */
1.292 brouard 10451:
10452:
1.177 brouard 10453: #if defined __INTEL_COMPILER
1.178 brouard 10454: #if defined(__GNUC__)
10455: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10456: #endif
1.177 brouard 10457: #elif defined(__GNUC__)
1.179 brouard 10458: #ifndef __APPLE__
1.174 brouard 10459: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10460: #endif
1.177 brouard 10461: struct utsname sysInfo;
1.178 brouard 10462: int cross = CROSS;
10463: if (cross){
10464: printf("Cross-");
1.191 brouard 10465: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10466: }
1.174 brouard 10467: #endif
10468:
1.191 brouard 10469: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10470: #if defined(__clang__)
1.191 brouard 10471: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10472: #endif
10473: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10474: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10475: #endif
10476: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10477: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10478: #endif
10479: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10480: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10481: #endif
10482: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10483: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10484: #endif
10485: #if defined(_MSC_VER)
1.191 brouard 10486: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10487: #endif
10488: #if defined(__PGI)
1.191 brouard 10489: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10490: #endif
10491: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10492: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10493: #endif
1.191 brouard 10494: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10495:
1.167 brouard 10496: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10497: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10498: // Windows (x64 and x86)
1.191 brouard 10499: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10500: #elif __unix__ // all unices, not all compilers
10501: // Unix
1.191 brouard 10502: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10503: #elif __linux__
10504: // linux
1.191 brouard 10505: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10506: #elif __APPLE__
1.174 brouard 10507: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10508: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10509: #endif
10510:
10511: /* __MINGW32__ */
10512: /* __CYGWIN__ */
10513: /* __MINGW64__ */
10514: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10515: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10516: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10517: /* _WIN64 // Defined for applications for Win64. */
10518: /* _M_X64 // Defined for compilations that target x64 processors. */
10519: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10520:
1.167 brouard 10521: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10522: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10523: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10524: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10525: #else
1.191 brouard 10526: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10527: #endif
10528:
1.169 brouard 10529: #if defined(__GNUC__)
10530: # if defined(__GNUC_PATCHLEVEL__)
10531: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10532: + __GNUC_MINOR__ * 100 \
10533: + __GNUC_PATCHLEVEL__)
10534: # else
10535: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10536: + __GNUC_MINOR__ * 100)
10537: # endif
1.174 brouard 10538: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10539: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10540:
10541: if (uname(&sysInfo) != -1) {
10542: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10543: 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 10544: }
10545: else
10546: perror("uname() error");
1.179 brouard 10547: //#ifndef __INTEL_COMPILER
10548: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10549: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10550: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10551: #endif
1.169 brouard 10552: #endif
1.172 brouard 10553:
1.286 brouard 10554: // void main ()
1.172 brouard 10555: // {
1.169 brouard 10556: #if defined(_MSC_VER)
1.174 brouard 10557: if (IsWow64()){
1.191 brouard 10558: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10559: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10560: }
10561: else{
1.191 brouard 10562: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10563: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10564: }
1.172 brouard 10565: // printf("\nPress Enter to continue...");
10566: // getchar();
10567: // }
10568:
1.169 brouard 10569: #endif
10570:
1.167 brouard 10571:
1.219 brouard 10572: }
1.136 brouard 10573:
1.219 brouard 10574: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 10575: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.235 brouard 10576: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10577: /* double ftolpl = 1.e-10; */
1.180 brouard 10578: double age, agebase, agelim;
1.203 brouard 10579: double tot;
1.180 brouard 10580:
1.202 brouard 10581: strcpy(filerespl,"PL_");
10582: strcat(filerespl,fileresu);
10583: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 10584: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10585: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 10586: }
1.288 brouard 10587: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
10588: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10589: pstamp(ficrespl);
1.288 brouard 10590: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10591: fprintf(ficrespl,"#Age ");
10592: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10593: fprintf(ficrespl,"\n");
1.180 brouard 10594:
1.219 brouard 10595: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10596:
1.219 brouard 10597: agebase=ageminpar;
10598: agelim=agemaxpar;
1.180 brouard 10599:
1.227 brouard 10600: /* i1=pow(2,ncoveff); */
1.234 brouard 10601: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10602: if (cptcovn < 1){i1=1;}
1.180 brouard 10603:
1.238 brouard 10604: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10605: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10606: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10607: continue;
1.235 brouard 10608:
1.238 brouard 10609: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10610: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10611: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10612: /* k=k+1; */
10613: /* to clean */
10614: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10615: fprintf(ficrespl,"#******");
10616: printf("#******");
10617: fprintf(ficlog,"#******");
10618: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10619: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10620: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10621: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10622: }
10623: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10624: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10625: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10626: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10627: }
10628: fprintf(ficrespl,"******\n");
10629: printf("******\n");
10630: fprintf(ficlog,"******\n");
10631: if(invalidvarcomb[k]){
10632: printf("\nCombination (%d) ignored because no case \n",k);
10633: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10634: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10635: continue;
10636: }
1.219 brouard 10637:
1.238 brouard 10638: fprintf(ficrespl,"#Age ");
10639: for(j=1;j<=cptcoveff;j++) {
10640: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10641: }
10642: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10643: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10644:
1.238 brouard 10645: for (age=agebase; age<=agelim; age++){
10646: /* for (age=agebase; age<=agebase; age++){ */
10647: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10648: fprintf(ficrespl,"%.0f ",age );
10649: for(j=1;j<=cptcoveff;j++)
10650: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10651: tot=0.;
10652: for(i=1; i<=nlstate;i++){
10653: tot += prlim[i][i];
10654: fprintf(ficrespl," %.5f", prlim[i][i]);
10655: }
10656: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10657: } /* Age */
10658: /* was end of cptcod */
10659: } /* cptcov */
10660: } /* nres */
1.219 brouard 10661: return 0;
1.180 brouard 10662: }
10663:
1.218 brouard 10664: 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 10665: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 10666:
10667: /* Computes the back prevalence limit for any combination of covariate values
10668: * at any age between ageminpar and agemaxpar
10669: */
1.235 brouard 10670: int i, j, k, i1, nres=0 ;
1.217 brouard 10671: /* double ftolpl = 1.e-10; */
10672: double age, agebase, agelim;
10673: double tot;
1.218 brouard 10674: /* double ***mobaverage; */
10675: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10676:
10677: strcpy(fileresplb,"PLB_");
10678: strcat(fileresplb,fileresu);
10679: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 10680: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
10681: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 10682: }
1.288 brouard 10683: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
10684: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 10685: pstamp(ficresplb);
1.288 brouard 10686: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 10687: fprintf(ficresplb,"#Age ");
10688: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10689: fprintf(ficresplb,"\n");
10690:
1.218 brouard 10691:
10692: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10693:
10694: agebase=ageminpar;
10695: agelim=agemaxpar;
10696:
10697:
1.227 brouard 10698: i1=pow(2,cptcoveff);
1.218 brouard 10699: if (cptcovn < 1){i1=1;}
1.227 brouard 10700:
1.238 brouard 10701: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10702: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10703: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10704: continue;
10705: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10706: fprintf(ficresplb,"#******");
10707: printf("#******");
10708: fprintf(ficlog,"#******");
10709: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10710: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10711: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10712: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10713: }
10714: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10715: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10716: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10717: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10718: }
10719: fprintf(ficresplb,"******\n");
10720: printf("******\n");
10721: fprintf(ficlog,"******\n");
10722: if(invalidvarcomb[k]){
10723: printf("\nCombination (%d) ignored because no cases \n",k);
10724: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10725: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10726: continue;
10727: }
1.218 brouard 10728:
1.238 brouard 10729: fprintf(ficresplb,"#Age ");
10730: for(j=1;j<=cptcoveff;j++) {
10731: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10732: }
10733: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10734: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10735:
10736:
1.238 brouard 10737: for (age=agebase; age<=agelim; age++){
10738: /* for (age=agebase; age<=agebase; age++){ */
10739: if(mobilavproj > 0){
10740: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10741: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10742: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10743: }else if (mobilavproj == 0){
10744: 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);
10745: 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);
10746: exit(1);
10747: }else{
10748: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10749: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10750: /* printf("TOTOT\n"); */
10751: /* exit(1); */
1.238 brouard 10752: }
10753: fprintf(ficresplb,"%.0f ",age );
10754: for(j=1;j<=cptcoveff;j++)
10755: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10756: tot=0.;
10757: for(i=1; i<=nlstate;i++){
10758: tot += bprlim[i][i];
10759: fprintf(ficresplb," %.5f", bprlim[i][i]);
10760: }
10761: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10762: } /* Age */
10763: /* was end of cptcod */
1.255 brouard 10764: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10765: } /* end of any combination */
10766: } /* end of nres */
1.218 brouard 10767: /* hBijx(p, bage, fage); */
10768: /* fclose(ficrespijb); */
10769:
10770: return 0;
1.217 brouard 10771: }
1.218 brouard 10772:
1.180 brouard 10773: int hPijx(double *p, int bage, int fage){
10774: /*------------- h Pij x at various ages ------------*/
10775:
10776: int stepsize;
10777: int agelim;
10778: int hstepm;
10779: int nhstepm;
1.235 brouard 10780: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10781:
10782: double agedeb;
10783: double ***p3mat;
10784:
1.201 brouard 10785: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10786: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10787: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10788: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10789: }
10790: printf("Computing pij: result on file '%s' \n", filerespij);
10791: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10792:
10793: stepsize=(int) (stepm+YEARM-1)/YEARM;
10794: /*if (stepm<=24) stepsize=2;*/
10795:
10796: agelim=AGESUP;
10797: hstepm=stepsize*YEARM; /* Every year of age */
10798: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10799:
1.180 brouard 10800: /* hstepm=1; aff par mois*/
10801: pstamp(ficrespij);
10802: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10803: i1= pow(2,cptcoveff);
1.218 brouard 10804: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10805: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10806: /* k=k+1; */
1.235 brouard 10807: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10808: for(k=1; k<=i1;k++){
1.253 brouard 10809: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10810: continue;
1.183 brouard 10811: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10812: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10813: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10814: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10815: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10816: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10817: }
1.183 brouard 10818: fprintf(ficrespij,"******\n");
10819:
10820: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10821: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10822: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10823:
10824: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10825:
1.183 brouard 10826: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10827: oldm=oldms;savm=savms;
1.235 brouard 10828: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10829: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10830: for(i=1; i<=nlstate;i++)
10831: for(j=1; j<=nlstate+ndeath;j++)
10832: fprintf(ficrespij," %1d-%1d",i,j);
10833: fprintf(ficrespij,"\n");
10834: for (h=0; h<=nhstepm; h++){
10835: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10836: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10837: for(i=1; i<=nlstate;i++)
10838: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10839: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10840: fprintf(ficrespij,"\n");
10841: }
1.183 brouard 10842: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10843: fprintf(ficrespij,"\n");
10844: }
1.180 brouard 10845: /*}*/
10846: }
1.218 brouard 10847: return 0;
1.180 brouard 10848: }
1.218 brouard 10849:
10850: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10851: /*------------- h Bij x at various ages ------------*/
10852:
10853: int stepsize;
1.218 brouard 10854: /* int agelim; */
10855: int ageminl;
1.217 brouard 10856: int hstepm;
10857: int nhstepm;
1.238 brouard 10858: int h, i, i1, j, k, nres;
1.218 brouard 10859:
1.217 brouard 10860: double agedeb;
10861: double ***p3mat;
1.218 brouard 10862:
10863: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10864: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10865: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10866: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10867: }
10868: printf("Computing pij back: result on file '%s' \n", filerespijb);
10869: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10870:
10871: stepsize=(int) (stepm+YEARM-1)/YEARM;
10872: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10873:
1.218 brouard 10874: /* agelim=AGESUP; */
1.289 brouard 10875: ageminl=AGEINF; /* was 30 */
1.218 brouard 10876: hstepm=stepsize*YEARM; /* Every year of age */
10877: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10878:
10879: /* hstepm=1; aff par mois*/
10880: pstamp(ficrespijb);
1.255 brouard 10881: 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 10882: i1= pow(2,cptcoveff);
1.218 brouard 10883: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10884: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10885: /* k=k+1; */
1.238 brouard 10886: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10887: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10888: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10889: continue;
10890: fprintf(ficrespijb,"\n#****** ");
10891: for(j=1;j<=cptcoveff;j++)
10892: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10893: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10894: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10895: }
10896: fprintf(ficrespijb,"******\n");
1.264 brouard 10897: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10898: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10899: continue;
10900: }
10901:
10902: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10903: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10904: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
1.297 brouard 10905: 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 */
10906: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
1.238 brouard 10907:
10908: /* nhstepm=nhstepm*YEARM; aff par mois*/
10909:
1.266 brouard 10910: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10911: /* and memory limitations if stepm is small */
10912:
1.238 brouard 10913: /* oldm=oldms;savm=savms; */
10914: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10915: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10916: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10917: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10918: for(i=1; i<=nlstate;i++)
10919: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10920: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10921: fprintf(ficrespijb,"\n");
1.238 brouard 10922: for (h=0; h<=nhstepm; h++){
10923: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10924: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10925: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10926: for(i=1; i<=nlstate;i++)
10927: for(j=1; j<=nlstate+ndeath;j++)
10928: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10929: fprintf(ficrespijb,"\n");
10930: }
10931: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10932: fprintf(ficrespijb,"\n");
10933: } /* end age deb */
10934: } /* end combination */
10935: } /* end nres */
1.218 brouard 10936: return 0;
10937: } /* hBijx */
1.217 brouard 10938:
1.180 brouard 10939:
1.136 brouard 10940: /***********************************************/
10941: /**************** Main Program *****************/
10942: /***********************************************/
10943:
10944: int main(int argc, char *argv[])
10945: {
10946: #ifdef GSL
10947: const gsl_multimin_fminimizer_type *T;
10948: size_t iteri = 0, it;
10949: int rval = GSL_CONTINUE;
10950: int status = GSL_SUCCESS;
10951: double ssval;
10952: #endif
10953: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 10954: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
10955: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 10956: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10957: int jj, ll, li, lj, lk;
1.136 brouard 10958: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10959: int num_filled;
1.136 brouard 10960: int itimes;
10961: int NDIM=2;
10962: int vpopbased=0;
1.235 brouard 10963: int nres=0;
1.258 brouard 10964: int endishere=0;
1.277 brouard 10965: int noffset=0;
1.274 brouard 10966: int ncurrv=0; /* Temporary variable */
10967:
1.164 brouard 10968: char ca[32], cb[32];
1.136 brouard 10969: /* FILE *fichtm; *//* Html File */
10970: /* FILE *ficgp;*/ /*Gnuplot File */
10971: struct stat info;
1.191 brouard 10972: double agedeb=0.;
1.194 brouard 10973:
10974: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10975: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10976:
1.165 brouard 10977: double fret;
1.191 brouard 10978: double dum=0.; /* Dummy variable */
1.136 brouard 10979: double ***p3mat;
1.218 brouard 10980: /* double ***mobaverage; */
1.164 brouard 10981:
10982: char line[MAXLINE];
1.197 brouard 10983: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10984:
1.234 brouard 10985: char modeltemp[MAXLINE];
1.230 brouard 10986: char resultline[MAXLINE];
10987:
1.136 brouard 10988: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10989: char *tok, *val; /* pathtot */
1.290 brouard 10990: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs declared globally ;*/
1.195 brouard 10991: int c, h , cpt, c2;
1.191 brouard 10992: int jl=0;
10993: int i1, j1, jk, stepsize=0;
1.194 brouard 10994: int count=0;
10995:
1.164 brouard 10996: int *tab;
1.136 brouard 10997: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 10998: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
10999: /* double anprojf, mprojf, jprojf; */
11000: /* double jintmean,mintmean,aintmean; */
11001: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11002: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
11003: double yrfproj= 10.0; /* Number of years of forward projections */
11004: double yrbproj= 10.0; /* Number of years of backward projections */
11005: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 11006: int mobilav=0,popforecast=0;
1.191 brouard 11007: int hstepm=0, nhstepm=0;
1.136 brouard 11008: int agemortsup;
11009: float sumlpop=0.;
11010: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
11011: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
11012:
1.191 brouard 11013: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 11014: double ftolpl=FTOL;
11015: double **prlim;
1.217 brouard 11016: double **bprlim;
1.136 brouard 11017: double ***param; /* Matrix of parameters */
1.251 brouard 11018: double ***paramstart; /* Matrix of starting parameter values */
11019: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 11020: double **matcov; /* Matrix of covariance */
1.203 brouard 11021: double **hess; /* Hessian matrix */
1.136 brouard 11022: double ***delti3; /* Scale */
11023: double *delti; /* Scale */
11024: double ***eij, ***vareij;
11025: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 11026:
1.136 brouard 11027: double *epj, vepp;
1.164 brouard 11028:
1.273 brouard 11029: double dateprev1, dateprev2;
1.296 brouard 11030: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
11031: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
11032:
1.217 brouard 11033:
1.136 brouard 11034: double **ximort;
1.145 brouard 11035: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 11036: int *dcwave;
11037:
1.164 brouard 11038: char z[1]="c";
1.136 brouard 11039:
11040: /*char *strt;*/
11041: char strtend[80];
1.126 brouard 11042:
1.164 brouard 11043:
1.126 brouard 11044: /* setlocale (LC_ALL, ""); */
11045: /* bindtextdomain (PACKAGE, LOCALEDIR); */
11046: /* textdomain (PACKAGE); */
11047: /* setlocale (LC_CTYPE, ""); */
11048: /* setlocale (LC_MESSAGES, ""); */
11049:
11050: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 11051: rstart_time = time(NULL);
11052: /* (void) gettimeofday(&start_time,&tzp);*/
11053: start_time = *localtime(&rstart_time);
1.126 brouard 11054: curr_time=start_time;
1.157 brouard 11055: /*tml = *localtime(&start_time.tm_sec);*/
11056: /* strcpy(strstart,asctime(&tml)); */
11057: strcpy(strstart,asctime(&start_time));
1.126 brouard 11058:
11059: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 11060: /* tp.tm_sec = tp.tm_sec +86400; */
11061: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 11062: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
11063: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
11064: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 11065: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 11066: /* strt=asctime(&tmg); */
11067: /* printf("Time(after) =%s",strstart); */
11068: /* (void) time (&time_value);
11069: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
11070: * tm = *localtime(&time_value);
11071: * strstart=asctime(&tm);
11072: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
11073: */
11074:
11075: nberr=0; /* Number of errors and warnings */
11076: nbwarn=0;
1.184 brouard 11077: #ifdef WIN32
11078: _getcwd(pathcd, size);
11079: #else
1.126 brouard 11080: getcwd(pathcd, size);
1.184 brouard 11081: #endif
1.191 brouard 11082: syscompilerinfo(0);
1.196 brouard 11083: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 11084: if(argc <=1){
11085: printf("\nEnter the parameter file name: ");
1.205 brouard 11086: if(!fgets(pathr,FILENAMELENGTH,stdin)){
11087: printf("ERROR Empty parameter file name\n");
11088: goto end;
11089: }
1.126 brouard 11090: i=strlen(pathr);
11091: if(pathr[i-1]=='\n')
11092: pathr[i-1]='\0';
1.156 brouard 11093: i=strlen(pathr);
1.205 brouard 11094: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 11095: pathr[i-1]='\0';
1.205 brouard 11096: }
11097: i=strlen(pathr);
11098: if( i==0 ){
11099: printf("ERROR Empty parameter file name\n");
11100: goto end;
11101: }
11102: for (tok = pathr; tok != NULL; ){
1.126 brouard 11103: printf("Pathr |%s|\n",pathr);
11104: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
11105: printf("val= |%s| pathr=%s\n",val,pathr);
11106: strcpy (pathtot, val);
11107: if(pathr[0] == '\0') break; /* Dirty */
11108: }
11109: }
1.281 brouard 11110: else if (argc<=2){
11111: strcpy(pathtot,argv[1]);
11112: }
1.126 brouard 11113: else{
11114: strcpy(pathtot,argv[1]);
1.281 brouard 11115: strcpy(z,argv[2]);
11116: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 11117: }
11118: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
11119: /*cygwin_split_path(pathtot,path,optionfile);
11120: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
11121: /* cutv(path,optionfile,pathtot,'\\');*/
11122:
11123: /* Split argv[0], imach program to get pathimach */
11124: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
11125: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11126: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
11127: /* strcpy(pathimach,argv[0]); */
11128: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
11129: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
11130: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 11131: #ifdef WIN32
11132: _chdir(path); /* Can be a relative path */
11133: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
11134: #else
1.126 brouard 11135: chdir(path); /* Can be a relative path */
1.184 brouard 11136: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
11137: #endif
11138: printf("Current directory %s!\n",pathcd);
1.126 brouard 11139: strcpy(command,"mkdir ");
11140: strcat(command,optionfilefiname);
11141: if((outcmd=system(command)) != 0){
1.169 brouard 11142: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 11143: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
11144: /* fclose(ficlog); */
11145: /* exit(1); */
11146: }
11147: /* if((imk=mkdir(optionfilefiname))<0){ */
11148: /* perror("mkdir"); */
11149: /* } */
11150:
11151: /*-------- arguments in the command line --------*/
11152:
1.186 brouard 11153: /* Main Log file */
1.126 brouard 11154: strcat(filelog, optionfilefiname);
11155: strcat(filelog,".log"); /* */
11156: if((ficlog=fopen(filelog,"w"))==NULL) {
11157: printf("Problem with logfile %s\n",filelog);
11158: goto end;
11159: }
11160: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 11161: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 11162: fprintf(ficlog,"\nEnter the parameter file name: \n");
11163: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
11164: path=%s \n\
11165: optionfile=%s\n\
11166: optionfilext=%s\n\
1.156 brouard 11167: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 11168:
1.197 brouard 11169: syscompilerinfo(1);
1.167 brouard 11170:
1.126 brouard 11171: printf("Local time (at start):%s",strstart);
11172: fprintf(ficlog,"Local time (at start): %s",strstart);
11173: fflush(ficlog);
11174: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 11175: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 11176:
11177: /* */
11178: strcpy(fileres,"r");
11179: strcat(fileres, optionfilefiname);
1.201 brouard 11180: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 11181: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 11182: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 11183:
1.186 brouard 11184: /* Main ---------arguments file --------*/
1.126 brouard 11185:
11186: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 11187: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
11188: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 11189: fflush(ficlog);
1.149 brouard 11190: /* goto end; */
11191: exit(70);
1.126 brouard 11192: }
11193:
11194: strcpy(filereso,"o");
1.201 brouard 11195: strcat(filereso,fileresu);
1.126 brouard 11196: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
11197: printf("Problem with Output resultfile: %s\n", filereso);
11198: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
11199: fflush(ficlog);
11200: goto end;
11201: }
1.278 brouard 11202: /*-------- Rewriting parameter file ----------*/
11203: strcpy(rfileres,"r"); /* "Rparameterfile */
11204: strcat(rfileres,optionfilefiname); /* Parameter file first name */
11205: strcat(rfileres,"."); /* */
11206: strcat(rfileres,optionfilext); /* Other files have txt extension */
11207: if((ficres =fopen(rfileres,"w"))==NULL) {
11208: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
11209: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
11210: fflush(ficlog);
11211: goto end;
11212: }
11213: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 11214:
1.278 brouard 11215:
1.126 brouard 11216: /* Reads comments: lines beginning with '#' */
11217: numlinepar=0;
1.277 brouard 11218: /* Is it a BOM UTF-8 Windows file? */
11219: /* First parameter line */
1.197 brouard 11220: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 11221: noffset=0;
11222: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
11223: {
11224: noffset=noffset+3;
11225: printf("# File is an UTF8 Bom.\n"); // 0xBF
11226: }
1.302 brouard 11227: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
11228: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 11229: {
11230: noffset=noffset+2;
11231: printf("# File is an UTF16BE BOM file\n");
11232: }
11233: else if( line[0] == 0 && line[1] == 0)
11234: {
11235: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
11236: noffset=noffset+4;
11237: printf("# File is an UTF16BE BOM file\n");
11238: }
11239: } else{
11240: ;/*printf(" Not a BOM file\n");*/
11241: }
11242:
1.197 brouard 11243: /* If line starts with a # it is a comment */
1.277 brouard 11244: if (line[noffset] == '#') {
1.197 brouard 11245: numlinepar++;
11246: fputs(line,stdout);
11247: fputs(line,ficparo);
1.278 brouard 11248: fputs(line,ficres);
1.197 brouard 11249: fputs(line,ficlog);
11250: continue;
11251: }else
11252: break;
11253: }
11254: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11255: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11256: if (num_filled != 5) {
11257: printf("Should be 5 parameters\n");
1.283 brouard 11258: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11259: }
1.126 brouard 11260: numlinepar++;
1.197 brouard 11261: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11262: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11263: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11264: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11265: }
11266: /* Second parameter line */
11267: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11268: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11269: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11270: if (line[0] == '#') {
11271: numlinepar++;
1.283 brouard 11272: printf("%s",line);
11273: fprintf(ficres,"%s",line);
11274: fprintf(ficparo,"%s",line);
11275: fprintf(ficlog,"%s",line);
1.197 brouard 11276: continue;
11277: }else
11278: break;
11279: }
1.223 brouard 11280: 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", \
11281: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11282: if (num_filled != 11) {
11283: 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 11284: printf("but line=%s\n",line);
1.283 brouard 11285: 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");
11286: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11287: }
1.286 brouard 11288: if( lastpass > maxwav){
11289: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11290: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11291: fflush(ficlog);
11292: goto end;
11293: }
11294: 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 11295: 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 11296: 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 11297: 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 11298: }
1.203 brouard 11299: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11300: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11301: /* Third parameter line */
11302: while(fgets(line, MAXLINE, ficpar)) {
11303: /* If line starts with a # it is a comment */
11304: if (line[0] == '#') {
11305: numlinepar++;
1.283 brouard 11306: printf("%s",line);
11307: fprintf(ficres,"%s",line);
11308: fprintf(ficparo,"%s",line);
11309: fprintf(ficlog,"%s",line);
1.197 brouard 11310: continue;
11311: }else
11312: break;
11313: }
1.201 brouard 11314: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11315: if (num_filled != 1){
1.302 brouard 11316: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
11317: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 11318: model[0]='\0';
11319: goto end;
11320: }
11321: else{
11322: if (model[0]=='+'){
11323: for(i=1; i<=strlen(model);i++)
11324: modeltemp[i-1]=model[i];
1.201 brouard 11325: strcpy(model,modeltemp);
1.197 brouard 11326: }
11327: }
1.199 brouard 11328: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11329: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11330: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11331: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11332: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11333: }
11334: /* 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); */
11335: /* numlinepar=numlinepar+3; /\* In general *\/ */
11336: /* 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 11337: /* 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); */
11338: /* 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 11339: fflush(ficlog);
1.190 brouard 11340: /* if(model[0]=='#'|| model[0]== '\0'){ */
11341: if(model[0]=='#'){
1.279 brouard 11342: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11343: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11344: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11345: if(mle != -1){
1.279 brouard 11346: 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 11347: exit(1);
11348: }
11349: }
1.126 brouard 11350: while((c=getc(ficpar))=='#' && c!= EOF){
11351: ungetc(c,ficpar);
11352: fgets(line, MAXLINE, ficpar);
11353: numlinepar++;
1.195 brouard 11354: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11355: z[0]=line[1];
11356: }
11357: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11358: fputs(line, stdout);
11359: //puts(line);
1.126 brouard 11360: fputs(line,ficparo);
11361: fputs(line,ficlog);
11362: }
11363: ungetc(c,ficpar);
11364:
11365:
1.290 brouard 11366: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
11367: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
11368: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
11369: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11370: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11371: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11372: v1+v2*age+v2*v3 makes cptcovn = 3
11373: */
11374: if (strlen(model)>1)
1.187 brouard 11375: 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 11376: else
1.187 brouard 11377: ncovmodel=2; /* Constant and age */
1.133 brouard 11378: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11379: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11380: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11381: 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);
11382: 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);
11383: fflush(stdout);
11384: fclose (ficlog);
11385: goto end;
11386: }
1.126 brouard 11387: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11388: delti=delti3[1][1];
11389: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11390: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11391: /* We could also provide initial parameters values giving by simple logistic regression
11392: * only one way, that is without matrix product. We will have nlstate maximizations */
11393: /* for(i=1;i<nlstate;i++){ */
11394: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11395: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11396: /* } */
1.126 brouard 11397: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11398: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11399: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11400: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11401: fclose (ficparo);
11402: fclose (ficlog);
11403: goto end;
11404: exit(0);
1.220 brouard 11405: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11406: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11407: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11408: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11409: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11410: matcov=matrix(1,npar,1,npar);
1.203 brouard 11411: hess=matrix(1,npar,1,npar);
1.220 brouard 11412: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11413: /* Read guessed parameters */
1.126 brouard 11414: /* Reads comments: lines beginning with '#' */
11415: while((c=getc(ficpar))=='#' && c!= EOF){
11416: ungetc(c,ficpar);
11417: fgets(line, MAXLINE, ficpar);
11418: numlinepar++;
1.141 brouard 11419: fputs(line,stdout);
1.126 brouard 11420: fputs(line,ficparo);
11421: fputs(line,ficlog);
11422: }
11423: ungetc(c,ficpar);
11424:
11425: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11426: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11427: for(i=1; i <=nlstate; i++){
1.234 brouard 11428: j=0;
1.126 brouard 11429: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11430: if(jj==i) continue;
11431: j++;
1.292 brouard 11432: while((c=getc(ficpar))=='#' && c!= EOF){
11433: ungetc(c,ficpar);
11434: fgets(line, MAXLINE, ficpar);
11435: numlinepar++;
11436: fputs(line,stdout);
11437: fputs(line,ficparo);
11438: fputs(line,ficlog);
11439: }
11440: ungetc(c,ficpar);
1.234 brouard 11441: fscanf(ficpar,"%1d%1d",&i1,&j1);
11442: if ((i1 != i) || (j1 != jj)){
11443: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11444: It might be a problem of design; if ncovcol and the model are correct\n \
11445: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11446: exit(1);
11447: }
11448: fprintf(ficparo,"%1d%1d",i1,j1);
11449: if(mle==1)
11450: printf("%1d%1d",i,jj);
11451: fprintf(ficlog,"%1d%1d",i,jj);
11452: for(k=1; k<=ncovmodel;k++){
11453: fscanf(ficpar," %lf",¶m[i][j][k]);
11454: if(mle==1){
11455: printf(" %lf",param[i][j][k]);
11456: fprintf(ficlog," %lf",param[i][j][k]);
11457: }
11458: else
11459: fprintf(ficlog," %lf",param[i][j][k]);
11460: fprintf(ficparo," %lf",param[i][j][k]);
11461: }
11462: fscanf(ficpar,"\n");
11463: numlinepar++;
11464: if(mle==1)
11465: printf("\n");
11466: fprintf(ficlog,"\n");
11467: fprintf(ficparo,"\n");
1.126 brouard 11468: }
11469: }
11470: fflush(ficlog);
1.234 brouard 11471:
1.251 brouard 11472: /* Reads parameters values */
1.126 brouard 11473: p=param[1][1];
1.251 brouard 11474: pstart=paramstart[1][1];
1.126 brouard 11475:
11476: /* Reads comments: lines beginning with '#' */
11477: while((c=getc(ficpar))=='#' && c!= EOF){
11478: ungetc(c,ficpar);
11479: fgets(line, MAXLINE, ficpar);
11480: numlinepar++;
1.141 brouard 11481: fputs(line,stdout);
1.126 brouard 11482: fputs(line,ficparo);
11483: fputs(line,ficlog);
11484: }
11485: ungetc(c,ficpar);
11486:
11487: for(i=1; i <=nlstate; i++){
11488: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11489: fscanf(ficpar,"%1d%1d",&i1,&j1);
11490: if ( (i1-i) * (j1-j) != 0){
11491: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11492: exit(1);
11493: }
11494: printf("%1d%1d",i,j);
11495: fprintf(ficparo,"%1d%1d",i1,j1);
11496: fprintf(ficlog,"%1d%1d",i1,j1);
11497: for(k=1; k<=ncovmodel;k++){
11498: fscanf(ficpar,"%le",&delti3[i][j][k]);
11499: printf(" %le",delti3[i][j][k]);
11500: fprintf(ficparo," %le",delti3[i][j][k]);
11501: fprintf(ficlog," %le",delti3[i][j][k]);
11502: }
11503: fscanf(ficpar,"\n");
11504: numlinepar++;
11505: printf("\n");
11506: fprintf(ficparo,"\n");
11507: fprintf(ficlog,"\n");
1.126 brouard 11508: }
11509: }
11510: fflush(ficlog);
1.234 brouard 11511:
1.145 brouard 11512: /* Reads covariance matrix */
1.126 brouard 11513: delti=delti3[1][1];
1.220 brouard 11514:
11515:
1.126 brouard 11516: /* 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 11517:
1.126 brouard 11518: /* Reads comments: lines beginning with '#' */
11519: while((c=getc(ficpar))=='#' && c!= EOF){
11520: ungetc(c,ficpar);
11521: fgets(line, MAXLINE, ficpar);
11522: numlinepar++;
1.141 brouard 11523: fputs(line,stdout);
1.126 brouard 11524: fputs(line,ficparo);
11525: fputs(line,ficlog);
11526: }
11527: ungetc(c,ficpar);
1.220 brouard 11528:
1.126 brouard 11529: matcov=matrix(1,npar,1,npar);
1.203 brouard 11530: hess=matrix(1,npar,1,npar);
1.131 brouard 11531: for(i=1; i <=npar; i++)
11532: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11533:
1.194 brouard 11534: /* Scans npar lines */
1.126 brouard 11535: for(i=1; i <=npar; i++){
1.226 brouard 11536: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11537: if(count != 3){
1.226 brouard 11538: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11539: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11540: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11541: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11542: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11543: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11544: exit(1);
1.220 brouard 11545: }else{
1.226 brouard 11546: if(mle==1)
11547: printf("%1d%1d%d",i1,j1,jk);
11548: }
11549: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11550: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11551: for(j=1; j <=i; j++){
1.226 brouard 11552: fscanf(ficpar," %le",&matcov[i][j]);
11553: if(mle==1){
11554: printf(" %.5le",matcov[i][j]);
11555: }
11556: fprintf(ficlog," %.5le",matcov[i][j]);
11557: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11558: }
11559: fscanf(ficpar,"\n");
11560: numlinepar++;
11561: if(mle==1)
1.220 brouard 11562: printf("\n");
1.126 brouard 11563: fprintf(ficlog,"\n");
11564: fprintf(ficparo,"\n");
11565: }
1.194 brouard 11566: /* End of read covariance matrix npar lines */
1.126 brouard 11567: for(i=1; i <=npar; i++)
11568: for(j=i+1;j<=npar;j++)
1.226 brouard 11569: matcov[i][j]=matcov[j][i];
1.126 brouard 11570:
11571: if(mle==1)
11572: printf("\n");
11573: fprintf(ficlog,"\n");
11574:
11575: fflush(ficlog);
11576:
11577: } /* End of mle != -3 */
1.218 brouard 11578:
1.186 brouard 11579: /* Main data
11580: */
1.290 brouard 11581: nobs=lastobs-firstobs+1; /* was = lastobs;*/
11582: /* num=lvector(1,n); */
11583: /* moisnais=vector(1,n); */
11584: /* annais=vector(1,n); */
11585: /* moisdc=vector(1,n); */
11586: /* andc=vector(1,n); */
11587: /* weight=vector(1,n); */
11588: /* agedc=vector(1,n); */
11589: /* cod=ivector(1,n); */
11590: /* for(i=1;i<=n;i++){ */
11591: num=lvector(firstobs,lastobs);
11592: moisnais=vector(firstobs,lastobs);
11593: annais=vector(firstobs,lastobs);
11594: moisdc=vector(firstobs,lastobs);
11595: andc=vector(firstobs,lastobs);
11596: weight=vector(firstobs,lastobs);
11597: agedc=vector(firstobs,lastobs);
11598: cod=ivector(firstobs,lastobs);
11599: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 11600: num[i]=0;
11601: moisnais[i]=0;
11602: annais[i]=0;
11603: moisdc[i]=0;
11604: andc[i]=0;
11605: agedc[i]=0;
11606: cod[i]=0;
11607: weight[i]=1.0; /* Equal weights, 1 by default */
11608: }
1.290 brouard 11609: mint=matrix(1,maxwav,firstobs,lastobs);
11610: anint=matrix(1,maxwav,firstobs,lastobs);
11611: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11612: tab=ivector(1,NCOVMAX);
1.144 brouard 11613: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11614: 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 11615:
1.136 brouard 11616: /* Reads data from file datafile */
11617: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11618: goto end;
11619:
11620: /* Calculation of the number of parameters from char model */
1.234 brouard 11621: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11622: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11623: k=3 V4 Tvar[k=3]= 4 (from V4)
11624: k=2 V1 Tvar[k=2]= 1 (from V1)
11625: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11626: */
11627:
11628: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11629: TvarsDind=ivector(1,NCOVMAX); /* */
11630: TvarsD=ivector(1,NCOVMAX); /* */
11631: TvarsQind=ivector(1,NCOVMAX); /* */
11632: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11633: TvarF=ivector(1,NCOVMAX); /* */
11634: TvarFind=ivector(1,NCOVMAX); /* */
11635: TvarV=ivector(1,NCOVMAX); /* */
11636: TvarVind=ivector(1,NCOVMAX); /* */
11637: TvarA=ivector(1,NCOVMAX); /* */
11638: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11639: TvarFD=ivector(1,NCOVMAX); /* */
11640: TvarFDind=ivector(1,NCOVMAX); /* */
11641: TvarFQ=ivector(1,NCOVMAX); /* */
11642: TvarFQind=ivector(1,NCOVMAX); /* */
11643: TvarVD=ivector(1,NCOVMAX); /* */
11644: TvarVDind=ivector(1,NCOVMAX); /* */
11645: TvarVQ=ivector(1,NCOVMAX); /* */
11646: TvarVQind=ivector(1,NCOVMAX); /* */
11647:
1.230 brouard 11648: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11649: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11650: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11651: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11652: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11653: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11654: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11655: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11656: */
11657: /* For model-covariate k tells which data-covariate to use but
11658: because this model-covariate is a construction we invent a new column
11659: ncovcol + k1
11660: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11661: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11662: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11663: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11664: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11665: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11666: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11667: */
1.145 brouard 11668: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11669: 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 11670: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11671: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11672: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11673: 4 covariates (3 plus signs)
11674: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11675: */
1.230 brouard 11676: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11677: * individual dummy, fixed or varying:
11678: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11679: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11680: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11681: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11682: * Tmodelind[1]@9={9,0,3,2,}*/
11683: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11684: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11685: * individual quantitative, fixed or varying:
11686: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11687: * 3, 1, 0, 0, 0, 0, 0, 0},
11688: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11689: /* Main decodemodel */
11690:
1.187 brouard 11691:
1.223 brouard 11692: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11693: goto end;
11694:
1.137 brouard 11695: if((double)(lastobs-imx)/(double)imx > 1.10){
11696: nbwarn++;
11697: 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);
11698: 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);
11699: }
1.136 brouard 11700: /* if(mle==1){*/
1.137 brouard 11701: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11702: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11703: }
11704:
11705: /*-calculation of age at interview from date of interview and age at death -*/
11706: agev=matrix(1,maxwav,1,imx);
11707:
11708: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11709: goto end;
11710:
1.126 brouard 11711:
1.136 brouard 11712: agegomp=(int)agemin;
1.290 brouard 11713: free_vector(moisnais,firstobs,lastobs);
11714: free_vector(annais,firstobs,lastobs);
1.126 brouard 11715: /* free_matrix(mint,1,maxwav,1,n);
11716: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11717: /* free_vector(moisdc,1,n); */
11718: /* free_vector(andc,1,n); */
1.145 brouard 11719: /* */
11720:
1.126 brouard 11721: wav=ivector(1,imx);
1.214 brouard 11722: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11723: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11724: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11725: 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.*/
11726: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11727: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11728:
11729: /* Concatenates waves */
1.214 brouard 11730: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11731: Death is a valid wave (if date is known).
11732: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11733: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11734: and mw[mi+1][i]. dh depends on stepm.
11735: */
11736:
1.126 brouard 11737: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11738: /* Concatenates waves */
1.145 brouard 11739:
1.290 brouard 11740: free_vector(moisdc,firstobs,lastobs);
11741: free_vector(andc,firstobs,lastobs);
1.215 brouard 11742:
1.126 brouard 11743: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11744: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11745: ncodemax[1]=1;
1.145 brouard 11746: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11747: cptcoveff=0;
1.220 brouard 11748: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11749: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11750: }
11751:
11752: ncovcombmax=pow(2,cptcoveff);
11753: invalidvarcomb=ivector(1, ncovcombmax);
11754: for(i=1;i<ncovcombmax;i++)
11755: invalidvarcomb[i]=0;
11756:
1.211 brouard 11757: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11758: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11759: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11760:
1.200 brouard 11761: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11762: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11763: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11764: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11765: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11766: * (currently 0 or 1) in the data.
11767: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11768: * corresponding modality (h,j).
11769: */
11770:
1.145 brouard 11771: h=0;
11772: /*if (cptcovn > 0) */
1.126 brouard 11773: m=pow(2,cptcoveff);
11774:
1.144 brouard 11775: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11776: * For k=4 covariates, h goes from 1 to m=2**k
11777: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11778: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11779: * h\k 1 2 3 4
1.143 brouard 11780: *______________________________
11781: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11782: * 2 2 1 1 1
11783: * 3 i=2 1 2 1 1
11784: * 4 2 2 1 1
11785: * 5 i=3 1 i=2 1 2 1
11786: * 6 2 1 2 1
11787: * 7 i=4 1 2 2 1
11788: * 8 2 2 2 1
1.197 brouard 11789: * 9 i=5 1 i=3 1 i=2 1 2
11790: * 10 2 1 1 2
11791: * 11 i=6 1 2 1 2
11792: * 12 2 2 1 2
11793: * 13 i=7 1 i=4 1 2 2
11794: * 14 2 1 2 2
11795: * 15 i=8 1 2 2 2
11796: * 16 2 2 2 2
1.143 brouard 11797: */
1.212 brouard 11798: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11799: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11800: * and the value of each covariate?
11801: * V1=1, V2=1, V3=2, V4=1 ?
11802: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11803: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11804: * In order to get the real value in the data, we use nbcode
11805: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11806: * We are keeping this crazy system in order to be able (in the future?)
11807: * to have more than 2 values (0 or 1) for a covariate.
11808: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11809: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11810: * bbbbbbbb
11811: * 76543210
11812: * h-1 00000101 (6-1=5)
1.219 brouard 11813: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11814: * &
11815: * 1 00000001 (1)
1.219 brouard 11816: * 00000000 = 1 & ((h-1) >> (k-1))
11817: * +1= 00000001 =1
1.211 brouard 11818: *
11819: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11820: * h' 1101 =2^3+2^2+0x2^1+2^0
11821: * >>k' 11
11822: * & 00000001
11823: * = 00000001
11824: * +1 = 00000010=2 = codtabm(14,3)
11825: * Reverse h=6 and m=16?
11826: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11827: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11828: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11829: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11830: * V3=decodtabm(14,3,2**4)=2
11831: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11832: *(h-1) >> (j-1) 0011 =13 >> 2
11833: * &1 000000001
11834: * = 000000001
11835: * +1= 000000010 =2
11836: * 2211
11837: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11838: * V3=2
1.220 brouard 11839: * codtabm and decodtabm are identical
1.211 brouard 11840: */
11841:
1.145 brouard 11842:
11843: free_ivector(Ndum,-1,NCOVMAX);
11844:
11845:
1.126 brouard 11846:
1.186 brouard 11847: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11848: strcpy(optionfilegnuplot,optionfilefiname);
11849: if(mle==-3)
1.201 brouard 11850: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11851: strcat(optionfilegnuplot,".gp");
11852:
11853: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11854: printf("Problem with file %s",optionfilegnuplot);
11855: }
11856: else{
1.204 brouard 11857: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11858: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11859: //fprintf(ficgp,"set missing 'NaNq'\n");
11860: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11861: }
11862: /* fclose(ficgp);*/
1.186 brouard 11863:
11864:
11865: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11866:
11867: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11868: if(mle==-3)
1.201 brouard 11869: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11870: strcat(optionfilehtm,".htm");
11871: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11872: printf("Problem with %s \n",optionfilehtm);
11873: exit(0);
1.126 brouard 11874: }
11875:
11876: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11877: strcat(optionfilehtmcov,"-cov.htm");
11878: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11879: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11880: }
11881: else{
11882: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11883: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11884: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11885: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11886: }
11887:
1.213 brouard 11888: 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 11889: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11890: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11891: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11892: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11893: \n\
11894: <hr size=\"2\" color=\"#EC5E5E\">\
11895: <ul><li><h4>Parameter files</h4>\n\
11896: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11897: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11898: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11899: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11900: - Date and time at start: %s</ul>\n",\
11901: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11902: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11903: fileres,fileres,\
11904: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11905: fflush(fichtm);
11906:
11907: strcpy(pathr,path);
11908: strcat(pathr,optionfilefiname);
1.184 brouard 11909: #ifdef WIN32
11910: _chdir(optionfilefiname); /* Move to directory named optionfile */
11911: #else
1.126 brouard 11912: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11913: #endif
11914:
1.126 brouard 11915:
1.220 brouard 11916: /* Calculates basic frequencies. Computes observed prevalence at single age
11917: and for any valid combination of covariates
1.126 brouard 11918: and prints on file fileres'p'. */
1.251 brouard 11919: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11920: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11921:
11922: fprintf(fichtm,"\n");
1.286 brouard 11923: 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 11924: ftol, stepm);
11925: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
11926: ncurrv=1;
11927: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
11928: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
11929: ncurrv=i;
11930: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 11931: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 11932: ncurrv=i;
11933: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 11934: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 11935: ncurrv=i;
11936: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
11937: 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", \
11938: nlstate, ndeath, maxwav, mle, weightopt);
11939:
11940: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
11941: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
11942:
11943:
11944: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Total number of observations=%d <br>\n\
1.126 brouard 11945: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11946: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 11947: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 11948: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 11949: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11950: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11951: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11952: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11953:
1.126 brouard 11954: /* For Powell, parameters are in a vector p[] starting at p[1]
11955: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11956: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11957:
11958: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11959: /* For mortality only */
1.126 brouard 11960: if (mle==-3){
1.136 brouard 11961: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11962: for(i=1;i<=NDIM;i++)
11963: for(j=1;j<=NDIM;j++)
11964: ximort[i][j]=0.;
1.186 brouard 11965: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 11966: cens=ivector(firstobs,lastobs);
11967: ageexmed=vector(firstobs,lastobs);
11968: agecens=vector(firstobs,lastobs);
11969: dcwave=ivector(firstobs,lastobs);
1.223 brouard 11970:
1.126 brouard 11971: for (i=1; i<=imx; i++){
11972: dcwave[i]=-1;
11973: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11974: if (s[m][i]>nlstate) {
11975: dcwave[i]=m;
11976: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11977: break;
11978: }
1.126 brouard 11979: }
1.226 brouard 11980:
1.126 brouard 11981: for (i=1; i<=imx; i++) {
11982: if (wav[i]>0){
1.226 brouard 11983: ageexmed[i]=agev[mw[1][i]][i];
11984: j=wav[i];
11985: agecens[i]=1.;
11986:
11987: if (ageexmed[i]> 1 && wav[i] > 0){
11988: agecens[i]=agev[mw[j][i]][i];
11989: cens[i]= 1;
11990: }else if (ageexmed[i]< 1)
11991: cens[i]= -1;
11992: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11993: cens[i]=0 ;
1.126 brouard 11994: }
11995: else cens[i]=-1;
11996: }
11997:
11998: for (i=1;i<=NDIM;i++) {
11999: for (j=1;j<=NDIM;j++)
1.226 brouard 12000: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 12001: }
12002:
1.302 brouard 12003: p[1]=0.0268; p[NDIM]=0.083;
12004: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 12005:
12006:
1.136 brouard 12007: #ifdef GSL
12008: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 12009: #else
1.126 brouard 12010: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 12011: #endif
1.201 brouard 12012: strcpy(filerespow,"POW-MORT_");
12013: strcat(filerespow,fileresu);
1.126 brouard 12014: if((ficrespow=fopen(filerespow,"w"))==NULL) {
12015: printf("Problem with resultfile: %s\n", filerespow);
12016: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
12017: }
1.136 brouard 12018: #ifdef GSL
12019: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 12020: #else
1.126 brouard 12021: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 12022: #endif
1.126 brouard 12023: /* for (i=1;i<=nlstate;i++)
12024: for(j=1;j<=nlstate+ndeath;j++)
12025: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
12026: */
12027: fprintf(ficrespow,"\n");
1.136 brouard 12028: #ifdef GSL
12029: /* gsl starts here */
12030: T = gsl_multimin_fminimizer_nmsimplex;
12031: gsl_multimin_fminimizer *sfm = NULL;
12032: gsl_vector *ss, *x;
12033: gsl_multimin_function minex_func;
12034:
12035: /* Initial vertex size vector */
12036: ss = gsl_vector_alloc (NDIM);
12037:
12038: if (ss == NULL){
12039: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
12040: }
12041: /* Set all step sizes to 1 */
12042: gsl_vector_set_all (ss, 0.001);
12043:
12044: /* Starting point */
1.126 brouard 12045:
1.136 brouard 12046: x = gsl_vector_alloc (NDIM);
12047:
12048: if (x == NULL){
12049: gsl_vector_free(ss);
12050: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
12051: }
12052:
12053: /* Initialize method and iterate */
12054: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 12055: /* gsl_vector_set(x, 0, 0.0268); */
12056: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 12057: gsl_vector_set(x, 0, p[1]);
12058: gsl_vector_set(x, 1, p[2]);
12059:
12060: minex_func.f = &gompertz_f;
12061: minex_func.n = NDIM;
12062: minex_func.params = (void *)&p; /* ??? */
12063:
12064: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
12065: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
12066:
12067: printf("Iterations beginning .....\n\n");
12068: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
12069:
12070: iteri=0;
12071: while (rval == GSL_CONTINUE){
12072: iteri++;
12073: status = gsl_multimin_fminimizer_iterate(sfm);
12074:
12075: if (status) printf("error: %s\n", gsl_strerror (status));
12076: fflush(0);
12077:
12078: if (status)
12079: break;
12080:
12081: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
12082: ssval = gsl_multimin_fminimizer_size (sfm);
12083:
12084: if (rval == GSL_SUCCESS)
12085: printf ("converged to a local maximum at\n");
12086:
12087: printf("%5d ", iteri);
12088: for (it = 0; it < NDIM; it++){
12089: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
12090: }
12091: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
12092: }
12093:
12094: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
12095:
12096: gsl_vector_free(x); /* initial values */
12097: gsl_vector_free(ss); /* inital step size */
12098: for (it=0; it<NDIM; it++){
12099: p[it+1]=gsl_vector_get(sfm->x,it);
12100: fprintf(ficrespow," %.12lf", p[it]);
12101: }
12102: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
12103: #endif
12104: #ifdef POWELL
12105: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
12106: #endif
1.126 brouard 12107: fclose(ficrespow);
12108:
1.203 brouard 12109: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 12110:
12111: for(i=1; i <=NDIM; i++)
12112: for(j=i+1;j<=NDIM;j++)
1.220 brouard 12113: matcov[i][j]=matcov[j][i];
1.126 brouard 12114:
12115: printf("\nCovariance matrix\n ");
1.203 brouard 12116: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 12117: for(i=1; i <=NDIM; i++) {
12118: for(j=1;j<=NDIM;j++){
1.220 brouard 12119: printf("%f ",matcov[i][j]);
12120: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 12121: }
1.203 brouard 12122: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 12123: }
12124:
12125: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 12126: for (i=1;i<=NDIM;i++) {
1.126 brouard 12127: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 12128: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
12129: }
1.302 brouard 12130: lsurv=vector(agegomp,AGESUP);
12131: lpop=vector(agegomp,AGESUP);
12132: tpop=vector(agegomp,AGESUP);
1.126 brouard 12133: lsurv[agegomp]=100000;
12134:
12135: for (k=agegomp;k<=AGESUP;k++) {
12136: agemortsup=k;
12137: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
12138: }
12139:
12140: for (k=agegomp;k<agemortsup;k++)
12141: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
12142:
12143: for (k=agegomp;k<agemortsup;k++){
12144: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
12145: sumlpop=sumlpop+lpop[k];
12146: }
12147:
12148: tpop[agegomp]=sumlpop;
12149: for (k=agegomp;k<(agemortsup-3);k++){
12150: /* tpop[k+1]=2;*/
12151: tpop[k+1]=tpop[k]-lpop[k];
12152: }
12153:
12154:
12155: printf("\nAge lx qx dx Lx Tx e(x)\n");
12156: for (k=agegomp;k<(agemortsup-2);k++)
12157: 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]);
12158:
12159:
12160: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 12161: ageminpar=50;
12162: agemaxpar=100;
1.194 brouard 12163: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
12164: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12165: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12166: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
12167: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
12168: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12169: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12170: }else{
12171: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
12172: 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 12173: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 12174: }
1.201 brouard 12175: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 12176: stepm, weightopt,\
12177: model,imx,p,matcov,agemortsup);
12178:
1.302 brouard 12179: free_vector(lsurv,agegomp,AGESUP);
12180: free_vector(lpop,agegomp,AGESUP);
12181: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 12182: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 12183: free_ivector(dcwave,firstobs,lastobs);
12184: free_vector(agecens,firstobs,lastobs);
12185: free_vector(ageexmed,firstobs,lastobs);
12186: free_ivector(cens,firstobs,lastobs);
1.220 brouard 12187: #ifdef GSL
1.136 brouard 12188: #endif
1.186 brouard 12189: } /* Endof if mle==-3 mortality only */
1.205 brouard 12190: /* Standard */
12191: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
12192: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12193: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 12194: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 12195: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12196: for (k=1; k<=npar;k++)
12197: printf(" %d %8.5f",k,p[k]);
12198: printf("\n");
1.205 brouard 12199: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
12200: /* mlikeli uses func not funcone */
1.247 brouard 12201: /* for(i=1;i<nlstate;i++){ */
12202: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
12203: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
12204: /* } */
1.205 brouard 12205: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
12206: }
12207: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
12208: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
12209: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
12210: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12211: }
12212: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 12213: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
12214: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
12215: for (k=1; k<=npar;k++)
12216: printf(" %d %8.5f",k,p[k]);
12217: printf("\n");
12218:
12219: /*--------- results files --------------*/
1.283 brouard 12220: /* 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 12221:
12222:
12223: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12224: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12225: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
12226: for(i=1,jk=1; i <=nlstate; i++){
12227: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 12228: if (k != i) {
12229: printf("%d%d ",i,k);
12230: fprintf(ficlog,"%d%d ",i,k);
12231: fprintf(ficres,"%1d%1d ",i,k);
12232: for(j=1; j <=ncovmodel; j++){
12233: printf("%12.7f ",p[jk]);
12234: fprintf(ficlog,"%12.7f ",p[jk]);
12235: fprintf(ficres,"%12.7f ",p[jk]);
12236: jk++;
12237: }
12238: printf("\n");
12239: fprintf(ficlog,"\n");
12240: fprintf(ficres,"\n");
12241: }
1.126 brouard 12242: }
12243: }
1.203 brouard 12244: if(mle != 0){
12245: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 12246: ftolhess=ftol; /* Usually correct */
1.203 brouard 12247: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
12248: 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");
12249: 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");
12250: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 12251: for(k=1; k <=(nlstate+ndeath); k++){
12252: if (k != i) {
12253: printf("%d%d ",i,k);
12254: fprintf(ficlog,"%d%d ",i,k);
12255: for(j=1; j <=ncovmodel; j++){
12256: printf("%12.7f W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk], p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
12257: fprintf(ficlog,"%12.7f W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk], p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
12258: jk++;
12259: }
12260: printf("\n");
12261: fprintf(ficlog,"\n");
12262: }
12263: }
1.193 brouard 12264: }
1.203 brouard 12265: } /* end of hesscov and Wald tests */
1.225 brouard 12266:
1.203 brouard 12267: /* */
1.126 brouard 12268: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
12269: printf("# Scales (for hessian or gradient estimation)\n");
12270: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
12271: for(i=1,jk=1; i <=nlstate; i++){
12272: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 12273: if (j!=i) {
12274: fprintf(ficres,"%1d%1d",i,j);
12275: printf("%1d%1d",i,j);
12276: fprintf(ficlog,"%1d%1d",i,j);
12277: for(k=1; k<=ncovmodel;k++){
12278: printf(" %.5e",delti[jk]);
12279: fprintf(ficlog," %.5e",delti[jk]);
12280: fprintf(ficres," %.5e",delti[jk]);
12281: jk++;
12282: }
12283: printf("\n");
12284: fprintf(ficlog,"\n");
12285: fprintf(ficres,"\n");
12286: }
1.126 brouard 12287: }
12288: }
12289:
12290: 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 12291: if(mle >= 1) /* To big for the screen */
1.126 brouard 12292: 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");
12293: 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");
12294: /* # 121 Var(a12)\n\ */
12295: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12296: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12297: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12298: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12299: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12300: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12301: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12302:
12303:
12304: /* Just to have a covariance matrix which will be more understandable
12305: even is we still don't want to manage dictionary of variables
12306: */
12307: for(itimes=1;itimes<=2;itimes++){
12308: jj=0;
12309: for(i=1; i <=nlstate; i++){
1.225 brouard 12310: for(j=1; j <=nlstate+ndeath; j++){
12311: if(j==i) continue;
12312: for(k=1; k<=ncovmodel;k++){
12313: jj++;
12314: ca[0]= k+'a'-1;ca[1]='\0';
12315: if(itimes==1){
12316: if(mle>=1)
12317: printf("#%1d%1d%d",i,j,k);
12318: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12319: fprintf(ficres,"#%1d%1d%d",i,j,k);
12320: }else{
12321: if(mle>=1)
12322: printf("%1d%1d%d",i,j,k);
12323: fprintf(ficlog,"%1d%1d%d",i,j,k);
12324: fprintf(ficres,"%1d%1d%d",i,j,k);
12325: }
12326: ll=0;
12327: for(li=1;li <=nlstate; li++){
12328: for(lj=1;lj <=nlstate+ndeath; lj++){
12329: if(lj==li) continue;
12330: for(lk=1;lk<=ncovmodel;lk++){
12331: ll++;
12332: if(ll<=jj){
12333: cb[0]= lk +'a'-1;cb[1]='\0';
12334: if(ll<jj){
12335: if(itimes==1){
12336: if(mle>=1)
12337: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12338: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12339: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12340: }else{
12341: if(mle>=1)
12342: printf(" %.5e",matcov[jj][ll]);
12343: fprintf(ficlog," %.5e",matcov[jj][ll]);
12344: fprintf(ficres," %.5e",matcov[jj][ll]);
12345: }
12346: }else{
12347: if(itimes==1){
12348: if(mle>=1)
12349: printf(" Var(%s%1d%1d)",ca,i,j);
12350: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12351: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12352: }else{
12353: if(mle>=1)
12354: printf(" %.7e",matcov[jj][ll]);
12355: fprintf(ficlog," %.7e",matcov[jj][ll]);
12356: fprintf(ficres," %.7e",matcov[jj][ll]);
12357: }
12358: }
12359: }
12360: } /* end lk */
12361: } /* end lj */
12362: } /* end li */
12363: if(mle>=1)
12364: printf("\n");
12365: fprintf(ficlog,"\n");
12366: fprintf(ficres,"\n");
12367: numlinepar++;
12368: } /* end k*/
12369: } /*end j */
1.126 brouard 12370: } /* end i */
12371: } /* end itimes */
12372:
12373: fflush(ficlog);
12374: fflush(ficres);
1.225 brouard 12375: while(fgets(line, MAXLINE, ficpar)) {
12376: /* If line starts with a # it is a comment */
12377: if (line[0] == '#') {
12378: numlinepar++;
12379: fputs(line,stdout);
12380: fputs(line,ficparo);
12381: fputs(line,ficlog);
1.299 brouard 12382: fputs(line,ficres);
1.225 brouard 12383: continue;
12384: }else
12385: break;
12386: }
12387:
1.209 brouard 12388: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12389: /* ungetc(c,ficpar); */
12390: /* fgets(line, MAXLINE, ficpar); */
12391: /* fputs(line,stdout); */
12392: /* fputs(line,ficparo); */
12393: /* } */
12394: /* ungetc(c,ficpar); */
1.126 brouard 12395:
12396: estepm=0;
1.209 brouard 12397: 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 12398:
12399: if (num_filled != 6) {
12400: 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);
12401: 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);
12402: goto end;
12403: }
12404: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12405: }
12406: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12407: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12408:
1.209 brouard 12409: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12410: if (estepm==0 || estepm < stepm) estepm=stepm;
12411: if (fage <= 2) {
12412: bage = ageminpar;
12413: fage = agemaxpar;
12414: }
12415:
12416: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12417: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12418: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12419:
1.186 brouard 12420: /* Other stuffs, more or less useful */
1.254 brouard 12421: while(fgets(line, MAXLINE, ficpar)) {
12422: /* If line starts with a # it is a comment */
12423: if (line[0] == '#') {
12424: numlinepar++;
12425: fputs(line,stdout);
12426: fputs(line,ficparo);
12427: fputs(line,ficlog);
1.299 brouard 12428: fputs(line,ficres);
1.254 brouard 12429: continue;
12430: }else
12431: break;
12432: }
12433:
12434: 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){
12435:
12436: if (num_filled != 7) {
12437: 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);
12438: 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);
12439: goto end;
12440: }
12441: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12442: 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);
12443: 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);
12444: 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 12445: }
1.254 brouard 12446:
12447: while(fgets(line, MAXLINE, ficpar)) {
12448: /* If line starts with a # it is a comment */
12449: if (line[0] == '#') {
12450: numlinepar++;
12451: fputs(line,stdout);
12452: fputs(line,ficparo);
12453: fputs(line,ficlog);
1.299 brouard 12454: fputs(line,ficres);
1.254 brouard 12455: continue;
12456: }else
12457: break;
1.126 brouard 12458: }
12459:
12460:
12461: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12462: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12463:
1.254 brouard 12464: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12465: if (num_filled != 1) {
12466: 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);
12467: 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);
12468: goto end;
12469: }
12470: printf("pop_based=%d\n",popbased);
12471: fprintf(ficlog,"pop_based=%d\n",popbased);
12472: fprintf(ficparo,"pop_based=%d\n",popbased);
12473: fprintf(ficres,"pop_based=%d\n",popbased);
12474: }
12475:
1.258 brouard 12476: /* Results */
1.307 brouard 12477: endishere=0;
1.258 brouard 12478: nresult=0;
1.308 brouard 12479: parameterline=0;
1.258 brouard 12480: do{
12481: if(!fgets(line, MAXLINE, ficpar)){
12482: endishere=1;
1.308 brouard 12483: parameterline=15;
1.258 brouard 12484: }else if (line[0] == '#') {
12485: /* If line starts with a # it is a comment */
1.254 brouard 12486: numlinepar++;
12487: fputs(line,stdout);
12488: fputs(line,ficparo);
12489: fputs(line,ficlog);
1.299 brouard 12490: fputs(line,ficres);
1.254 brouard 12491: continue;
1.258 brouard 12492: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12493: parameterline=11;
1.296 brouard 12494: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 12495: parameterline=12;
1.307 brouard 12496: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 12497: parameterline=13;
1.307 brouard 12498: }
1.258 brouard 12499: else{
12500: parameterline=14;
1.254 brouard 12501: }
1.308 brouard 12502: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 12503: case 11:
1.296 brouard 12504: 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)){
12505: 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 12506: 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);
12507: 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);
12508: 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);
12509: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12510: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12511: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 12512: prvforecast = 1;
12513: }
12514: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 ! brouard 12515: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
! 12516: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
! 12517: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 12518: prvforecast = 2;
12519: }
12520: else {
12521: 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);
12522: 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);
12523: goto end;
1.258 brouard 12524: }
1.254 brouard 12525: break;
1.258 brouard 12526: case 12:
1.296 brouard 12527: 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)){
12528: 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);
12529: 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);
12530: 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);
12531: 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);
12532: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 12533: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12534: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 12535: prvbackcast = 1;
12536: }
12537: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 ! brouard 12538: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
! 12539: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
! 12540: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 12541: prvbackcast = 2;
12542: }
12543: else {
12544: 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);
12545: 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);
12546: goto end;
1.258 brouard 12547: }
1.230 brouard 12548: break;
1.258 brouard 12549: case 13:
1.307 brouard 12550: num_filled=sscanf(line,"result:%[^\n]\n",resultline);
12551: nresult++; /* Sum of resultlines */
12552: printf("Result %d: result:%s\n",nresult, resultline);
12553: if(nresult > MAXRESULTLINES){
12554: 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. ",MAXRESULTLINES,nresult,rfileres);
12555: 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. ",MAXRESULTLINES,nresult,rfileres);
12556: goto end;
12557: }
1.310 brouard 12558: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.307 brouard 12559: fprintf(ficparo,"result: %s\n",resultline);
12560: fprintf(ficres,"result: %s\n",resultline);
12561: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 12562: } else
12563: goto end;
1.307 brouard 12564: break;
12565: case 14:
12566: printf("Error: Unknown command '%s'\n",line);
12567: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
12568: if(ncovmodel >=2 && nresult==0 ){
12569: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
12570: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12571: }
1.307 brouard 12572: /* goto end; */
12573: break;
1.308 brouard 12574: case 15:
12575: printf("End of resultlines.\n");
12576: fprintf(ficlog,"End of resultlines.\n");
12577: break;
12578: default: /* parameterline =0 */
1.307 brouard 12579: nresult=1;
12580: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 12581: } /* End switch parameterline */
12582: }while(endishere==0); /* End do */
1.126 brouard 12583:
1.230 brouard 12584: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12585: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12586:
12587: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12588: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12589: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12590: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12591: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12592: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12593: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12594: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12595: }else{
1.270 brouard 12596: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 12597: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
12598: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
12599: if(prvforecast==1){
12600: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
12601: jprojd=jproj1;
12602: mprojd=mproj1;
12603: anprojd=anproj1;
12604: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
12605: jprojf=jproj2;
12606: mprojf=mproj2;
12607: anprojf=anproj2;
12608: } else if(prvforecast == 2){
12609: dateprojd=dateintmean;
12610: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
12611: dateprojf=dateintmean+yrfproj;
12612: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
12613: }
12614: if(prvbackcast==1){
12615: datebackd=(jback1+12*mback1+365*anback1)/365;
12616: jbackd=jback1;
12617: mbackd=mback1;
12618: anbackd=anback1;
12619: datebackf=(jback2+12*mback2+365*anback2)/365;
12620: jbackf=jback2;
12621: mbackf=mback2;
12622: anbackf=anback2;
12623: } else if(prvbackcast == 2){
12624: datebackd=dateintmean;
12625: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
12626: datebackf=dateintmean-yrbproj;
12627: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
12628: }
12629:
12630: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
1.220 brouard 12631: }
12632: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 12633: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
12634: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 12635:
1.225 brouard 12636: /*------------ free_vector -------------*/
12637: /* chdir(path); */
1.220 brouard 12638:
1.215 brouard 12639: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12640: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12641: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12642: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 12643: free_lvector(num,firstobs,lastobs);
12644: free_vector(agedc,firstobs,lastobs);
1.126 brouard 12645: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12646: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12647: fclose(ficparo);
12648: fclose(ficres);
1.220 brouard 12649:
12650:
1.186 brouard 12651: /* Other results (useful)*/
1.220 brouard 12652:
12653:
1.126 brouard 12654: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12655: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12656: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12657: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12658: fclose(ficrespl);
12659:
12660: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12661: /*#include "hpijx.h"*/
12662: hPijx(p, bage, fage);
1.145 brouard 12663: fclose(ficrespij);
1.227 brouard 12664:
1.220 brouard 12665: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12666: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12667: k=1;
1.126 brouard 12668: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12669:
1.269 brouard 12670: /* Prevalence for each covariate combination in probs[age][status][cov] */
12671: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12672: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12673: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12674: for(k=1;k<=ncovcombmax;k++)
12675: probs[i][j][k]=0.;
1.269 brouard 12676: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
12677: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12678: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 12679: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12680: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12681: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12682: for(k=1;k<=ncovcombmax;k++)
12683: mobaverages[i][j][k]=0.;
1.219 brouard 12684: mobaverage=mobaverages;
12685: if (mobilav!=0) {
1.235 brouard 12686: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12687: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12688: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12689: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12690: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12691: }
1.269 brouard 12692: } else if (mobilavproj !=0) {
1.235 brouard 12693: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12694: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12695: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12696: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12697: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12698: }
1.269 brouard 12699: }else{
12700: printf("Internal error moving average\n");
12701: fflush(stdout);
12702: exit(1);
1.219 brouard 12703: }
12704: }/* end if moving average */
1.227 brouard 12705:
1.126 brouard 12706: /*---------- Forecasting ------------------*/
1.296 brouard 12707: if(prevfcast==1){
12708: /* /\* if(stepm ==1){*\/ */
12709: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
12710: /*This done previously after freqsummary.*/
12711: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
12712: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
12713:
12714: /* } else if (prvforecast==2){ */
12715: /* /\* if(stepm ==1){*\/ */
12716: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
12717: /* } */
12718: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
12719: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 12720: }
1.269 brouard 12721:
1.296 brouard 12722: /* Prevbcasting */
12723: if(prevbcast==1){
1.219 brouard 12724: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12725: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12726: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12727:
12728: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12729:
12730: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 12731:
1.219 brouard 12732: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12733: fclose(ficresplb);
12734:
1.222 brouard 12735: hBijx(p, bage, fage, mobaverage);
12736: fclose(ficrespijb);
1.219 brouard 12737:
1.296 brouard 12738: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
12739: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
12740: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
12741: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
12742: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
12743: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
12744:
12745:
1.269 brouard 12746: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12747:
12748:
1.269 brouard 12749: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12750: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12751: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12752: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 12753: } /* end Prevbcasting */
1.268 brouard 12754:
1.186 brouard 12755:
12756: /* ------ Other prevalence ratios------------ */
1.126 brouard 12757:
1.215 brouard 12758: free_ivector(wav,1,imx);
12759: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12760: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12761: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12762:
12763:
1.127 brouard 12764: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12765:
1.201 brouard 12766: strcpy(filerese,"E_");
12767: strcat(filerese,fileresu);
1.126 brouard 12768: if((ficreseij=fopen(filerese,"w"))==NULL) {
12769: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12770: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12771: }
1.208 brouard 12772: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12773: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12774:
12775: pstamp(ficreseij);
1.219 brouard 12776:
1.235 brouard 12777: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12778: if (cptcovn < 1){i1=1;}
12779:
12780: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12781: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12782: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12783: continue;
1.219 brouard 12784: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12785: printf("\n#****** ");
1.225 brouard 12786: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12787: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12788: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12789: }
12790: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12791: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12792: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12793: }
12794: fprintf(ficreseij,"******\n");
1.235 brouard 12795: printf("******\n");
1.219 brouard 12796:
12797: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12798: oldm=oldms;savm=savms;
1.235 brouard 12799: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12800:
1.219 brouard 12801: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12802: }
12803: fclose(ficreseij);
1.208 brouard 12804: printf("done evsij\n");fflush(stdout);
12805: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 12806:
1.218 brouard 12807:
1.227 brouard 12808: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12809:
1.201 brouard 12810: strcpy(filerest,"T_");
12811: strcat(filerest,fileresu);
1.127 brouard 12812: if((ficrest=fopen(filerest,"w"))==NULL) {
12813: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12814: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12815: }
1.208 brouard 12816: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12817: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12818: strcpy(fileresstde,"STDE_");
12819: strcat(fileresstde,fileresu);
1.126 brouard 12820: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12821: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12822: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12823: }
1.227 brouard 12824: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12825: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12826:
1.201 brouard 12827: strcpy(filerescve,"CVE_");
12828: strcat(filerescve,fileresu);
1.126 brouard 12829: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12830: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12831: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12832: }
1.227 brouard 12833: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12834: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12835:
1.201 brouard 12836: strcpy(fileresv,"V_");
12837: strcat(fileresv,fileresu);
1.126 brouard 12838: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12839: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12840: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12841: }
1.227 brouard 12842: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12843: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12844:
1.235 brouard 12845: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12846: if (cptcovn < 1){i1=1;}
12847:
12848: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12849: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12850: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12851: continue;
1.242 brouard 12852: printf("\n#****** Result for:");
12853: fprintf(ficrest,"\n#****** Result for:");
12854: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12855: for(j=1;j<=cptcoveff;j++){
12856: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12857: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12858: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12859: }
1.235 brouard 12860: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12861: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12862: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12863: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12864: }
1.208 brouard 12865: fprintf(ficrest,"******\n");
1.227 brouard 12866: fprintf(ficlog,"******\n");
12867: printf("******\n");
1.208 brouard 12868:
12869: fprintf(ficresstdeij,"\n#****** ");
12870: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12871: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12872: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12873: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12874: }
1.235 brouard 12875: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12876: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12877: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12878: }
1.208 brouard 12879: fprintf(ficresstdeij,"******\n");
12880: fprintf(ficrescveij,"******\n");
12881:
12882: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12883: /* pstamp(ficresvij); */
1.225 brouard 12884: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12885: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12886: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12887: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12888: }
1.208 brouard 12889: fprintf(ficresvij,"******\n");
12890:
12891: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12892: oldm=oldms;savm=savms;
1.235 brouard 12893: printf(" cvevsij ");
12894: fprintf(ficlog, " cvevsij ");
12895: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12896: printf(" end cvevsij \n ");
12897: fprintf(ficlog, " end cvevsij \n ");
12898:
12899: /*
12900: */
12901: /* goto endfree; */
12902:
12903: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12904: pstamp(ficrest);
12905:
1.269 brouard 12906: epj=vector(1,nlstate+1);
1.208 brouard 12907: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12908: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12909: cptcod= 0; /* To be deleted */
12910: printf("varevsij vpopbased=%d \n",vpopbased);
12911: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12912: 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 12913: 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 ");
12914: if(vpopbased==1)
12915: 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);
12916: else
1.288 brouard 12917: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12918: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12919: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12920: fprintf(ficrest,"\n");
12921: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 12922: printf("Computing age specific forward period (stable) prevalences in each health state \n");
12923: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12924: for(age=bage; age <=fage ;age++){
1.235 brouard 12925: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12926: if (vpopbased==1) {
12927: if(mobilav ==0){
12928: for(i=1; i<=nlstate;i++)
12929: prlim[i][i]=probs[(int)age][i][k];
12930: }else{ /* mobilav */
12931: for(i=1; i<=nlstate;i++)
12932: prlim[i][i]=mobaverage[(int)age][i][k];
12933: }
12934: }
1.219 brouard 12935:
1.227 brouard 12936: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12937: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12938: /* printf(" age %4.0f ",age); */
12939: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12940: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12941: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12942: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12943: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12944: }
12945: epj[nlstate+1] +=epj[j];
12946: }
12947: /* printf(" age %4.0f \n",age); */
1.219 brouard 12948:
1.227 brouard 12949: for(i=1, vepp=0.;i <=nlstate;i++)
12950: for(j=1;j <=nlstate;j++)
12951: vepp += vareij[i][j][(int)age];
12952: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12953: for(j=1;j <=nlstate;j++){
12954: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12955: }
12956: fprintf(ficrest,"\n");
12957: }
1.208 brouard 12958: } /* End vpopbased */
1.269 brouard 12959: free_vector(epj,1,nlstate+1);
1.208 brouard 12960: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12961: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 12962: printf("done selection\n");fflush(stdout);
12963: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12964:
1.235 brouard 12965: } /* End k selection */
1.227 brouard 12966:
12967: printf("done State-specific expectancies\n");fflush(stdout);
12968: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12969:
1.288 brouard 12970: /* variance-covariance of forward period prevalence*/
1.269 brouard 12971: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12972:
1.227 brouard 12973:
1.290 brouard 12974: free_vector(weight,firstobs,lastobs);
1.227 brouard 12975: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 12976: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
12977: free_matrix(anint,1,maxwav,firstobs,lastobs);
12978: free_matrix(mint,1,maxwav,firstobs,lastobs);
12979: free_ivector(cod,firstobs,lastobs);
1.227 brouard 12980: free_ivector(tab,1,NCOVMAX);
12981: fclose(ficresstdeij);
12982: fclose(ficrescveij);
12983: fclose(ficresvij);
12984: fclose(ficrest);
12985: fclose(ficpar);
12986:
12987:
1.126 brouard 12988: /*---------- End : free ----------------*/
1.219 brouard 12989: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 12990: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
12991: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12992: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12993: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12994: } /* mle==-3 arrives here for freeing */
1.227 brouard 12995: /* endfree:*/
12996: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12997: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12998: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 brouard 12999: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
13000: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
13001: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
13002: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 13003: free_matrix(matcov,1,npar,1,npar);
13004: free_matrix(hess,1,npar,1,npar);
13005: /*free_vector(delti,1,npar);*/
13006: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13007: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 13008: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 13009: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13010:
13011: free_ivector(ncodemax,1,NCOVMAX);
13012: free_ivector(ncodemaxwundef,1,NCOVMAX);
13013: free_ivector(Dummy,-1,NCOVMAX);
13014: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 13015: free_ivector(DummyV,1,NCOVMAX);
13016: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 13017: free_ivector(Typevar,-1,NCOVMAX);
13018: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 13019: free_ivector(TvarsQ,1,NCOVMAX);
13020: free_ivector(TvarsQind,1,NCOVMAX);
13021: free_ivector(TvarsD,1,NCOVMAX);
13022: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 13023: free_ivector(TvarFD,1,NCOVMAX);
13024: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 13025: free_ivector(TvarF,1,NCOVMAX);
13026: free_ivector(TvarFind,1,NCOVMAX);
13027: free_ivector(TvarV,1,NCOVMAX);
13028: free_ivector(TvarVind,1,NCOVMAX);
13029: free_ivector(TvarA,1,NCOVMAX);
13030: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 13031: free_ivector(TvarFQ,1,NCOVMAX);
13032: free_ivector(TvarFQind,1,NCOVMAX);
13033: free_ivector(TvarVD,1,NCOVMAX);
13034: free_ivector(TvarVDind,1,NCOVMAX);
13035: free_ivector(TvarVQ,1,NCOVMAX);
13036: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 13037: free_ivector(Tvarsel,1,NCOVMAX);
13038: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 13039: free_ivector(Tposprod,1,NCOVMAX);
13040: free_ivector(Tprod,1,NCOVMAX);
13041: free_ivector(Tvaraff,1,NCOVMAX);
13042: free_ivector(invalidvarcomb,1,ncovcombmax);
13043: free_ivector(Tage,1,NCOVMAX);
13044: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 13045: free_ivector(TmodelInvind,1,NCOVMAX);
13046: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 13047:
13048: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
13049: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 13050: fflush(fichtm);
13051: fflush(ficgp);
13052:
1.227 brouard 13053:
1.126 brouard 13054: if((nberr >0) || (nbwarn>0)){
1.216 brouard 13055: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
13056: 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 13057: }else{
13058: printf("End of Imach\n");
13059: fprintf(ficlog,"End of Imach\n");
13060: }
13061: printf("See log file on %s\n",filelog);
13062: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 13063: /*(void) gettimeofday(&end_time,&tzp);*/
13064: rend_time = time(NULL);
13065: end_time = *localtime(&rend_time);
13066: /* tml = *localtime(&end_time.tm_sec); */
13067: strcpy(strtend,asctime(&end_time));
1.126 brouard 13068: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
13069: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 13070: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 13071:
1.157 brouard 13072: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
13073: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
13074: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 13075: /* printf("Total time was %d uSec.\n", total_usecs);*/
13076: /* if(fileappend(fichtm,optionfilehtm)){ */
13077: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13078: fclose(fichtm);
13079: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
13080: fclose(fichtmcov);
13081: fclose(ficgp);
13082: fclose(ficlog);
13083: /*------ End -----------*/
1.227 brouard 13084:
1.281 brouard 13085:
13086: /* Executes gnuplot */
1.227 brouard 13087:
13088: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 13089: #ifdef WIN32
1.227 brouard 13090: if (_chdir(pathcd) != 0)
13091: printf("Can't move to directory %s!\n",path);
13092: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 13093: #else
1.227 brouard 13094: if(chdir(pathcd) != 0)
13095: printf("Can't move to directory %s!\n", path);
13096: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 13097: #endif
1.126 brouard 13098: printf("Current directory %s!\n",pathcd);
13099: /*strcat(plotcmd,CHARSEPARATOR);*/
13100: sprintf(plotcmd,"gnuplot");
1.157 brouard 13101: #ifdef _WIN32
1.126 brouard 13102: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
13103: #endif
13104: if(!stat(plotcmd,&info)){
1.158 brouard 13105: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13106: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 13107: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 13108: }else
13109: strcpy(pplotcmd,plotcmd);
1.157 brouard 13110: #ifdef __unix
1.126 brouard 13111: strcpy(plotcmd,GNUPLOTPROGRAM);
13112: if(!stat(plotcmd,&info)){
1.158 brouard 13113: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 13114: }else
13115: strcpy(pplotcmd,plotcmd);
13116: #endif
13117: }else
13118: strcpy(pplotcmd,plotcmd);
13119:
13120: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 13121: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 13122: strcpy(pplotcmd,plotcmd);
1.227 brouard 13123:
1.126 brouard 13124: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 13125: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 13126: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 13127: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 13128: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 13129: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 13130: strcpy(plotcmd,pplotcmd);
13131: }
1.126 brouard 13132: }
1.158 brouard 13133: printf(" Successful, please wait...");
1.126 brouard 13134: while (z[0] != 'q') {
13135: /* chdir(path); */
1.154 brouard 13136: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 13137: scanf("%s",z);
13138: /* if (z[0] == 'c') system("./imach"); */
13139: if (z[0] == 'e') {
1.158 brouard 13140: #ifdef __APPLE__
1.152 brouard 13141: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 13142: #elif __linux
13143: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 13144: #else
1.152 brouard 13145: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 13146: #endif
13147: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
13148: system(pplotcmd);
1.126 brouard 13149: }
13150: else if (z[0] == 'g') system(plotcmd);
13151: else if (z[0] == 'q') exit(0);
13152: }
1.227 brouard 13153: end:
1.126 brouard 13154: while (z[0] != 'q') {
1.195 brouard 13155: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 13156: scanf("%s",z);
13157: }
1.283 brouard 13158: printf("End\n");
1.282 brouard 13159: exit(0);
1.126 brouard 13160: }
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