Annotation of imach/src/imach.c, revision 1.290
1.290 ! brouard 1: /* $Id: imach.c,v 1.289 2018/12/13 09:16:26 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.290 ! brouard 4: Revision 1.289 2018/12/13 09:16:26 brouard
! 5: Summary: Bug for young ages (<-30) will be in r17
! 6:
1.289 brouard 7: Revision 1.288 2018/05/02 20:58:27 brouard
8: Summary: Some bugs fixed
9:
1.288 brouard 10: Revision 1.287 2018/05/01 17:57:25 brouard
11: Summary: Bug fixed by providing frequencies only for non missing covariates
12:
1.287 brouard 13: Revision 1.286 2018/04/27 14:27:04 brouard
14: Summary: some minor bugs
15:
1.286 brouard 16: Revision 1.285 2018/04/21 21:02:16 brouard
17: Summary: Some bugs fixed, valgrind tested
18:
1.285 brouard 19: Revision 1.284 2018/04/20 05:22:13 brouard
20: Summary: Computing mean and stdeviation of fixed quantitative variables
21:
1.284 brouard 22: Revision 1.283 2018/04/19 14:49:16 brouard
23: Summary: Some minor bugs fixed
24:
1.283 brouard 25: Revision 1.282 2018/02/27 22:50:02 brouard
26: *** empty log message ***
27:
1.282 brouard 28: Revision 1.281 2018/02/27 19:25:23 brouard
29: Summary: Adding second argument for quitting
30:
1.281 brouard 31: Revision 1.280 2018/02/21 07:58:13 brouard
32: Summary: 0.99r15
33:
34: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
35:
1.280 brouard 36: Revision 1.279 2017/07/20 13:35:01 brouard
37: Summary: temporary working
38:
1.279 brouard 39: Revision 1.278 2017/07/19 14:09:02 brouard
40: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
41:
1.278 brouard 42: Revision 1.277 2017/07/17 08:53:49 brouard
43: Summary: BOM files can be read now
44:
1.277 brouard 45: Revision 1.276 2017/06/30 15:48:31 brouard
46: Summary: Graphs improvements
47:
1.276 brouard 48: Revision 1.275 2017/06/30 13:39:33 brouard
49: Summary: Saito's color
50:
1.275 brouard 51: Revision 1.274 2017/06/29 09:47:08 brouard
52: Summary: Version 0.99r14
53:
1.274 brouard 54: Revision 1.273 2017/06/27 11:06:02 brouard
55: Summary: More documentation on projections
56:
1.273 brouard 57: Revision 1.272 2017/06/27 10:22:40 brouard
58: Summary: Color of backprojection changed from 6 to 5(yellow)
59:
1.272 brouard 60: Revision 1.271 2017/06/27 10:17:50 brouard
61: Summary: Some bug with rint
62:
1.271 brouard 63: Revision 1.270 2017/05/24 05:45:29 brouard
64: *** empty log message ***
65:
1.270 brouard 66: Revision 1.269 2017/05/23 08:39:25 brouard
67: Summary: Code into subroutine, cleanings
68:
1.269 brouard 69: Revision 1.268 2017/05/18 20:09:32 brouard
70: Summary: backprojection and confidence intervals of backprevalence
71:
1.268 brouard 72: Revision 1.267 2017/05/13 10:25:05 brouard
73: Summary: temporary save for backprojection
74:
1.267 brouard 75: Revision 1.266 2017/05/13 07:26:12 brouard
76: Summary: Version 0.99r13 (improvements and bugs fixed)
77:
1.266 brouard 78: Revision 1.265 2017/04/26 16:22:11 brouard
79: Summary: imach 0.99r13 Some bugs fixed
80:
1.265 brouard 81: Revision 1.264 2017/04/26 06:01:29 brouard
82: Summary: Labels in graphs
83:
1.264 brouard 84: Revision 1.263 2017/04/24 15:23:15 brouard
85: Summary: to save
86:
1.263 brouard 87: Revision 1.262 2017/04/18 16:48:12 brouard
88: *** empty log message ***
89:
1.262 brouard 90: Revision 1.261 2017/04/05 10:14:09 brouard
91: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
92:
1.261 brouard 93: Revision 1.260 2017/04/04 17:46:59 brouard
94: Summary: Gnuplot indexations fixed (humm)
95:
1.260 brouard 96: Revision 1.259 2017/04/04 13:01:16 brouard
97: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
98:
1.259 brouard 99: Revision 1.258 2017/04/03 10:17:47 brouard
100: Summary: Version 0.99r12
101:
102: Some cleanings, conformed with updated documentation.
103:
1.258 brouard 104: Revision 1.257 2017/03/29 16:53:30 brouard
105: Summary: Temp
106:
1.257 brouard 107: Revision 1.256 2017/03/27 05:50:23 brouard
108: Summary: Temporary
109:
1.256 brouard 110: Revision 1.255 2017/03/08 16:02:28 brouard
111: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
112:
1.255 brouard 113: Revision 1.254 2017/03/08 07:13:00 brouard
114: Summary: Fixing data parameter line
115:
1.254 brouard 116: Revision 1.253 2016/12/15 11:59:41 brouard
117: Summary: 0.99 in progress
118:
1.253 brouard 119: Revision 1.252 2016/09/15 21:15:37 brouard
120: *** empty log message ***
121:
1.252 brouard 122: Revision 1.251 2016/09/15 15:01:13 brouard
123: Summary: not working
124:
1.251 brouard 125: Revision 1.250 2016/09/08 16:07:27 brouard
126: Summary: continue
127:
1.250 brouard 128: Revision 1.249 2016/09/07 17:14:18 brouard
129: Summary: Starting values from frequencies
130:
1.249 brouard 131: Revision 1.248 2016/09/07 14:10:18 brouard
132: *** empty log message ***
133:
1.248 brouard 134: Revision 1.247 2016/09/02 11:11:21 brouard
135: *** empty log message ***
136:
1.247 brouard 137: Revision 1.246 2016/09/02 08:49:22 brouard
138: *** empty log message ***
139:
1.246 brouard 140: Revision 1.245 2016/09/02 07:25:01 brouard
141: *** empty log message ***
142:
1.245 brouard 143: Revision 1.244 2016/09/02 07:17:34 brouard
144: *** empty log message ***
145:
1.244 brouard 146: Revision 1.243 2016/09/02 06:45:35 brouard
147: *** empty log message ***
148:
1.243 brouard 149: Revision 1.242 2016/08/30 15:01:20 brouard
150: Summary: Fixing a lots
151:
1.242 brouard 152: Revision 1.241 2016/08/29 17:17:25 brouard
153: Summary: gnuplot problem in Back projection to fix
154:
1.241 brouard 155: Revision 1.240 2016/08/29 07:53:18 brouard
156: Summary: Better
157:
1.240 brouard 158: Revision 1.239 2016/08/26 15:51:03 brouard
159: Summary: Improvement in Powell output in order to copy and paste
160:
161: Author:
162:
1.239 brouard 163: Revision 1.238 2016/08/26 14:23:35 brouard
164: Summary: Starting tests of 0.99
165:
1.238 brouard 166: Revision 1.237 2016/08/26 09:20:19 brouard
167: Summary: to valgrind
168:
1.237 brouard 169: Revision 1.236 2016/08/25 10:50:18 brouard
170: *** empty log message ***
171:
1.236 brouard 172: Revision 1.235 2016/08/25 06:59:23 brouard
173: *** empty log message ***
174:
1.235 brouard 175: Revision 1.234 2016/08/23 16:51:20 brouard
176: *** empty log message ***
177:
1.234 brouard 178: Revision 1.233 2016/08/23 07:40:50 brouard
179: Summary: not working
180:
1.233 brouard 181: Revision 1.232 2016/08/22 14:20:21 brouard
182: Summary: not working
183:
1.232 brouard 184: Revision 1.231 2016/08/22 07:17:15 brouard
185: Summary: not working
186:
1.231 brouard 187: Revision 1.230 2016/08/22 06:55:53 brouard
188: Summary: Not working
189:
1.230 brouard 190: Revision 1.229 2016/07/23 09:45:53 brouard
191: Summary: Completing for func too
192:
1.229 brouard 193: Revision 1.228 2016/07/22 17:45:30 brouard
194: Summary: Fixing some arrays, still debugging
195:
1.227 brouard 196: Revision 1.226 2016/07/12 18:42:34 brouard
197: Summary: temp
198:
1.226 brouard 199: Revision 1.225 2016/07/12 08:40:03 brouard
200: Summary: saving but not running
201:
1.225 brouard 202: Revision 1.224 2016/07/01 13:16:01 brouard
203: Summary: Fixes
204:
1.224 brouard 205: Revision 1.223 2016/02/19 09:23:35 brouard
206: Summary: temporary
207:
1.223 brouard 208: Revision 1.222 2016/02/17 08:14:50 brouard
209: Summary: Probably last 0.98 stable version 0.98r6
210:
1.222 brouard 211: Revision 1.221 2016/02/15 23:35:36 brouard
212: Summary: minor bug
213:
1.220 brouard 214: Revision 1.219 2016/02/15 00:48:12 brouard
215: *** empty log message ***
216:
1.219 brouard 217: Revision 1.218 2016/02/12 11:29:23 brouard
218: Summary: 0.99 Back projections
219:
1.218 brouard 220: Revision 1.217 2015/12/23 17:18:31 brouard
221: Summary: Experimental backcast
222:
1.217 brouard 223: Revision 1.216 2015/12/18 17:32:11 brouard
224: Summary: 0.98r4 Warning and status=-2
225:
226: Version 0.98r4 is now:
227: - displaying an error when status is -1, date of interview unknown and date of death known;
228: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
229: Older changes concerning s=-2, dating from 2005 have been supersed.
230:
1.216 brouard 231: Revision 1.215 2015/12/16 08:52:24 brouard
232: Summary: 0.98r4 working
233:
1.215 brouard 234: Revision 1.214 2015/12/16 06:57:54 brouard
235: Summary: temporary not working
236:
1.214 brouard 237: Revision 1.213 2015/12/11 18:22:17 brouard
238: Summary: 0.98r4
239:
1.213 brouard 240: Revision 1.212 2015/11/21 12:47:24 brouard
241: Summary: minor typo
242:
1.212 brouard 243: Revision 1.211 2015/11/21 12:41:11 brouard
244: Summary: 0.98r3 with some graph of projected cross-sectional
245:
246: Author: Nicolas Brouard
247:
1.211 brouard 248: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 249: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 250: Summary: Adding ftolpl parameter
251: Author: N Brouard
252:
253: We had difficulties to get smoothed confidence intervals. It was due
254: to the period prevalence which wasn't computed accurately. The inner
255: parameter ftolpl is now an outer parameter of the .imach parameter
256: file after estepm. If ftolpl is small 1.e-4 and estepm too,
257: computation are long.
258:
1.209 brouard 259: Revision 1.208 2015/11/17 14:31:57 brouard
260: Summary: temporary
261:
1.208 brouard 262: Revision 1.207 2015/10/27 17:36:57 brouard
263: *** empty log message ***
264:
1.207 brouard 265: Revision 1.206 2015/10/24 07:14:11 brouard
266: *** empty log message ***
267:
1.206 brouard 268: Revision 1.205 2015/10/23 15:50:53 brouard
269: Summary: 0.98r3 some clarification for graphs on likelihood contributions
270:
1.205 brouard 271: Revision 1.204 2015/10/01 16:20:26 brouard
272: Summary: Some new graphs of contribution to likelihood
273:
1.204 brouard 274: Revision 1.203 2015/09/30 17:45:14 brouard
275: Summary: looking at better estimation of the hessian
276:
277: Also a better criteria for convergence to the period prevalence And
278: therefore adding the number of years needed to converge. (The
279: prevalence in any alive state shold sum to one
280:
1.203 brouard 281: Revision 1.202 2015/09/22 19:45:16 brouard
282: Summary: Adding some overall graph on contribution to likelihood. Might change
283:
1.202 brouard 284: Revision 1.201 2015/09/15 17:34:58 brouard
285: Summary: 0.98r0
286:
287: - Some new graphs like suvival functions
288: - Some bugs fixed like model=1+age+V2.
289:
1.201 brouard 290: Revision 1.200 2015/09/09 16:53:55 brouard
291: Summary: Big bug thanks to Flavia
292:
293: Even model=1+age+V2. did not work anymore
294:
1.200 brouard 295: Revision 1.199 2015/09/07 14:09:23 brouard
296: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
297:
1.199 brouard 298: Revision 1.198 2015/09/03 07:14:39 brouard
299: Summary: 0.98q5 Flavia
300:
1.198 brouard 301: Revision 1.197 2015/09/01 18:24:39 brouard
302: *** empty log message ***
303:
1.197 brouard 304: Revision 1.196 2015/08/18 23:17:52 brouard
305: Summary: 0.98q5
306:
1.196 brouard 307: Revision 1.195 2015/08/18 16:28:39 brouard
308: Summary: Adding a hack for testing purpose
309:
310: After reading the title, ftol and model lines, if the comment line has
311: a q, starting with #q, the answer at the end of the run is quit. It
312: permits to run test files in batch with ctest. The former workaround was
313: $ echo q | imach foo.imach
314:
1.195 brouard 315: Revision 1.194 2015/08/18 13:32:00 brouard
316: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
317:
1.194 brouard 318: Revision 1.193 2015/08/04 07:17:42 brouard
319: Summary: 0.98q4
320:
1.193 brouard 321: Revision 1.192 2015/07/16 16:49:02 brouard
322: Summary: Fixing some outputs
323:
1.192 brouard 324: Revision 1.191 2015/07/14 10:00:33 brouard
325: Summary: Some fixes
326:
1.191 brouard 327: Revision 1.190 2015/05/05 08:51:13 brouard
328: Summary: Adding digits in output parameters (7 digits instead of 6)
329:
330: Fix 1+age+.
331:
1.190 brouard 332: Revision 1.189 2015/04/30 14:45:16 brouard
333: Summary: 0.98q2
334:
1.189 brouard 335: Revision 1.188 2015/04/30 08:27:53 brouard
336: *** empty log message ***
337:
1.188 brouard 338: Revision 1.187 2015/04/29 09:11:15 brouard
339: *** empty log message ***
340:
1.187 brouard 341: Revision 1.186 2015/04/23 12:01:52 brouard
342: Summary: V1*age is working now, version 0.98q1
343:
344: Some codes had been disabled in order to simplify and Vn*age was
345: working in the optimization phase, ie, giving correct MLE parameters,
346: but, as usual, outputs were not correct and program core dumped.
347:
1.186 brouard 348: Revision 1.185 2015/03/11 13:26:42 brouard
349: Summary: Inclusion of compile and links command line for Intel Compiler
350:
1.185 brouard 351: Revision 1.184 2015/03/11 11:52:39 brouard
352: Summary: Back from Windows 8. Intel Compiler
353:
1.184 brouard 354: Revision 1.183 2015/03/10 20:34:32 brouard
355: Summary: 0.98q0, trying with directest, mnbrak fixed
356:
357: We use directest instead of original Powell test; probably no
358: incidence on the results, but better justifications;
359: We fixed Numerical Recipes mnbrak routine which was wrong and gave
360: wrong results.
361:
1.183 brouard 362: Revision 1.182 2015/02/12 08:19:57 brouard
363: Summary: Trying to keep directest which seems simpler and more general
364: Author: Nicolas Brouard
365:
1.182 brouard 366: Revision 1.181 2015/02/11 23:22:24 brouard
367: Summary: Comments on Powell added
368:
369: Author:
370:
1.181 brouard 371: Revision 1.180 2015/02/11 17:33:45 brouard
372: Summary: Finishing move from main to function (hpijx and prevalence_limit)
373:
1.180 brouard 374: Revision 1.179 2015/01/04 09:57:06 brouard
375: Summary: back to OS/X
376:
1.179 brouard 377: Revision 1.178 2015/01/04 09:35:48 brouard
378: *** empty log message ***
379:
1.178 brouard 380: Revision 1.177 2015/01/03 18:40:56 brouard
381: Summary: Still testing ilc32 on OSX
382:
1.177 brouard 383: Revision 1.176 2015/01/03 16:45:04 brouard
384: *** empty log message ***
385:
1.176 brouard 386: Revision 1.175 2015/01/03 16:33:42 brouard
387: *** empty log message ***
388:
1.175 brouard 389: Revision 1.174 2015/01/03 16:15:49 brouard
390: Summary: Still in cross-compilation
391:
1.174 brouard 392: Revision 1.173 2015/01/03 12:06:26 brouard
393: Summary: trying to detect cross-compilation
394:
1.173 brouard 395: Revision 1.172 2014/12/27 12:07:47 brouard
396: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
397:
1.172 brouard 398: Revision 1.171 2014/12/23 13:26:59 brouard
399: Summary: Back from Visual C
400:
401: Still problem with utsname.h on Windows
402:
1.171 brouard 403: Revision 1.170 2014/12/23 11:17:12 brouard
404: Summary: Cleaning some \%% back to %%
405:
406: The escape was mandatory for a specific compiler (which one?), but too many warnings.
407:
1.170 brouard 408: Revision 1.169 2014/12/22 23:08:31 brouard
409: Summary: 0.98p
410:
411: Outputs some informations on compiler used, OS etc. Testing on different platforms.
412:
1.169 brouard 413: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 414: Summary: update
1.169 brouard 415:
1.168 brouard 416: Revision 1.167 2014/12/22 13:50:56 brouard
417: Summary: Testing uname and compiler version and if compiled 32 or 64
418:
419: Testing on Linux 64
420:
1.167 brouard 421: Revision 1.166 2014/12/22 11:40:47 brouard
422: *** empty log message ***
423:
1.166 brouard 424: Revision 1.165 2014/12/16 11:20:36 brouard
425: Summary: After compiling on Visual C
426:
427: * imach.c (Module): Merging 1.61 to 1.162
428:
1.165 brouard 429: Revision 1.164 2014/12/16 10:52:11 brouard
430: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
431:
432: * imach.c (Module): Merging 1.61 to 1.162
433:
1.164 brouard 434: Revision 1.163 2014/12/16 10:30:11 brouard
435: * imach.c (Module): Merging 1.61 to 1.162
436:
1.163 brouard 437: Revision 1.162 2014/09/25 11:43:39 brouard
438: Summary: temporary backup 0.99!
439:
1.162 brouard 440: Revision 1.1 2014/09/16 11:06:58 brouard
441: Summary: With some code (wrong) for nlopt
442:
443: Author:
444:
445: Revision 1.161 2014/09/15 20:41:41 brouard
446: Summary: Problem with macro SQR on Intel compiler
447:
1.161 brouard 448: Revision 1.160 2014/09/02 09:24:05 brouard
449: *** empty log message ***
450:
1.160 brouard 451: Revision 1.159 2014/09/01 10:34:10 brouard
452: Summary: WIN32
453: Author: Brouard
454:
1.159 brouard 455: Revision 1.158 2014/08/27 17:11:51 brouard
456: *** empty log message ***
457:
1.158 brouard 458: Revision 1.157 2014/08/27 16:26:55 brouard
459: Summary: Preparing windows Visual studio version
460: Author: Brouard
461:
462: In order to compile on Visual studio, time.h is now correct and time_t
463: and tm struct should be used. difftime should be used but sometimes I
464: just make the differences in raw time format (time(&now).
465: Trying to suppress #ifdef LINUX
466: Add xdg-open for __linux in order to open default browser.
467:
1.157 brouard 468: Revision 1.156 2014/08/25 20:10:10 brouard
469: *** empty log message ***
470:
1.156 brouard 471: Revision 1.155 2014/08/25 18:32:34 brouard
472: Summary: New compile, minor changes
473: Author: Brouard
474:
1.155 brouard 475: Revision 1.154 2014/06/20 17:32:08 brouard
476: Summary: Outputs now all graphs of convergence to period prevalence
477:
1.154 brouard 478: Revision 1.153 2014/06/20 16:45:46 brouard
479: Summary: If 3 live state, convergence to period prevalence on same graph
480: Author: Brouard
481:
1.153 brouard 482: Revision 1.152 2014/06/18 17:54:09 brouard
483: Summary: open browser, use gnuplot on same dir than imach if not found in the path
484:
1.152 brouard 485: Revision 1.151 2014/06/18 16:43:30 brouard
486: *** empty log message ***
487:
1.151 brouard 488: Revision 1.150 2014/06/18 16:42:35 brouard
489: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
490: Author: brouard
491:
1.150 brouard 492: Revision 1.149 2014/06/18 15:51:14 brouard
493: Summary: Some fixes in parameter files errors
494: Author: Nicolas Brouard
495:
1.149 brouard 496: Revision 1.148 2014/06/17 17:38:48 brouard
497: Summary: Nothing new
498: Author: Brouard
499:
500: Just a new packaging for OS/X version 0.98nS
501:
1.148 brouard 502: Revision 1.147 2014/06/16 10:33:11 brouard
503: *** empty log message ***
504:
1.147 brouard 505: Revision 1.146 2014/06/16 10:20:28 brouard
506: Summary: Merge
507: Author: Brouard
508:
509: Merge, before building revised version.
510:
1.146 brouard 511: Revision 1.145 2014/06/10 21:23:15 brouard
512: Summary: Debugging with valgrind
513: Author: Nicolas Brouard
514:
515: Lot of changes in order to output the results with some covariates
516: After the Edimburgh REVES conference 2014, it seems mandatory to
517: improve the code.
518: No more memory valgrind error but a lot has to be done in order to
519: continue the work of splitting the code into subroutines.
520: Also, decodemodel has been improved. Tricode is still not
521: optimal. nbcode should be improved. Documentation has been added in
522: the source code.
523:
1.144 brouard 524: Revision 1.143 2014/01/26 09:45:38 brouard
525: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
526:
527: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
528: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
529:
1.143 brouard 530: Revision 1.142 2014/01/26 03:57:36 brouard
531: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
532:
533: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
534:
1.142 brouard 535: Revision 1.141 2014/01/26 02:42:01 brouard
536: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
537:
1.141 brouard 538: Revision 1.140 2011/09/02 10:37:54 brouard
539: Summary: times.h is ok with mingw32 now.
540:
1.140 brouard 541: Revision 1.139 2010/06/14 07:50:17 brouard
542: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
543: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
544:
1.139 brouard 545: Revision 1.138 2010/04/30 18:19:40 brouard
546: *** empty log message ***
547:
1.138 brouard 548: Revision 1.137 2010/04/29 18:11:38 brouard
549: (Module): Checking covariates for more complex models
550: than V1+V2. A lot of change to be done. Unstable.
551:
1.137 brouard 552: Revision 1.136 2010/04/26 20:30:53 brouard
553: (Module): merging some libgsl code. Fixing computation
554: of likelione (using inter/intrapolation if mle = 0) in order to
555: get same likelihood as if mle=1.
556: Some cleaning of code and comments added.
557:
1.136 brouard 558: Revision 1.135 2009/10/29 15:33:14 brouard
559: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
560:
1.135 brouard 561: Revision 1.134 2009/10/29 13:18:53 brouard
562: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
563:
1.134 brouard 564: Revision 1.133 2009/07/06 10:21:25 brouard
565: just nforces
566:
1.133 brouard 567: Revision 1.132 2009/07/06 08:22:05 brouard
568: Many tings
569:
1.132 brouard 570: Revision 1.131 2009/06/20 16:22:47 brouard
571: Some dimensions resccaled
572:
1.131 brouard 573: Revision 1.130 2009/05/26 06:44:34 brouard
574: (Module): Max Covariate is now set to 20 instead of 8. A
575: lot of cleaning with variables initialized to 0. Trying to make
576: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
577:
1.130 brouard 578: Revision 1.129 2007/08/31 13:49:27 lievre
579: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
580:
1.129 lievre 581: Revision 1.128 2006/06/30 13:02:05 brouard
582: (Module): Clarifications on computing e.j
583:
1.128 brouard 584: Revision 1.127 2006/04/28 18:11:50 brouard
585: (Module): Yes the sum of survivors was wrong since
586: imach-114 because nhstepm was no more computed in the age
587: loop. Now we define nhstepma in the age loop.
588: (Module): In order to speed up (in case of numerous covariates) we
589: compute health expectancies (without variances) in a first step
590: and then all the health expectancies with variances or standard
591: deviation (needs data from the Hessian matrices) which slows the
592: computation.
593: In the future we should be able to stop the program is only health
594: expectancies and graph are needed without standard deviations.
595:
1.127 brouard 596: Revision 1.126 2006/04/28 17:23:28 brouard
597: (Module): Yes the sum of survivors was wrong since
598: imach-114 because nhstepm was no more computed in the age
599: loop. Now we define nhstepma in the age loop.
600: Version 0.98h
601:
1.126 brouard 602: Revision 1.125 2006/04/04 15:20:31 lievre
603: Errors in calculation of health expectancies. Age was not initialized.
604: Forecasting file added.
605:
606: Revision 1.124 2006/03/22 17:13:53 lievre
607: Parameters are printed with %lf instead of %f (more numbers after the comma).
608: The log-likelihood is printed in the log file
609:
610: Revision 1.123 2006/03/20 10:52:43 brouard
611: * imach.c (Module): <title> changed, corresponds to .htm file
612: name. <head> headers where missing.
613:
614: * imach.c (Module): Weights can have a decimal point as for
615: English (a comma might work with a correct LC_NUMERIC environment,
616: otherwise the weight is truncated).
617: Modification of warning when the covariates values are not 0 or
618: 1.
619: Version 0.98g
620:
621: Revision 1.122 2006/03/20 09:45:41 brouard
622: (Module): Weights can have a decimal point as for
623: English (a comma might work with a correct LC_NUMERIC environment,
624: otherwise the weight is truncated).
625: Modification of warning when the covariates values are not 0 or
626: 1.
627: Version 0.98g
628:
629: Revision 1.121 2006/03/16 17:45:01 lievre
630: * imach.c (Module): Comments concerning covariates added
631:
632: * imach.c (Module): refinements in the computation of lli if
633: status=-2 in order to have more reliable computation if stepm is
634: not 1 month. Version 0.98f
635:
636: Revision 1.120 2006/03/16 15:10:38 lievre
637: (Module): refinements in the computation of lli if
638: status=-2 in order to have more reliable computation if stepm is
639: not 1 month. Version 0.98f
640:
641: Revision 1.119 2006/03/15 17:42:26 brouard
642: (Module): Bug if status = -2, the loglikelihood was
643: computed as likelihood omitting the logarithm. Version O.98e
644:
645: Revision 1.118 2006/03/14 18:20:07 brouard
646: (Module): varevsij Comments added explaining the second
647: table of variances if popbased=1 .
648: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
649: (Module): Function pstamp added
650: (Module): Version 0.98d
651:
652: Revision 1.117 2006/03/14 17:16:22 brouard
653: (Module): varevsij Comments added explaining the second
654: table of variances if popbased=1 .
655: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
656: (Module): Function pstamp added
657: (Module): Version 0.98d
658:
659: Revision 1.116 2006/03/06 10:29:27 brouard
660: (Module): Variance-covariance wrong links and
661: varian-covariance of ej. is needed (Saito).
662:
663: Revision 1.115 2006/02/27 12:17:45 brouard
664: (Module): One freematrix added in mlikeli! 0.98c
665:
666: Revision 1.114 2006/02/26 12:57:58 brouard
667: (Module): Some improvements in processing parameter
668: filename with strsep.
669:
670: Revision 1.113 2006/02/24 14:20:24 brouard
671: (Module): Memory leaks checks with valgrind and:
672: datafile was not closed, some imatrix were not freed and on matrix
673: allocation too.
674:
675: Revision 1.112 2006/01/30 09:55:26 brouard
676: (Module): Back to gnuplot.exe instead of wgnuplot.exe
677:
678: Revision 1.111 2006/01/25 20:38:18 brouard
679: (Module): Lots of cleaning and bugs added (Gompertz)
680: (Module): Comments can be added in data file. Missing date values
681: can be a simple dot '.'.
682:
683: Revision 1.110 2006/01/25 00:51:50 brouard
684: (Module): Lots of cleaning and bugs added (Gompertz)
685:
686: Revision 1.109 2006/01/24 19:37:15 brouard
687: (Module): Comments (lines starting with a #) are allowed in data.
688:
689: Revision 1.108 2006/01/19 18:05:42 lievre
690: Gnuplot problem appeared...
691: To be fixed
692:
693: Revision 1.107 2006/01/19 16:20:37 brouard
694: Test existence of gnuplot in imach path
695:
696: Revision 1.106 2006/01/19 13:24:36 brouard
697: Some cleaning and links added in html output
698:
699: Revision 1.105 2006/01/05 20:23:19 lievre
700: *** empty log message ***
701:
702: Revision 1.104 2005/09/30 16:11:43 lievre
703: (Module): sump fixed, loop imx fixed, and simplifications.
704: (Module): If the status is missing at the last wave but we know
705: that the person is alive, then we can code his/her status as -2
706: (instead of missing=-1 in earlier versions) and his/her
707: contributions to the likelihood is 1 - Prob of dying from last
708: health status (= 1-p13= p11+p12 in the easiest case of somebody in
709: the healthy state at last known wave). Version is 0.98
710:
711: Revision 1.103 2005/09/30 15:54:49 lievre
712: (Module): sump fixed, loop imx fixed, and simplifications.
713:
714: Revision 1.102 2004/09/15 17:31:30 brouard
715: Add the possibility to read data file including tab characters.
716:
717: Revision 1.101 2004/09/15 10:38:38 brouard
718: Fix on curr_time
719:
720: Revision 1.100 2004/07/12 18:29:06 brouard
721: Add version for Mac OS X. Just define UNIX in Makefile
722:
723: Revision 1.99 2004/06/05 08:57:40 brouard
724: *** empty log message ***
725:
726: Revision 1.98 2004/05/16 15:05:56 brouard
727: New version 0.97 . First attempt to estimate force of mortality
728: directly from the data i.e. without the need of knowing the health
729: state at each age, but using a Gompertz model: log u =a + b*age .
730: This is the basic analysis of mortality and should be done before any
731: other analysis, in order to test if the mortality estimated from the
732: cross-longitudinal survey is different from the mortality estimated
733: from other sources like vital statistic data.
734:
735: The same imach parameter file can be used but the option for mle should be -3.
736:
1.133 brouard 737: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 738: former routines in order to include the new code within the former code.
739:
740: The output is very simple: only an estimate of the intercept and of
741: the slope with 95% confident intervals.
742:
743: Current limitations:
744: A) Even if you enter covariates, i.e. with the
745: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
746: B) There is no computation of Life Expectancy nor Life Table.
747:
748: Revision 1.97 2004/02/20 13:25:42 lievre
749: Version 0.96d. Population forecasting command line is (temporarily)
750: suppressed.
751:
752: Revision 1.96 2003/07/15 15:38:55 brouard
753: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
754: rewritten within the same printf. Workaround: many printfs.
755:
756: Revision 1.95 2003/07/08 07:54:34 brouard
757: * imach.c (Repository):
758: (Repository): Using imachwizard code to output a more meaningful covariance
759: matrix (cov(a12,c31) instead of numbers.
760:
761: Revision 1.94 2003/06/27 13:00:02 brouard
762: Just cleaning
763:
764: Revision 1.93 2003/06/25 16:33:55 brouard
765: (Module): On windows (cygwin) function asctime_r doesn't
766: exist so I changed back to asctime which exists.
767: (Module): Version 0.96b
768:
769: Revision 1.92 2003/06/25 16:30:45 brouard
770: (Module): On windows (cygwin) function asctime_r doesn't
771: exist so I changed back to asctime which exists.
772:
773: Revision 1.91 2003/06/25 15:30:29 brouard
774: * imach.c (Repository): Duplicated warning errors corrected.
775: (Repository): Elapsed time after each iteration is now output. It
776: helps to forecast when convergence will be reached. Elapsed time
777: is stamped in powell. We created a new html file for the graphs
778: concerning matrix of covariance. It has extension -cov.htm.
779:
780: Revision 1.90 2003/06/24 12:34:15 brouard
781: (Module): Some bugs corrected for windows. Also, when
782: mle=-1 a template is output in file "or"mypar.txt with the design
783: of the covariance matrix to be input.
784:
785: Revision 1.89 2003/06/24 12:30:52 brouard
786: (Module): Some bugs corrected for windows. Also, when
787: mle=-1 a template is output in file "or"mypar.txt with the design
788: of the covariance matrix to be input.
789:
790: Revision 1.88 2003/06/23 17:54:56 brouard
791: * 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.
792:
793: Revision 1.87 2003/06/18 12:26:01 brouard
794: Version 0.96
795:
796: Revision 1.86 2003/06/17 20:04:08 brouard
797: (Module): Change position of html and gnuplot routines and added
798: routine fileappend.
799:
800: Revision 1.85 2003/06/17 13:12:43 brouard
801: * imach.c (Repository): Check when date of death was earlier that
802: current date of interview. It may happen when the death was just
803: prior to the death. In this case, dh was negative and likelihood
804: was wrong (infinity). We still send an "Error" but patch by
805: assuming that the date of death was just one stepm after the
806: interview.
807: (Repository): Because some people have very long ID (first column)
808: we changed int to long in num[] and we added a new lvector for
809: memory allocation. But we also truncated to 8 characters (left
810: truncation)
811: (Repository): No more line truncation errors.
812:
813: Revision 1.84 2003/06/13 21:44:43 brouard
814: * imach.c (Repository): Replace "freqsummary" at a correct
815: place. It differs from routine "prevalence" which may be called
816: many times. Probs is memory consuming and must be used with
817: parcimony.
818: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
819:
820: Revision 1.83 2003/06/10 13:39:11 lievre
821: *** empty log message ***
822:
823: Revision 1.82 2003/06/05 15:57:20 brouard
824: Add log in imach.c and fullversion number is now printed.
825:
826: */
827: /*
828: Interpolated Markov Chain
829:
830: Short summary of the programme:
831:
1.227 brouard 832: This program computes Healthy Life Expectancies or State-specific
833: (if states aren't health statuses) Expectancies from
834: cross-longitudinal data. Cross-longitudinal data consist in:
835:
836: -1- a first survey ("cross") where individuals from different ages
837: are interviewed on their health status or degree of disability (in
838: the case of a health survey which is our main interest)
839:
840: -2- at least a second wave of interviews ("longitudinal") which
841: measure each change (if any) in individual health status. Health
842: expectancies are computed from the time spent in each health state
843: according to a model. More health states you consider, more time is
844: necessary to reach the Maximum Likelihood of the parameters involved
845: in the model. The simplest model is the multinomial logistic model
846: where pij is the probability to be observed in state j at the second
847: wave conditional to be observed in state i at the first
848: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
849: etc , where 'age' is age and 'sex' is a covariate. If you want to
850: have a more complex model than "constant and age", you should modify
851: the program where the markup *Covariates have to be included here
852: again* invites you to do it. More covariates you add, slower the
1.126 brouard 853: convergence.
854:
855: The advantage of this computer programme, compared to a simple
856: multinomial logistic model, is clear when the delay between waves is not
857: identical for each individual. Also, if a individual missed an
858: intermediate interview, the information is lost, but taken into
859: account using an interpolation or extrapolation.
860:
861: hPijx is the probability to be observed in state i at age x+h
862: conditional to the observed state i at age x. The delay 'h' can be
863: split into an exact number (nh*stepm) of unobserved intermediate
864: states. This elementary transition (by month, quarter,
865: semester or year) is modelled as a multinomial logistic. The hPx
866: matrix is simply the matrix product of nh*stepm elementary matrices
867: and the contribution of each individual to the likelihood is simply
868: hPijx.
869:
870: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 871: of the life expectancies. It also computes the period (stable) prevalence.
872:
873: Back prevalence and projections:
1.227 brouard 874:
875: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
876: double agemaxpar, double ftolpl, int *ncvyearp, double
877: dateprev1,double dateprev2, int firstpass, int lastpass, int
878: mobilavproj)
879:
880: Computes the back prevalence limit for any combination of
881: covariate values k at any age between ageminpar and agemaxpar and
882: returns it in **bprlim. In the loops,
883:
884: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
885: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
886:
887: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 888: Computes for any combination of covariates k and any age between bage and fage
889: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
890: oldm=oldms;savm=savms;
1.227 brouard 891:
1.267 brouard 892: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 893: Computes the transition matrix starting at age 'age' over
894: 'nhstepm*hstepm*stepm' months (i.e. until
895: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 896: nhstepm*hstepm matrices.
897:
898: Returns p3mat[i][j][h] after calling
899: p3mat[i][j][h]=matprod2(newm,
900: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
901: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
902: oldm);
1.226 brouard 903:
904: Important routines
905:
906: - func (or funcone), computes logit (pij) distinguishing
907: o fixed variables (single or product dummies or quantitative);
908: o varying variables by:
909: (1) wave (single, product dummies, quantitative),
910: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
911: % fixed dummy (treated) or quantitative (not done because time-consuming);
912: % varying dummy (not done) or quantitative (not done);
913: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
914: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
915: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
916: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
917: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 918:
1.226 brouard 919:
920:
1.133 brouard 921: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
922: Institut national d'études démographiques, Paris.
1.126 brouard 923: This software have been partly granted by Euro-REVES, a concerted action
924: from the European Union.
925: It is copyrighted identically to a GNU software product, ie programme and
926: software can be distributed freely for non commercial use. Latest version
927: can be accessed at http://euroreves.ined.fr/imach .
928:
929: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
930: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
931:
932: **********************************************************************/
933: /*
934: main
935: read parameterfile
936: read datafile
937: concatwav
938: freqsummary
939: if (mle >= 1)
940: mlikeli
941: print results files
942: if mle==1
943: computes hessian
944: read end of parameter file: agemin, agemax, bage, fage, estepm
945: begin-prev-date,...
946: open gnuplot file
947: open html file
1.145 brouard 948: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
949: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
950: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
951: freexexit2 possible for memory heap.
952:
953: h Pij x | pij_nom ficrestpij
954: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
955: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
956: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
957:
958: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
959: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
960: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
961: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
962: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
963:
1.126 brouard 964: forecasting if prevfcast==1 prevforecast call prevalence()
965: health expectancies
966: Variance-covariance of DFLE
967: prevalence()
968: movingaverage()
969: varevsij()
970: if popbased==1 varevsij(,popbased)
971: total life expectancies
972: Variance of period (stable) prevalence
973: end
974: */
975:
1.187 brouard 976: /* #define DEBUG */
977: /* #define DEBUGBRENT */
1.203 brouard 978: /* #define DEBUGLINMIN */
979: /* #define DEBUGHESS */
980: #define DEBUGHESSIJ
1.224 brouard 981: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 982: #define POWELL /* Instead of NLOPT */
1.224 brouard 983: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 984: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
985: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 986:
987: #include <math.h>
988: #include <stdio.h>
989: #include <stdlib.h>
990: #include <string.h>
1.226 brouard 991: #include <ctype.h>
1.159 brouard 992:
993: #ifdef _WIN32
994: #include <io.h>
1.172 brouard 995: #include <windows.h>
996: #include <tchar.h>
1.159 brouard 997: #else
1.126 brouard 998: #include <unistd.h>
1.159 brouard 999: #endif
1.126 brouard 1000:
1001: #include <limits.h>
1002: #include <sys/types.h>
1.171 brouard 1003:
1004: #if defined(__GNUC__)
1005: #include <sys/utsname.h> /* Doesn't work on Windows */
1006: #endif
1007:
1.126 brouard 1008: #include <sys/stat.h>
1009: #include <errno.h>
1.159 brouard 1010: /* extern int errno; */
1.126 brouard 1011:
1.157 brouard 1012: /* #ifdef LINUX */
1013: /* #include <time.h> */
1014: /* #include "timeval.h" */
1015: /* #else */
1016: /* #include <sys/time.h> */
1017: /* #endif */
1018:
1.126 brouard 1019: #include <time.h>
1020:
1.136 brouard 1021: #ifdef GSL
1022: #include <gsl/gsl_errno.h>
1023: #include <gsl/gsl_multimin.h>
1024: #endif
1025:
1.167 brouard 1026:
1.162 brouard 1027: #ifdef NLOPT
1028: #include <nlopt.h>
1029: typedef struct {
1030: double (* function)(double [] );
1031: } myfunc_data ;
1032: #endif
1033:
1.126 brouard 1034: /* #include <libintl.h> */
1035: /* #define _(String) gettext (String) */
1036:
1.251 brouard 1037: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1038:
1039: #define GNUPLOTPROGRAM "gnuplot"
1040: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1041: #define FILENAMELENGTH 132
1042:
1043: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1044: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1045:
1.144 brouard 1046: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1047: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1048:
1049: #define NINTERVMAX 8
1.144 brouard 1050: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1051: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.290 ! brouard 1052: /* #define NCOVMAX 20 */ /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 1053: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1054: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1055: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 ! brouard 1056: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1057: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1058: /* #define AGESUP 130 */
1.288 brouard 1059: /* #define AGESUP 150 */
1060: #define AGESUP 200
1.268 brouard 1061: #define AGEINF 0
1.218 brouard 1062: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1063: #define AGEBASE 40
1.194 brouard 1064: #define AGEOVERFLOW 1.e20
1.164 brouard 1065: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1066: #ifdef _WIN32
1067: #define DIRSEPARATOR '\\'
1068: #define CHARSEPARATOR "\\"
1069: #define ODIRSEPARATOR '/'
1070: #else
1.126 brouard 1071: #define DIRSEPARATOR '/'
1072: #define CHARSEPARATOR "/"
1073: #define ODIRSEPARATOR '\\'
1074: #endif
1075:
1.290 ! brouard 1076: /* $Id: imach.c,v 1.289 2018/12/13 09:16:26 brouard Exp $ */
1.126 brouard 1077: /* $State: Exp $ */
1.196 brouard 1078: #include "version.h"
1079: char version[]=__IMACH_VERSION__;
1.283 brouard 1080: char copyright[]="April 2018,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2018";
1.290 ! brouard 1081: char fullversion[]="$Revision: 1.289 $ $Date: 2018/12/13 09:16:26 $";
1.126 brouard 1082: char strstart[80];
1083: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1084: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1085: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1086: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1087: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1088: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1089: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1090: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1091: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1092: int cptcovprodnoage=0; /**< Number of covariate products without age */
1093: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1094: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1095: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1096: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1097: int nsd=0; /**< Total number of single dummy variables (output) */
1098: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1099: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1100: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1101: int ntveff=0; /**< ntveff number of effective time varying variables */
1102: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1103: int cptcov=0; /* Working variable */
1.290 ! brouard 1104: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1105: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 1106: int npar=NPARMAX;
1107: int nlstate=2; /* Number of live states */
1108: int ndeath=1; /* Number of dead states */
1.130 brouard 1109: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1110: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1111: int popbased=0;
1112:
1113: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1114: int maxwav=0; /* Maxim number of waves */
1115: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1116: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1117: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1118: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1119: int mle=1, weightopt=0;
1.126 brouard 1120: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1121: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1122: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1123: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1124: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1125: int selected(int kvar); /* Is covariate kvar selected for printing results */
1126:
1.130 brouard 1127: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1128: double **matprod2(); /* test */
1.126 brouard 1129: double **oldm, **newm, **savm; /* Working pointers to matrices */
1130: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1131: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1132:
1.136 brouard 1133: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1134: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1135: FILE *ficlog, *ficrespow;
1.130 brouard 1136: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1137: double fretone; /* Only one call to likelihood */
1.130 brouard 1138: long ipmx=0; /* Number of contributions */
1.126 brouard 1139: double sw; /* Sum of weights */
1140: char filerespow[FILENAMELENGTH];
1141: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1142: FILE *ficresilk;
1143: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1144: FILE *ficresprobmorprev;
1145: FILE *fichtm, *fichtmcov; /* Html File */
1146: FILE *ficreseij;
1147: char filerese[FILENAMELENGTH];
1148: FILE *ficresstdeij;
1149: char fileresstde[FILENAMELENGTH];
1150: FILE *ficrescveij;
1151: char filerescve[FILENAMELENGTH];
1152: FILE *ficresvij;
1153: char fileresv[FILENAMELENGTH];
1.269 brouard 1154:
1.126 brouard 1155: char title[MAXLINE];
1.234 brouard 1156: char model[MAXLINE]; /**< The model line */
1.217 brouard 1157: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1158: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1159: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1160: char command[FILENAMELENGTH];
1161: int outcmd=0;
1162:
1.217 brouard 1163: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1164: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1165: char filelog[FILENAMELENGTH]; /* Log file */
1166: char filerest[FILENAMELENGTH];
1167: char fileregp[FILENAMELENGTH];
1168: char popfile[FILENAMELENGTH];
1169:
1170: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1171:
1.157 brouard 1172: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1173: /* struct timezone tzp; */
1174: /* extern int gettimeofday(); */
1175: struct tm tml, *gmtime(), *localtime();
1176:
1177: extern time_t time();
1178:
1179: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1180: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1181: struct tm tm;
1182:
1.126 brouard 1183: char strcurr[80], strfor[80];
1184:
1185: char *endptr;
1186: long lval;
1187: double dval;
1188:
1189: #define NR_END 1
1190: #define FREE_ARG char*
1191: #define FTOL 1.0e-10
1192:
1193: #define NRANSI
1.240 brouard 1194: #define ITMAX 200
1195: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1196:
1197: #define TOL 2.0e-4
1198:
1199: #define CGOLD 0.3819660
1200: #define ZEPS 1.0e-10
1201: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1202:
1203: #define GOLD 1.618034
1204: #define GLIMIT 100.0
1205: #define TINY 1.0e-20
1206:
1207: static double maxarg1,maxarg2;
1208: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1209: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1210:
1211: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1212: #define rint(a) floor(a+0.5)
1.166 brouard 1213: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1214: #define mytinydouble 1.0e-16
1.166 brouard 1215: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1216: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1217: /* static double dsqrarg; */
1218: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1219: static double sqrarg;
1220: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1221: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1222: int agegomp= AGEGOMP;
1223:
1224: int imx;
1225: int stepm=1;
1226: /* Stepm, step in month: minimum step interpolation*/
1227:
1228: int estepm;
1229: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1230:
1231: int m,nb;
1232: long *num;
1.197 brouard 1233: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1234: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1235: covariate for which somebody answered excluding
1236: undefined. Usually 2: 0 and 1. */
1237: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1238: covariate for which somebody answered including
1239: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1240: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1241: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1242: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1243: double *ageexmed,*agecens;
1244: double dateintmean=0;
1245:
1246: double *weight;
1247: int **s; /* Status */
1.141 brouard 1248: double *agedc;
1.145 brouard 1249: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1250: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1251: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1252: double **coqvar; /* Fixed quantitative covariate nqv */
1253: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1254: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1255: double idx;
1256: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1257: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1258: /*k 1 2 3 4 5 6 7 8 9 */
1259: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1260: /* Tndvar[k] 1 2 3 4 5 */
1261: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1262: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1263: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1264: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1265: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1266: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1267: /* Tprod[i]=k 4 7 */
1268: /* Tage[i]=k 5 8 */
1269: /* */
1270: /* Type */
1271: /* V 1 2 3 4 5 */
1272: /* F F V V V */
1273: /* D Q D D Q */
1274: /* */
1275: int *TvarsD;
1276: int *TvarsDind;
1277: int *TvarsQ;
1278: int *TvarsQind;
1279:
1.235 brouard 1280: #define MAXRESULTLINES 10
1281: int nresult=0;
1.258 brouard 1282: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1283: int TKresult[MAXRESULTLINES];
1.237 brouard 1284: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1285: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1286: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1287: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1288: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1289: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1290:
1.234 brouard 1291: /* 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 1292: 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 */
1293: 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 */
1294: 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 */
1295: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1296: 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 */
1297: 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 1298: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1299: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1300: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1301: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1302: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1303: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1304: 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 */
1305: 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 */
1306:
1.230 brouard 1307: int *Tvarsel; /**< Selected covariates for output */
1308: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1309: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1310: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1311: 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 1312: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1313: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1314: int *Tage;
1.227 brouard 1315: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1316: 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 1317: 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*/
1318: 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 1319: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1320: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1321: int **Tvard;
1322: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1323: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1324: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1325: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1326: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1327: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1328: double *lsurv, *lpop, *tpop;
1329:
1.231 brouard 1330: #define FD 1; /* Fixed dummy covariate */
1331: #define FQ 2; /* Fixed quantitative covariate */
1332: #define FP 3; /* Fixed product covariate */
1333: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1334: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1335: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1336: #define VD 10; /* Varying dummy covariate */
1337: #define VQ 11; /* Varying quantitative covariate */
1338: #define VP 12; /* Varying product covariate */
1339: #define VPDD 13; /* Varying product dummy*dummy covariate */
1340: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1341: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1342: #define APFD 16; /* Age product * fixed dummy covariate */
1343: #define APFQ 17; /* Age product * fixed quantitative covariate */
1344: #define APVD 18; /* Age product * varying dummy covariate */
1345: #define APVQ 19; /* Age product * varying quantitative covariate */
1346:
1347: #define FTYPE 1; /* Fixed covariate */
1348: #define VTYPE 2; /* Varying covariate (loop in wave) */
1349: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1350:
1351: struct kmodel{
1352: int maintype; /* main type */
1353: int subtype; /* subtype */
1354: };
1355: struct kmodel modell[NCOVMAX];
1356:
1.143 brouard 1357: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1358: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1359:
1360: /**************** split *************************/
1361: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1362: {
1363: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1364: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1365: */
1366: char *ss; /* pointer */
1.186 brouard 1367: int l1=0, l2=0; /* length counters */
1.126 brouard 1368:
1369: l1 = strlen(path ); /* length of path */
1370: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1371: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1372: if ( ss == NULL ) { /* no directory, so determine current directory */
1373: strcpy( name, path ); /* we got the fullname name because no directory */
1374: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1375: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1376: /* get current working directory */
1377: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1378: #ifdef WIN32
1379: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1380: #else
1381: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1382: #endif
1.126 brouard 1383: return( GLOCK_ERROR_GETCWD );
1384: }
1385: /* got dirc from getcwd*/
1386: printf(" DIRC = %s \n",dirc);
1.205 brouard 1387: } else { /* strip directory from path */
1.126 brouard 1388: ss++; /* after this, the filename */
1389: l2 = strlen( ss ); /* length of filename */
1390: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1391: strcpy( name, ss ); /* save file name */
1392: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1393: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1394: printf(" DIRC2 = %s \n",dirc);
1395: }
1396: /* We add a separator at the end of dirc if not exists */
1397: l1 = strlen( dirc ); /* length of directory */
1398: if( dirc[l1-1] != DIRSEPARATOR ){
1399: dirc[l1] = DIRSEPARATOR;
1400: dirc[l1+1] = 0;
1401: printf(" DIRC3 = %s \n",dirc);
1402: }
1403: ss = strrchr( name, '.' ); /* find last / */
1404: if (ss >0){
1405: ss++;
1406: strcpy(ext,ss); /* save extension */
1407: l1= strlen( name);
1408: l2= strlen(ss)+1;
1409: strncpy( finame, name, l1-l2);
1410: finame[l1-l2]= 0;
1411: }
1412:
1413: return( 0 ); /* we're done */
1414: }
1415:
1416:
1417: /******************************************/
1418:
1419: void replace_back_to_slash(char *s, char*t)
1420: {
1421: int i;
1422: int lg=0;
1423: i=0;
1424: lg=strlen(t);
1425: for(i=0; i<= lg; i++) {
1426: (s[i] = t[i]);
1427: if (t[i]== '\\') s[i]='/';
1428: }
1429: }
1430:
1.132 brouard 1431: char *trimbb(char *out, char *in)
1.137 brouard 1432: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1433: char *s;
1434: s=out;
1435: while (*in != '\0'){
1.137 brouard 1436: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1437: in++;
1438: }
1439: *out++ = *in++;
1440: }
1441: *out='\0';
1442: return s;
1443: }
1444:
1.187 brouard 1445: /* char *substrchaine(char *out, char *in, char *chain) */
1446: /* { */
1447: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1448: /* char *s, *t; */
1449: /* t=in;s=out; */
1450: /* while ((*in != *chain) && (*in != '\0')){ */
1451: /* *out++ = *in++; */
1452: /* } */
1453:
1454: /* /\* *in matches *chain *\/ */
1455: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1456: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1457: /* } */
1458: /* in--; chain--; */
1459: /* while ( (*in != '\0')){ */
1460: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1461: /* *out++ = *in++; */
1462: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1463: /* } */
1464: /* *out='\0'; */
1465: /* out=s; */
1466: /* return out; */
1467: /* } */
1468: char *substrchaine(char *out, char *in, char *chain)
1469: {
1470: /* Substract chain 'chain' from 'in', return and output 'out' */
1471: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1472:
1473: char *strloc;
1474:
1475: strcpy (out, in);
1476: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1477: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1478: if(strloc != NULL){
1479: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1480: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1481: /* strcpy (strloc, strloc +strlen(chain));*/
1482: }
1483: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1484: return out;
1485: }
1486:
1487:
1.145 brouard 1488: char *cutl(char *blocc, char *alocc, char *in, char occ)
1489: {
1.187 brouard 1490: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1491: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1492: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1493: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1494: */
1.160 brouard 1495: char *s, *t;
1.145 brouard 1496: t=in;s=in;
1497: while ((*in != occ) && (*in != '\0')){
1498: *alocc++ = *in++;
1499: }
1500: if( *in == occ){
1501: *(alocc)='\0';
1502: s=++in;
1503: }
1504:
1505: if (s == t) {/* occ not found */
1506: *(alocc-(in-s))='\0';
1507: in=s;
1508: }
1509: while ( *in != '\0'){
1510: *blocc++ = *in++;
1511: }
1512:
1513: *blocc='\0';
1514: return t;
1515: }
1.137 brouard 1516: char *cutv(char *blocc, char *alocc, char *in, char occ)
1517: {
1.187 brouard 1518: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1519: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1520: gives blocc="abcdef2ghi" and alocc="j".
1521: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1522: */
1523: char *s, *t;
1524: t=in;s=in;
1525: while (*in != '\0'){
1526: while( *in == occ){
1527: *blocc++ = *in++;
1528: s=in;
1529: }
1530: *blocc++ = *in++;
1531: }
1532: if (s == t) /* occ not found */
1533: *(blocc-(in-s))='\0';
1534: else
1535: *(blocc-(in-s)-1)='\0';
1536: in=s;
1537: while ( *in != '\0'){
1538: *alocc++ = *in++;
1539: }
1540:
1541: *alocc='\0';
1542: return s;
1543: }
1544:
1.126 brouard 1545: int nbocc(char *s, char occ)
1546: {
1547: int i,j=0;
1548: int lg=20;
1549: i=0;
1550: lg=strlen(s);
1551: for(i=0; i<= lg; i++) {
1.234 brouard 1552: if (s[i] == occ ) j++;
1.126 brouard 1553: }
1554: return j;
1555: }
1556:
1.137 brouard 1557: /* void cutv(char *u,char *v, char*t, char occ) */
1558: /* { */
1559: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1560: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1561: /* gives u="abcdef2ghi" and v="j" *\/ */
1562: /* int i,lg,j,p=0; */
1563: /* i=0; */
1564: /* lg=strlen(t); */
1565: /* for(j=0; j<=lg-1; j++) { */
1566: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1567: /* } */
1.126 brouard 1568:
1.137 brouard 1569: /* for(j=0; j<p; j++) { */
1570: /* (u[j] = t[j]); */
1571: /* } */
1572: /* u[p]='\0'; */
1.126 brouard 1573:
1.137 brouard 1574: /* for(j=0; j<= lg; j++) { */
1575: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1576: /* } */
1577: /* } */
1.126 brouard 1578:
1.160 brouard 1579: #ifdef _WIN32
1580: char * strsep(char **pp, const char *delim)
1581: {
1582: char *p, *q;
1583:
1584: if ((p = *pp) == NULL)
1585: return 0;
1586: if ((q = strpbrk (p, delim)) != NULL)
1587: {
1588: *pp = q + 1;
1589: *q = '\0';
1590: }
1591: else
1592: *pp = 0;
1593: return p;
1594: }
1595: #endif
1596:
1.126 brouard 1597: /********************** nrerror ********************/
1598:
1599: void nrerror(char error_text[])
1600: {
1601: fprintf(stderr,"ERREUR ...\n");
1602: fprintf(stderr,"%s\n",error_text);
1603: exit(EXIT_FAILURE);
1604: }
1605: /*********************** vector *******************/
1606: double *vector(int nl, int nh)
1607: {
1608: double *v;
1609: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1610: if (!v) nrerror("allocation failure in vector");
1611: return v-nl+NR_END;
1612: }
1613:
1614: /************************ free vector ******************/
1615: void free_vector(double*v, int nl, int nh)
1616: {
1617: free((FREE_ARG)(v+nl-NR_END));
1618: }
1619:
1620: /************************ivector *******************************/
1621: int *ivector(long nl,long nh)
1622: {
1623: int *v;
1624: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1625: if (!v) nrerror("allocation failure in ivector");
1626: return v-nl+NR_END;
1627: }
1628:
1629: /******************free ivector **************************/
1630: void free_ivector(int *v, long nl, long nh)
1631: {
1632: free((FREE_ARG)(v+nl-NR_END));
1633: }
1634:
1635: /************************lvector *******************************/
1636: long *lvector(long nl,long nh)
1637: {
1638: long *v;
1639: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1640: if (!v) nrerror("allocation failure in ivector");
1641: return v-nl+NR_END;
1642: }
1643:
1644: /******************free lvector **************************/
1645: void free_lvector(long *v, long nl, long nh)
1646: {
1647: free((FREE_ARG)(v+nl-NR_END));
1648: }
1649:
1650: /******************* imatrix *******************************/
1651: int **imatrix(long nrl, long nrh, long ncl, long nch)
1652: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1653: {
1654: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1655: int **m;
1656:
1657: /* allocate pointers to rows */
1658: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1659: if (!m) nrerror("allocation failure 1 in matrix()");
1660: m += NR_END;
1661: m -= nrl;
1662:
1663:
1664: /* allocate rows and set pointers to them */
1665: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1666: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1667: m[nrl] += NR_END;
1668: m[nrl] -= ncl;
1669:
1670: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1671:
1672: /* return pointer to array of pointers to rows */
1673: return m;
1674: }
1675:
1676: /****************** free_imatrix *************************/
1677: void free_imatrix(m,nrl,nrh,ncl,nch)
1678: int **m;
1679: long nch,ncl,nrh,nrl;
1680: /* free an int matrix allocated by imatrix() */
1681: {
1682: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1683: free((FREE_ARG) (m+nrl-NR_END));
1684: }
1685:
1686: /******************* matrix *******************************/
1687: double **matrix(long nrl, long nrh, long ncl, long nch)
1688: {
1689: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1690: double **m;
1691:
1692: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1693: if (!m) nrerror("allocation failure 1 in matrix()");
1694: m += NR_END;
1695: m -= nrl;
1696:
1697: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1698: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1699: m[nrl] += NR_END;
1700: m[nrl] -= ncl;
1701:
1702: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1703: return m;
1.145 brouard 1704: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1705: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1706: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1707: */
1708: }
1709:
1710: /*************************free matrix ************************/
1711: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1712: {
1713: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1714: free((FREE_ARG)(m+nrl-NR_END));
1715: }
1716:
1717: /******************* ma3x *******************************/
1718: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1719: {
1720: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1721: double ***m;
1722:
1723: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1724: if (!m) nrerror("allocation failure 1 in matrix()");
1725: m += NR_END;
1726: m -= nrl;
1727:
1728: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1729: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1730: m[nrl] += NR_END;
1731: m[nrl] -= ncl;
1732:
1733: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1734:
1735: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1736: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1737: m[nrl][ncl] += NR_END;
1738: m[nrl][ncl] -= nll;
1739: for (j=ncl+1; j<=nch; j++)
1740: m[nrl][j]=m[nrl][j-1]+nlay;
1741:
1742: for (i=nrl+1; i<=nrh; i++) {
1743: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1744: for (j=ncl+1; j<=nch; j++)
1745: m[i][j]=m[i][j-1]+nlay;
1746: }
1747: return m;
1748: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1749: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1750: */
1751: }
1752:
1753: /*************************free ma3x ************************/
1754: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1755: {
1756: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1757: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1758: free((FREE_ARG)(m+nrl-NR_END));
1759: }
1760:
1761: /*************** function subdirf ***********/
1762: char *subdirf(char fileres[])
1763: {
1764: /* Caution optionfilefiname is hidden */
1765: strcpy(tmpout,optionfilefiname);
1766: strcat(tmpout,"/"); /* Add to the right */
1767: strcat(tmpout,fileres);
1768: return tmpout;
1769: }
1770:
1771: /*************** function subdirf2 ***********/
1772: char *subdirf2(char fileres[], char *preop)
1773: {
1774:
1775: /* Caution optionfilefiname is hidden */
1776: strcpy(tmpout,optionfilefiname);
1777: strcat(tmpout,"/");
1778: strcat(tmpout,preop);
1779: strcat(tmpout,fileres);
1780: return tmpout;
1781: }
1782:
1783: /*************** function subdirf3 ***********/
1784: char *subdirf3(char fileres[], char *preop, char *preop2)
1785: {
1786:
1787: /* Caution optionfilefiname is hidden */
1788: strcpy(tmpout,optionfilefiname);
1789: strcat(tmpout,"/");
1790: strcat(tmpout,preop);
1791: strcat(tmpout,preop2);
1792: strcat(tmpout,fileres);
1793: return tmpout;
1794: }
1.213 brouard 1795:
1796: /*************** function subdirfext ***********/
1797: char *subdirfext(char fileres[], char *preop, char *postop)
1798: {
1799:
1800: strcpy(tmpout,preop);
1801: strcat(tmpout,fileres);
1802: strcat(tmpout,postop);
1803: return tmpout;
1804: }
1.126 brouard 1805:
1.213 brouard 1806: /*************** function subdirfext3 ***********/
1807: char *subdirfext3(char fileres[], char *preop, char *postop)
1808: {
1809:
1810: /* Caution optionfilefiname is hidden */
1811: strcpy(tmpout,optionfilefiname);
1812: strcat(tmpout,"/");
1813: strcat(tmpout,preop);
1814: strcat(tmpout,fileres);
1815: strcat(tmpout,postop);
1816: return tmpout;
1817: }
1818:
1.162 brouard 1819: char *asc_diff_time(long time_sec, char ascdiff[])
1820: {
1821: long sec_left, days, hours, minutes;
1822: days = (time_sec) / (60*60*24);
1823: sec_left = (time_sec) % (60*60*24);
1824: hours = (sec_left) / (60*60) ;
1825: sec_left = (sec_left) %(60*60);
1826: minutes = (sec_left) /60;
1827: sec_left = (sec_left) % (60);
1828: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1829: return ascdiff;
1830: }
1831:
1.126 brouard 1832: /***************** f1dim *************************/
1833: extern int ncom;
1834: extern double *pcom,*xicom;
1835: extern double (*nrfunc)(double []);
1836:
1837: double f1dim(double x)
1838: {
1839: int j;
1840: double f;
1841: double *xt;
1842:
1843: xt=vector(1,ncom);
1844: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1845: f=(*nrfunc)(xt);
1846: free_vector(xt,1,ncom);
1847: return f;
1848: }
1849:
1850: /*****************brent *************************/
1851: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1852: {
1853: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1854: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1855: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1856: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1857: * returned function value.
1858: */
1.126 brouard 1859: int iter;
1860: double a,b,d,etemp;
1.159 brouard 1861: double fu=0,fv,fw,fx;
1.164 brouard 1862: double ftemp=0.;
1.126 brouard 1863: double p,q,r,tol1,tol2,u,v,w,x,xm;
1864: double e=0.0;
1865:
1866: a=(ax < cx ? ax : cx);
1867: b=(ax > cx ? ax : cx);
1868: x=w=v=bx;
1869: fw=fv=fx=(*f)(x);
1870: for (iter=1;iter<=ITMAX;iter++) {
1871: xm=0.5*(a+b);
1872: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1873: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1874: printf(".");fflush(stdout);
1875: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1876: #ifdef DEBUGBRENT
1.126 brouard 1877: 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);
1878: 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);
1879: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1880: #endif
1881: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1882: *xmin=x;
1883: return fx;
1884: }
1885: ftemp=fu;
1886: if (fabs(e) > tol1) {
1887: r=(x-w)*(fx-fv);
1888: q=(x-v)*(fx-fw);
1889: p=(x-v)*q-(x-w)*r;
1890: q=2.0*(q-r);
1891: if (q > 0.0) p = -p;
1892: q=fabs(q);
1893: etemp=e;
1894: e=d;
1895: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1896: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1897: else {
1.224 brouard 1898: d=p/q;
1899: u=x+d;
1900: if (u-a < tol2 || b-u < tol2)
1901: d=SIGN(tol1,xm-x);
1.126 brouard 1902: }
1903: } else {
1904: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1905: }
1906: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1907: fu=(*f)(u);
1908: if (fu <= fx) {
1909: if (u >= x) a=x; else b=x;
1910: SHFT(v,w,x,u)
1.183 brouard 1911: SHFT(fv,fw,fx,fu)
1912: } else {
1913: if (u < x) a=u; else b=u;
1914: if (fu <= fw || w == x) {
1.224 brouard 1915: v=w;
1916: w=u;
1917: fv=fw;
1918: fw=fu;
1.183 brouard 1919: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1920: v=u;
1921: fv=fu;
1.183 brouard 1922: }
1923: }
1.126 brouard 1924: }
1925: nrerror("Too many iterations in brent");
1926: *xmin=x;
1927: return fx;
1928: }
1929:
1930: /****************** mnbrak ***********************/
1931:
1932: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1933: double (*func)(double))
1.183 brouard 1934: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1935: the downhill direction (defined by the function as evaluated at the initial points) and returns
1936: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1937: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1938: */
1.126 brouard 1939: double ulim,u,r,q, dum;
1940: double fu;
1.187 brouard 1941:
1942: double scale=10.;
1943: int iterscale=0;
1944:
1945: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1946: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1947:
1948:
1949: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1950: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1951: /* *bx = *ax - (*ax - *bx)/scale; */
1952: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1953: /* } */
1954:
1.126 brouard 1955: if (*fb > *fa) {
1956: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1957: SHFT(dum,*fb,*fa,dum)
1958: }
1.126 brouard 1959: *cx=(*bx)+GOLD*(*bx-*ax);
1960: *fc=(*func)(*cx);
1.183 brouard 1961: #ifdef DEBUG
1.224 brouard 1962: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1963: 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 1964: #endif
1.224 brouard 1965: 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 1966: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1967: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1968: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1969: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1970: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1971: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1972: fu=(*func)(u);
1.163 brouard 1973: #ifdef DEBUG
1974: /* f(x)=A(x-u)**2+f(u) */
1975: double A, fparabu;
1976: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1977: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 1978: 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);
1979: 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 1980: /* And thus,it can be that fu > *fc even if fparabu < *fc */
1981: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
1982: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
1983: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 1984: #endif
1.184 brouard 1985: #ifdef MNBRAKORIGINAL
1.183 brouard 1986: #else
1.191 brouard 1987: /* if (fu > *fc) { */
1988: /* #ifdef DEBUG */
1989: /* printf("mnbrak4 fu > fc \n"); */
1990: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
1991: /* #endif */
1992: /* /\* 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 *\\/ *\/ */
1993: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
1994: /* dum=u; /\* Shifting c and u *\/ */
1995: /* u = *cx; */
1996: /* *cx = dum; */
1997: /* dum = fu; */
1998: /* fu = *fc; */
1999: /* *fc =dum; */
2000: /* } else { /\* end *\/ */
2001: /* #ifdef DEBUG */
2002: /* printf("mnbrak3 fu < fc \n"); */
2003: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2004: /* #endif */
2005: /* dum=u; /\* Shifting c and u *\/ */
2006: /* u = *cx; */
2007: /* *cx = dum; */
2008: /* dum = fu; */
2009: /* fu = *fc; */
2010: /* *fc =dum; */
2011: /* } */
1.224 brouard 2012: #ifdef DEBUGMNBRAK
2013: double A, fparabu;
2014: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2015: fparabu= *fa - A*(*ax-u)*(*ax-u);
2016: 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);
2017: 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 2018: #endif
1.191 brouard 2019: dum=u; /* Shifting c and u */
2020: u = *cx;
2021: *cx = dum;
2022: dum = fu;
2023: fu = *fc;
2024: *fc =dum;
1.183 brouard 2025: #endif
1.162 brouard 2026: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2027: #ifdef DEBUG
1.224 brouard 2028: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2029: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2030: #endif
1.126 brouard 2031: fu=(*func)(u);
2032: if (fu < *fc) {
1.183 brouard 2033: #ifdef DEBUG
1.224 brouard 2034: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2035: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2036: #endif
2037: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2038: SHFT(*fb,*fc,fu,(*func)(u))
2039: #ifdef DEBUG
2040: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2041: #endif
2042: }
1.162 brouard 2043: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2044: #ifdef DEBUG
1.224 brouard 2045: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2046: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2047: #endif
1.126 brouard 2048: u=ulim;
2049: fu=(*func)(u);
1.183 brouard 2050: } else { /* u could be left to b (if r > q parabola has a maximum) */
2051: #ifdef DEBUG
1.224 brouard 2052: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2053: 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 2054: #endif
1.126 brouard 2055: u=(*cx)+GOLD*(*cx-*bx);
2056: fu=(*func)(u);
1.224 brouard 2057: #ifdef DEBUG
2058: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2059: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2060: #endif
1.183 brouard 2061: } /* end tests */
1.126 brouard 2062: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2063: SHFT(*fa,*fb,*fc,fu)
2064: #ifdef DEBUG
1.224 brouard 2065: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2066: 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 2067: #endif
2068: } /* 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 2069: }
2070:
2071: /*************** linmin ************************/
1.162 brouard 2072: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2073: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2074: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2075: the value of func at the returned location p . This is actually all accomplished by calling the
2076: routines mnbrak and brent .*/
1.126 brouard 2077: int ncom;
2078: double *pcom,*xicom;
2079: double (*nrfunc)(double []);
2080:
1.224 brouard 2081: #ifdef LINMINORIGINAL
1.126 brouard 2082: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2083: #else
2084: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2085: #endif
1.126 brouard 2086: {
2087: double brent(double ax, double bx, double cx,
2088: double (*f)(double), double tol, double *xmin);
2089: double f1dim(double x);
2090: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2091: double *fc, double (*func)(double));
2092: int j;
2093: double xx,xmin,bx,ax;
2094: double fx,fb,fa;
1.187 brouard 2095:
1.203 brouard 2096: #ifdef LINMINORIGINAL
2097: #else
2098: double scale=10., axs, xxs; /* Scale added for infinity */
2099: #endif
2100:
1.126 brouard 2101: ncom=n;
2102: pcom=vector(1,n);
2103: xicom=vector(1,n);
2104: nrfunc=func;
2105: for (j=1;j<=n;j++) {
2106: pcom[j]=p[j];
1.202 brouard 2107: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2108: }
1.187 brouard 2109:
1.203 brouard 2110: #ifdef LINMINORIGINAL
2111: xx=1.;
2112: #else
2113: axs=0.0;
2114: xxs=1.;
2115: do{
2116: xx= xxs;
2117: #endif
1.187 brouard 2118: ax=0.;
2119: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2120: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2121: /* 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)) */
2122: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2123: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2124: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2125: /* 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 2126: #ifdef LINMINORIGINAL
2127: #else
2128: if (fx != fx){
1.224 brouard 2129: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2130: printf("|");
2131: fprintf(ficlog,"|");
1.203 brouard 2132: #ifdef DEBUGLINMIN
1.224 brouard 2133: 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 2134: #endif
2135: }
1.224 brouard 2136: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2137: #endif
2138:
1.191 brouard 2139: #ifdef DEBUGLINMIN
2140: 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 2141: 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 2142: #endif
1.224 brouard 2143: #ifdef LINMINORIGINAL
2144: #else
2145: if(fb == fx){ /* Flat function in the direction */
2146: xmin=xx;
2147: *flat=1;
2148: }else{
2149: *flat=0;
2150: #endif
2151: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2152: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2153: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2154: /* fmin = f(p[j] + xmin * xi[j]) */
2155: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2156: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2157: #ifdef DEBUG
1.224 brouard 2158: 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);
2159: 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);
2160: #endif
2161: #ifdef LINMINORIGINAL
2162: #else
2163: }
1.126 brouard 2164: #endif
1.191 brouard 2165: #ifdef DEBUGLINMIN
2166: printf("linmin end ");
1.202 brouard 2167: fprintf(ficlog,"linmin end ");
1.191 brouard 2168: #endif
1.126 brouard 2169: for (j=1;j<=n;j++) {
1.203 brouard 2170: #ifdef LINMINORIGINAL
2171: xi[j] *= xmin;
2172: #else
2173: #ifdef DEBUGLINMIN
2174: if(xxs <1.0)
2175: printf(" before xi[%d]=%12.8f", j,xi[j]);
2176: #endif
2177: 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) */
2178: #ifdef DEBUGLINMIN
2179: if(xxs <1.0)
2180: 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 );
2181: #endif
2182: #endif
1.187 brouard 2183: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2184: }
1.191 brouard 2185: #ifdef DEBUGLINMIN
1.203 brouard 2186: printf("\n");
1.191 brouard 2187: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2188: 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 2189: for (j=1;j<=n;j++) {
1.202 brouard 2190: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2191: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2192: if(j % ncovmodel == 0){
1.191 brouard 2193: printf("\n");
1.202 brouard 2194: fprintf(ficlog,"\n");
2195: }
1.191 brouard 2196: }
1.203 brouard 2197: #else
1.191 brouard 2198: #endif
1.126 brouard 2199: free_vector(xicom,1,n);
2200: free_vector(pcom,1,n);
2201: }
2202:
2203:
2204: /*************** powell ************************/
1.162 brouard 2205: /*
2206: Minimization of a function func of n variables. Input consists of an initial starting point
2207: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2208: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2209: such that failure to decrease by more than this amount on one iteration signals doneness. On
2210: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2211: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2212: */
1.224 brouard 2213: #ifdef LINMINORIGINAL
2214: #else
2215: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2216: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2217: #endif
1.126 brouard 2218: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2219: double (*func)(double []))
2220: {
1.224 brouard 2221: #ifdef LINMINORIGINAL
2222: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2223: double (*func)(double []));
1.224 brouard 2224: #else
1.241 brouard 2225: void linmin(double p[], double xi[], int n, double *fret,
2226: double (*func)(double []),int *flat);
1.224 brouard 2227: #endif
1.239 brouard 2228: int i,ibig,j,jk,k;
1.126 brouard 2229: double del,t,*pt,*ptt,*xit;
1.181 brouard 2230: double directest;
1.126 brouard 2231: double fp,fptt;
2232: double *xits;
2233: int niterf, itmp;
1.224 brouard 2234: #ifdef LINMINORIGINAL
2235: #else
2236:
2237: flatdir=ivector(1,n);
2238: for (j=1;j<=n;j++) flatdir[j]=0;
2239: #endif
1.126 brouard 2240:
2241: pt=vector(1,n);
2242: ptt=vector(1,n);
2243: xit=vector(1,n);
2244: xits=vector(1,n);
2245: *fret=(*func)(p);
2246: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2247: rcurr_time = time(NULL);
1.126 brouard 2248: for (*iter=1;;++(*iter)) {
1.187 brouard 2249: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2250: ibig=0;
2251: del=0.0;
1.157 brouard 2252: rlast_time=rcurr_time;
2253: /* (void) gettimeofday(&curr_time,&tzp); */
2254: rcurr_time = time(NULL);
2255: curr_time = *localtime(&rcurr_time);
2256: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2257: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2258: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2259: for (i=1;i<=n;i++) {
1.126 brouard 2260: fprintf(ficrespow," %.12lf", p[i]);
2261: }
1.239 brouard 2262: fprintf(ficrespow,"\n");fflush(ficrespow);
2263: printf("\n#model= 1 + age ");
2264: fprintf(ficlog,"\n#model= 1 + age ");
2265: if(nagesqr==1){
1.241 brouard 2266: printf(" + age*age ");
2267: fprintf(ficlog," + age*age ");
1.239 brouard 2268: }
2269: for(j=1;j <=ncovmodel-2;j++){
2270: if(Typevar[j]==0) {
2271: printf(" + V%d ",Tvar[j]);
2272: fprintf(ficlog," + V%d ",Tvar[j]);
2273: }else if(Typevar[j]==1) {
2274: printf(" + V%d*age ",Tvar[j]);
2275: fprintf(ficlog," + V%d*age ",Tvar[j]);
2276: }else if(Typevar[j]==2) {
2277: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2278: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2279: }
2280: }
1.126 brouard 2281: printf("\n");
1.239 brouard 2282: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2283: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2284: fprintf(ficlog,"\n");
1.239 brouard 2285: for(i=1,jk=1; i <=nlstate; i++){
2286: for(k=1; k <=(nlstate+ndeath); k++){
2287: if (k != i) {
2288: printf("%d%d ",i,k);
2289: fprintf(ficlog,"%d%d ",i,k);
2290: for(j=1; j <=ncovmodel; j++){
2291: printf("%12.7f ",p[jk]);
2292: fprintf(ficlog,"%12.7f ",p[jk]);
2293: jk++;
2294: }
2295: printf("\n");
2296: fprintf(ficlog,"\n");
2297: }
2298: }
2299: }
1.241 brouard 2300: if(*iter <=3 && *iter >1){
1.157 brouard 2301: tml = *localtime(&rcurr_time);
2302: strcpy(strcurr,asctime(&tml));
2303: rforecast_time=rcurr_time;
1.126 brouard 2304: itmp = strlen(strcurr);
2305: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2306: strcurr[itmp-1]='\0';
1.162 brouard 2307: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2308: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2309: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2310: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2311: forecast_time = *localtime(&rforecast_time);
2312: strcpy(strfor,asctime(&forecast_time));
2313: itmp = strlen(strfor);
2314: if(strfor[itmp-1]=='\n')
2315: strfor[itmp-1]='\0';
2316: 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);
2317: 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 2318: }
2319: }
1.187 brouard 2320: for (i=1;i<=n;i++) { /* For each direction i */
2321: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2322: fptt=(*fret);
2323: #ifdef DEBUG
1.203 brouard 2324: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2325: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2326: #endif
1.203 brouard 2327: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2328: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2329: #ifdef LINMINORIGINAL
1.188 brouard 2330: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2331: #else
2332: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2333: flatdir[i]=flat; /* Function is vanishing in that direction i */
2334: #endif
2335: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2336: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2337: /* because that direction will be replaced unless the gain del is small */
2338: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2339: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2340: /* with the new direction. */
2341: del=fabs(fptt-(*fret));
2342: ibig=i;
1.126 brouard 2343: }
2344: #ifdef DEBUG
2345: printf("%d %.12e",i,(*fret));
2346: fprintf(ficlog,"%d %.12e",i,(*fret));
2347: for (j=1;j<=n;j++) {
1.224 brouard 2348: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2349: printf(" x(%d)=%.12e",j,xit[j]);
2350: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2351: }
2352: for(j=1;j<=n;j++) {
1.225 brouard 2353: printf(" p(%d)=%.12e",j,p[j]);
2354: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2355: }
2356: printf("\n");
2357: fprintf(ficlog,"\n");
2358: #endif
1.187 brouard 2359: } /* end loop on each direction i */
2360: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2361: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2362: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2363: for(j=1;j<=n;j++) {
1.225 brouard 2364: if(flatdir[j] >0){
2365: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2366: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2367: }
2368: /* printf("\n"); */
2369: /* fprintf(ficlog,"\n"); */
2370: }
1.243 brouard 2371: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2372: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2373: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2374: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2375: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2376: /* decreased of more than 3.84 */
2377: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2378: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2379: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2380:
1.188 brouard 2381: /* Starting the program with initial values given by a former maximization will simply change */
2382: /* the scales of the directions and the directions, because the are reset to canonical directions */
2383: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2384: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2385: #ifdef DEBUG
2386: int k[2],l;
2387: k[0]=1;
2388: k[1]=-1;
2389: printf("Max: %.12e",(*func)(p));
2390: fprintf(ficlog,"Max: %.12e",(*func)(p));
2391: for (j=1;j<=n;j++) {
2392: printf(" %.12e",p[j]);
2393: fprintf(ficlog," %.12e",p[j]);
2394: }
2395: printf("\n");
2396: fprintf(ficlog,"\n");
2397: for(l=0;l<=1;l++) {
2398: for (j=1;j<=n;j++) {
2399: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2400: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2401: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2402: }
2403: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2404: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2405: }
2406: #endif
2407:
1.224 brouard 2408: #ifdef LINMINORIGINAL
2409: #else
2410: free_ivector(flatdir,1,n);
2411: #endif
1.126 brouard 2412: free_vector(xit,1,n);
2413: free_vector(xits,1,n);
2414: free_vector(ptt,1,n);
2415: free_vector(pt,1,n);
2416: return;
1.192 brouard 2417: } /* enough precision */
1.240 brouard 2418: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2419: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2420: ptt[j]=2.0*p[j]-pt[j];
2421: xit[j]=p[j]-pt[j];
2422: pt[j]=p[j];
2423: }
1.181 brouard 2424: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2425: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2426: if (*iter <=4) {
1.225 brouard 2427: #else
2428: #endif
1.224 brouard 2429: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2430: #else
1.161 brouard 2431: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2432: #endif
1.162 brouard 2433: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2434: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2435: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2436: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2437: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2438: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2439: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2440: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2441: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2442: /* Even if f3 <f1, directest can be negative and t >0 */
2443: /* mu² and del² are equal when f3=f1 */
2444: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2445: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2446: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2447: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2448: #ifdef NRCORIGINAL
2449: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2450: #else
2451: 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 2452: t= t- del*SQR(fp-fptt);
1.183 brouard 2453: #endif
1.202 brouard 2454: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2455: #ifdef DEBUG
1.181 brouard 2456: 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);
2457: 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 2458: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2459: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2460: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2461: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2462: 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);
2463: 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);
2464: #endif
1.183 brouard 2465: #ifdef POWELLORIGINAL
2466: if (t < 0.0) { /* Then we use it for new direction */
2467: #else
1.182 brouard 2468: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2469: 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 2470: 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 2471: 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 2472: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2473: }
1.181 brouard 2474: if (directest < 0.0) { /* Then we use it for new direction */
2475: #endif
1.191 brouard 2476: #ifdef DEBUGLINMIN
1.234 brouard 2477: printf("Before linmin in direction P%d-P0\n",n);
2478: for (j=1;j<=n;j++) {
2479: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2480: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2481: if(j % ncovmodel == 0){
2482: printf("\n");
2483: fprintf(ficlog,"\n");
2484: }
2485: }
1.224 brouard 2486: #endif
2487: #ifdef LINMINORIGINAL
1.234 brouard 2488: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2489: #else
1.234 brouard 2490: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2491: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2492: #endif
1.234 brouard 2493:
1.191 brouard 2494: #ifdef DEBUGLINMIN
1.234 brouard 2495: for (j=1;j<=n;j++) {
2496: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2497: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2498: if(j % ncovmodel == 0){
2499: printf("\n");
2500: fprintf(ficlog,"\n");
2501: }
2502: }
1.224 brouard 2503: #endif
1.234 brouard 2504: for (j=1;j<=n;j++) {
2505: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2506: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2507: }
1.224 brouard 2508: #ifdef LINMINORIGINAL
2509: #else
1.234 brouard 2510: for (j=1, flatd=0;j<=n;j++) {
2511: if(flatdir[j]>0)
2512: flatd++;
2513: }
2514: if(flatd >0){
1.255 brouard 2515: printf("%d flat directions: ",flatd);
2516: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2517: for (j=1;j<=n;j++) {
2518: if(flatdir[j]>0){
2519: printf("%d ",j);
2520: fprintf(ficlog,"%d ",j);
2521: }
2522: }
2523: printf("\n");
2524: fprintf(ficlog,"\n");
2525: }
1.191 brouard 2526: #endif
1.234 brouard 2527: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2528: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2529:
1.126 brouard 2530: #ifdef DEBUG
1.234 brouard 2531: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2532: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2533: for(j=1;j<=n;j++){
2534: printf(" %lf",xit[j]);
2535: fprintf(ficlog," %lf",xit[j]);
2536: }
2537: printf("\n");
2538: fprintf(ficlog,"\n");
1.126 brouard 2539: #endif
1.192 brouard 2540: } /* end of t or directest negative */
1.224 brouard 2541: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2542: #else
1.234 brouard 2543: } /* end if (fptt < fp) */
1.192 brouard 2544: #endif
1.225 brouard 2545: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2546: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2547: #else
1.224 brouard 2548: #endif
1.234 brouard 2549: } /* loop iteration */
1.126 brouard 2550: }
1.234 brouard 2551:
1.126 brouard 2552: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2553:
1.235 brouard 2554: 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 2555: {
1.279 brouard 2556: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2557: * (and selected quantitative values in nres)
2558: * by left multiplying the unit
2559: * matrix by transitions matrix until convergence is reached with precision ftolpl
2560: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2561: * Wx is row vector: population in state 1, population in state 2, population dead
2562: * or prevalence in state 1, prevalence in state 2, 0
2563: * newm is the matrix after multiplications, its rows are identical at a factor.
2564: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2565: * Output is prlim.
2566: * Initial matrix pimij
2567: */
1.206 brouard 2568: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2569: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2570: /* 0, 0 , 1} */
2571: /*
2572: * and after some iteration: */
2573: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2574: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2575: /* 0, 0 , 1} */
2576: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2577: /* {0.51571254859325999, 0.4842874514067399, */
2578: /* 0.51326036147820708, 0.48673963852179264} */
2579: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2580:
1.126 brouard 2581: int i, ii,j,k;
1.209 brouard 2582: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2583: /* double **matprod2(); */ /* test */
1.218 brouard 2584: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2585: double **newm;
1.209 brouard 2586: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2587: int ncvloop=0;
1.288 brouard 2588: int first=0;
1.169 brouard 2589:
1.209 brouard 2590: min=vector(1,nlstate);
2591: max=vector(1,nlstate);
2592: meandiff=vector(1,nlstate);
2593:
1.218 brouard 2594: /* Starting with matrix unity */
1.126 brouard 2595: for (ii=1;ii<=nlstate+ndeath;ii++)
2596: for (j=1;j<=nlstate+ndeath;j++){
2597: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2598: }
1.169 brouard 2599:
2600: cov[1]=1.;
2601:
2602: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2603: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2604: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2605: ncvloop++;
1.126 brouard 2606: newm=savm;
2607: /* Covariates have to be included here again */
1.138 brouard 2608: cov[2]=agefin;
1.187 brouard 2609: if(nagesqr==1)
2610: cov[3]= agefin*agefin;;
1.234 brouard 2611: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2612: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2613: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2614: /* 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 2615: }
2616: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2617: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2618: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2619: /* 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 2620: }
1.237 brouard 2621: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2622: if(Dummy[Tvar[Tage[k]]]){
2623: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2624: } else{
1.235 brouard 2625: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2626: }
1.235 brouard 2627: /* 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 2628: }
1.237 brouard 2629: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2630: /* 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 2631: if(Dummy[Tvard[k][1]==0]){
2632: if(Dummy[Tvard[k][2]==0]){
2633: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2634: }else{
2635: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2636: }
2637: }else{
2638: if(Dummy[Tvard[k][2]==0]){
2639: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2640: }else{
2641: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2642: }
2643: }
1.234 brouard 2644: }
1.138 brouard 2645: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2646: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2647: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2648: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2649: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2650: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2651: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2652:
1.126 brouard 2653: savm=oldm;
2654: oldm=newm;
1.209 brouard 2655:
2656: for(j=1; j<=nlstate; j++){
2657: max[j]=0.;
2658: min[j]=1.;
2659: }
2660: for(i=1;i<=nlstate;i++){
2661: sumnew=0;
2662: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2663: for(j=1; j<=nlstate; j++){
2664: prlim[i][j]= newm[i][j]/(1-sumnew);
2665: max[j]=FMAX(max[j],prlim[i][j]);
2666: min[j]=FMIN(min[j],prlim[i][j]);
2667: }
2668: }
2669:
1.126 brouard 2670: maxmax=0.;
1.209 brouard 2671: for(j=1; j<=nlstate; j++){
2672: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2673: maxmax=FMAX(maxmax,meandiff[j]);
2674: /* 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 2675: } /* j loop */
1.203 brouard 2676: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2677: /* 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 2678: if(maxmax < ftolpl){
1.209 brouard 2679: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2680: free_vector(min,1,nlstate);
2681: free_vector(max,1,nlstate);
2682: free_vector(meandiff,1,nlstate);
1.126 brouard 2683: return prlim;
2684: }
1.288 brouard 2685: } /* agefin loop */
1.208 brouard 2686: /* After some age loop it doesn't converge */
1.288 brouard 2687: if(!first){
2688: first=1;
2689: 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);
2690: }
2691: 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);
2692:
1.209 brouard 2693: /* 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); */
2694: free_vector(min,1,nlstate);
2695: free_vector(max,1,nlstate);
2696: free_vector(meandiff,1,nlstate);
1.208 brouard 2697:
1.169 brouard 2698: return prlim; /* should not reach here */
1.126 brouard 2699: }
2700:
1.217 brouard 2701:
2702: /**** Back Prevalence limit (stable or period prevalence) ****************/
2703:
1.218 brouard 2704: /* 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) */
2705: /* 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 2706: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2707: {
1.264 brouard 2708: /* 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 2709: matrix by transitions matrix until convergence is reached with precision ftolpl */
2710: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2711: /* Wx is row vector: population in state 1, population in state 2, population dead */
2712: /* or prevalence in state 1, prevalence in state 2, 0 */
2713: /* newm is the matrix after multiplications, its rows are identical at a factor */
2714: /* Initial matrix pimij */
2715: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2716: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2717: /* 0, 0 , 1} */
2718: /*
2719: * and after some iteration: */
2720: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2721: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2722: /* 0, 0 , 1} */
2723: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2724: /* {0.51571254859325999, 0.4842874514067399, */
2725: /* 0.51326036147820708, 0.48673963852179264} */
2726: /* If we start from prlim again, prlim tends to a constant matrix */
2727:
2728: int i, ii,j,k;
1.247 brouard 2729: int first=0;
1.217 brouard 2730: double *min, *max, *meandiff, maxmax,sumnew=0.;
2731: /* double **matprod2(); */ /* test */
2732: double **out, cov[NCOVMAX+1], **bmij();
2733: double **newm;
1.218 brouard 2734: double **dnewm, **doldm, **dsavm; /* for use */
2735: double **oldm, **savm; /* for use */
2736:
1.217 brouard 2737: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2738: int ncvloop=0;
2739:
2740: min=vector(1,nlstate);
2741: max=vector(1,nlstate);
2742: meandiff=vector(1,nlstate);
2743:
1.266 brouard 2744: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2745: oldm=oldms; savm=savms;
2746:
2747: /* Starting with matrix unity */
2748: for (ii=1;ii<=nlstate+ndeath;ii++)
2749: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2750: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2751: }
2752:
2753: cov[1]=1.;
2754:
2755: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2756: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2757: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 2758: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2759: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2760: ncvloop++;
1.218 brouard 2761: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2762: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2763: /* Covariates have to be included here again */
2764: cov[2]=agefin;
2765: if(nagesqr==1)
2766: cov[3]= agefin*agefin;;
1.242 brouard 2767: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2768: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2769: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2770: /* 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 2771: }
2772: /* for (k=1; k<=cptcovn;k++) { */
2773: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2774: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2775: /* /\* 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])]); *\/ */
2776: /* } */
2777: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2778: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2779: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2780: /* 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]); */
2781: }
2782: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2783: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2784: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2785: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2786: for (k=1; k<=cptcovage;k++){ /* For product with age */
2787: if(Dummy[Tvar[Tage[k]]]){
2788: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2789: } else{
2790: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2791: }
2792: /* 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]); */
2793: }
2794: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2795: /* 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]); */
2796: if(Dummy[Tvard[k][1]==0]){
2797: if(Dummy[Tvard[k][2]==0]){
2798: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2799: }else{
2800: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2801: }
2802: }else{
2803: if(Dummy[Tvard[k][2]==0]){
2804: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2805: }else{
2806: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2807: }
2808: }
1.217 brouard 2809: }
2810:
2811: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2812: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2813: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2814: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2815: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2816: /* ij should be linked to the correct index of cov */
2817: /* age and covariate values ij are in 'cov', but we need to pass
2818: * ij for the observed prevalence at age and status and covariate
2819: * number: prevacurrent[(int)agefin][ii][ij]
2820: */
2821: /* 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 *\/ */
2822: /* 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 *\/ */
2823: 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 2824: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2825: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2826: /* for(i=1; i<=nlstate+ndeath; i++) { */
2827: /* printf("%d newm= ",i); */
2828: /* for(j=1;j<=nlstate+ndeath;j++) { */
2829: /* printf("%f ",newm[i][j]); */
2830: /* } */
2831: /* printf("oldm * "); */
2832: /* for(j=1;j<=nlstate+ndeath;j++) { */
2833: /* printf("%f ",oldm[i][j]); */
2834: /* } */
1.268 brouard 2835: /* printf(" bmmij "); */
1.266 brouard 2836: /* for(j=1;j<=nlstate+ndeath;j++) { */
2837: /* printf("%f ",pmmij[i][j]); */
2838: /* } */
2839: /* printf("\n"); */
2840: /* } */
2841: /* } */
1.217 brouard 2842: savm=oldm;
2843: oldm=newm;
1.266 brouard 2844:
1.217 brouard 2845: for(j=1; j<=nlstate; j++){
2846: max[j]=0.;
2847: min[j]=1.;
2848: }
2849: for(j=1; j<=nlstate; j++){
2850: for(i=1;i<=nlstate;i++){
1.234 brouard 2851: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2852: bprlim[i][j]= newm[i][j];
2853: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2854: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2855: }
2856: }
1.218 brouard 2857:
1.217 brouard 2858: maxmax=0.;
2859: for(i=1; i<=nlstate; i++){
2860: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2861: maxmax=FMAX(maxmax,meandiff[i]);
2862: /* 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 2863: } /* i loop */
1.217 brouard 2864: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 2865: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2866: if(maxmax < ftolpl){
1.220 brouard 2867: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2868: free_vector(min,1,nlstate);
2869: free_vector(max,1,nlstate);
2870: free_vector(meandiff,1,nlstate);
2871: return bprlim;
2872: }
1.288 brouard 2873: } /* agefin loop */
1.217 brouard 2874: /* After some age loop it doesn't converge */
1.288 brouard 2875: if(!first){
1.247 brouard 2876: first=1;
2877: 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\
2878: 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);
2879: }
2880: 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 2881: 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);
2882: /* 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); */
2883: free_vector(min,1,nlstate);
2884: free_vector(max,1,nlstate);
2885: free_vector(meandiff,1,nlstate);
2886:
2887: return bprlim; /* should not reach here */
2888: }
2889:
1.126 brouard 2890: /*************** transition probabilities ***************/
2891:
2892: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2893: {
1.138 brouard 2894: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2895: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2896: model to the ncovmodel covariates (including constant and age).
2897: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2898: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2899: ncth covariate in the global vector x is given by the formula:
2900: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2901: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2902: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2903: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 2904: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 2905: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 2906: Sum on j ps[i][j] should equal to 1.
1.138 brouard 2907: */
2908: double s1, lnpijopii;
1.126 brouard 2909: /*double t34;*/
1.164 brouard 2910: int i,j, nc, ii, jj;
1.126 brouard 2911:
1.223 brouard 2912: for(i=1; i<= nlstate; i++){
2913: for(j=1; j<i;j++){
2914: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2915: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2916: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2917: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2918: }
2919: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2920: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2921: }
2922: for(j=i+1; j<=nlstate+ndeath;j++){
2923: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2924: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2925: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2926: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2927: }
2928: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2929: }
2930: }
1.218 brouard 2931:
1.223 brouard 2932: for(i=1; i<= nlstate; i++){
2933: s1=0;
2934: for(j=1; j<i; j++){
2935: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2936: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2937: }
2938: for(j=i+1; j<=nlstate+ndeath; j++){
2939: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2940: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2941: }
2942: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2943: ps[i][i]=1./(s1+1.);
2944: /* Computing other pijs */
2945: for(j=1; j<i; j++)
2946: ps[i][j]= exp(ps[i][j])*ps[i][i];
2947: for(j=i+1; j<=nlstate+ndeath; j++)
2948: ps[i][j]= exp(ps[i][j])*ps[i][i];
2949: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2950: } /* end i */
1.218 brouard 2951:
1.223 brouard 2952: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2953: for(jj=1; jj<= nlstate+ndeath; jj++){
2954: ps[ii][jj]=0;
2955: ps[ii][ii]=1;
2956: }
2957: }
1.218 brouard 2958:
2959:
1.223 brouard 2960: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2961: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2962: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2963: /* } */
2964: /* printf("\n "); */
2965: /* } */
2966: /* printf("\n ");printf("%lf ",cov[2]);*/
2967: /*
2968: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2969: goto end;*/
1.266 brouard 2970: return ps; /* Pointer is unchanged since its call */
1.126 brouard 2971: }
2972:
1.218 brouard 2973: /*************** backward transition probabilities ***************/
2974:
2975: /* 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 ) */
2976: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2977: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
2978: {
1.266 brouard 2979: /* Computes the backward probability at age agefin and covariate combination ij. In fact cov is already filled and x too.
2980: * 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 2981: */
1.218 brouard 2982: int i, ii, j,k;
1.222 brouard 2983:
2984: double **out, **pmij();
2985: double sumnew=0.;
1.218 brouard 2986: double agefin;
1.268 brouard 2987: double k3=0.; /* constant of the w_x diagonal matrixe (in order for B to sum to 1 even for death state) */
1.222 brouard 2988: double **dnewm, **dsavm, **doldm;
2989: double **bbmij;
2990:
1.218 brouard 2991: doldm=ddoldms; /* global pointers */
1.222 brouard 2992: dnewm=ddnewms;
2993: dsavm=ddsavms;
2994:
2995: agefin=cov[2];
1.268 brouard 2996: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 2997: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 2998: the observed prevalence (with this covariate ij) at beginning of transition */
2999: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3000:
3001: /* P_x */
1.266 brouard 3002: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 3003: /* outputs pmmij which is a stochastic matrix in row */
3004:
3005: /* Diag(w_x) */
3006: /* Problem with prevacurrent which can be zero */
3007: sumnew=0.;
1.269 brouard 3008: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3009: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.269 brouard 3010: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3011: sumnew+=prevacurrent[(int)agefin][ii][ij];
3012: }
3013: if(sumnew >0.01){ /* At least some value in the prevalence */
3014: for (ii=1;ii<=nlstate+ndeath;ii++){
3015: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3016: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3017: }
3018: }else{
3019: for (ii=1;ii<=nlstate+ndeath;ii++){
3020: for (j=1;j<=nlstate+ndeath;j++)
3021: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3022: }
3023: /* if(sumnew <0.9){ */
3024: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3025: /* } */
3026: }
3027: k3=0.0; /* We put the last diagonal to 0 */
3028: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3029: doldm[ii][ii]= k3;
3030: }
3031: /* End doldm, At the end doldm is diag[(w_i)] */
3032:
3033: /* left Product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm) */
3034: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* Bug Valgrind */
3035:
3036: /* Diag(Sum_i w^i_x p^ij_x */
3037: /* 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 3038: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3039: sumnew=0.;
1.222 brouard 3040: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3041: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3042: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3043: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3044: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3045: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3046: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3047: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3048: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3049: /* }else */
1.268 brouard 3050: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3051: } /*End ii */
3052: } /* 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 */
3053:
3054: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* Bug Valgrind */
3055: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3056: /* end bmij */
1.266 brouard 3057: return ps; /*pointer is unchanged */
1.218 brouard 3058: }
1.217 brouard 3059: /*************** transition probabilities ***************/
3060:
1.218 brouard 3061: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3062: {
3063: /* According to parameters values stored in x and the covariate's values stored in cov,
3064: computes the probability to be observed in state j being in state i by appying the
3065: model to the ncovmodel covariates (including constant and age).
3066: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3067: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3068: ncth covariate in the global vector x is given by the formula:
3069: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3070: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3071: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3072: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3073: Outputs ps[i][j] the probability to be observed in j being in j according to
3074: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3075: */
3076: double s1, lnpijopii;
3077: /*double t34;*/
3078: int i,j, nc, ii, jj;
3079:
1.234 brouard 3080: for(i=1; i<= nlstate; i++){
3081: for(j=1; j<i;j++){
3082: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3083: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3084: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3085: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3086: }
3087: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3088: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3089: }
3090: for(j=i+1; j<=nlstate+ndeath;j++){
3091: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3092: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3093: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3094: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3095: }
3096: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3097: }
3098: }
3099:
3100: for(i=1; i<= nlstate; i++){
3101: s1=0;
3102: for(j=1; j<i; j++){
3103: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3104: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3105: }
3106: for(j=i+1; j<=nlstate+ndeath; j++){
3107: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3108: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3109: }
3110: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3111: ps[i][i]=1./(s1+1.);
3112: /* Computing other pijs */
3113: for(j=1; j<i; j++)
3114: ps[i][j]= exp(ps[i][j])*ps[i][i];
3115: for(j=i+1; j<=nlstate+ndeath; j++)
3116: ps[i][j]= exp(ps[i][j])*ps[i][i];
3117: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3118: } /* end i */
3119:
3120: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3121: for(jj=1; jj<= nlstate+ndeath; jj++){
3122: ps[ii][jj]=0;
3123: ps[ii][ii]=1;
3124: }
3125: }
3126: /* Added for backcast */ /* Transposed matrix too */
3127: for(jj=1; jj<= nlstate+ndeath; jj++){
3128: s1=0.;
3129: for(ii=1; ii<= nlstate+ndeath; ii++){
3130: s1+=ps[ii][jj];
3131: }
3132: for(ii=1; ii<= nlstate; ii++){
3133: ps[ii][jj]=ps[ii][jj]/s1;
3134: }
3135: }
3136: /* Transposition */
3137: for(jj=1; jj<= nlstate+ndeath; jj++){
3138: for(ii=jj; ii<= nlstate+ndeath; ii++){
3139: s1=ps[ii][jj];
3140: ps[ii][jj]=ps[jj][ii];
3141: ps[jj][ii]=s1;
3142: }
3143: }
3144: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3145: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3146: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3147: /* } */
3148: /* printf("\n "); */
3149: /* } */
3150: /* printf("\n ");printf("%lf ",cov[2]);*/
3151: /*
3152: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3153: goto end;*/
3154: return ps;
1.217 brouard 3155: }
3156:
3157:
1.126 brouard 3158: /**************** Product of 2 matrices ******************/
3159:
1.145 brouard 3160: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3161: {
3162: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3163: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3164: /* in, b, out are matrice of pointers which should have been initialized
3165: before: only the contents of out is modified. The function returns
3166: a pointer to pointers identical to out */
1.145 brouard 3167: int i, j, k;
1.126 brouard 3168: for(i=nrl; i<= nrh; i++)
1.145 brouard 3169: for(k=ncolol; k<=ncoloh; k++){
3170: out[i][k]=0.;
3171: for(j=ncl; j<=nch; j++)
3172: out[i][k] +=in[i][j]*b[j][k];
3173: }
1.126 brouard 3174: return out;
3175: }
3176:
3177:
3178: /************* Higher Matrix Product ***************/
3179:
1.235 brouard 3180: 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 3181: {
1.218 brouard 3182: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3183: 'nhstepm*hstepm*stepm' months (i.e. until
3184: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3185: nhstepm*hstepm matrices.
3186: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3187: (typically every 2 years instead of every month which is too big
3188: for the memory).
3189: Model is determined by parameters x and covariates have to be
3190: included manually here.
3191:
3192: */
3193:
3194: int i, j, d, h, k;
1.131 brouard 3195: double **out, cov[NCOVMAX+1];
1.126 brouard 3196: double **newm;
1.187 brouard 3197: double agexact;
1.214 brouard 3198: double agebegin, ageend;
1.126 brouard 3199:
3200: /* Hstepm could be zero and should return the unit matrix */
3201: for (i=1;i<=nlstate+ndeath;i++)
3202: for (j=1;j<=nlstate+ndeath;j++){
3203: oldm[i][j]=(i==j ? 1.0 : 0.0);
3204: po[i][j][0]=(i==j ? 1.0 : 0.0);
3205: }
3206: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3207: for(h=1; h <=nhstepm; h++){
3208: for(d=1; d <=hstepm; d++){
3209: newm=savm;
3210: /* Covariates have to be included here again */
3211: cov[1]=1.;
1.214 brouard 3212: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3213: cov[2]=agexact;
3214: if(nagesqr==1)
1.227 brouard 3215: cov[3]= agexact*agexact;
1.235 brouard 3216: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3217: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3218: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3219: /* 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)); */
3220: }
3221: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3222: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3223: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3224: /* 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]); */
3225: }
3226: for (k=1; k<=cptcovage;k++){
3227: if(Dummy[Tvar[Tage[k]]]){
3228: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3229: } else{
3230: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3231: }
3232: /* 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]); */
3233: }
3234: for (k=1; k<=cptcovprod;k++){ /* */
3235: /* 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]); */
3236: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3237: }
3238: /* for (k=1; k<=cptcovn;k++) */
3239: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3240: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3241: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3242: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3243: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3244:
3245:
1.126 brouard 3246: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3247: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3248: /* right multiplication of oldm by the current matrix */
1.126 brouard 3249: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3250: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3251: /* if((int)age == 70){ */
3252: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3253: /* for(i=1; i<=nlstate+ndeath; i++) { */
3254: /* printf("%d pmmij ",i); */
3255: /* for(j=1;j<=nlstate+ndeath;j++) { */
3256: /* printf("%f ",pmmij[i][j]); */
3257: /* } */
3258: /* printf(" oldm "); */
3259: /* for(j=1;j<=nlstate+ndeath;j++) { */
3260: /* printf("%f ",oldm[i][j]); */
3261: /* } */
3262: /* printf("\n"); */
3263: /* } */
3264: /* } */
1.126 brouard 3265: savm=oldm;
3266: oldm=newm;
3267: }
3268: for(i=1; i<=nlstate+ndeath; i++)
3269: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3270: po[i][j][h]=newm[i][j];
3271: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3272: }
1.128 brouard 3273: /*printf("h=%d ",h);*/
1.126 brouard 3274: } /* end h */
1.267 brouard 3275: /* printf("\n H=%d \n",h); */
1.126 brouard 3276: return po;
3277: }
3278:
1.217 brouard 3279: /************* Higher Back Matrix Product ***************/
1.218 brouard 3280: /* 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 3281: 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 3282: {
1.266 brouard 3283: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3284: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3285: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3286: nhstepm*hstepm matrices.
3287: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3288: (typically every 2 years instead of every month which is too big
1.217 brouard 3289: for the memory).
1.218 brouard 3290: Model is determined by parameters x and covariates have to be
1.266 brouard 3291: included manually here. Then we use a call to bmij(x and cov)
3292: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3293: */
1.217 brouard 3294:
3295: int i, j, d, h, k;
1.266 brouard 3296: double **out, cov[NCOVMAX+1], **bmij();
3297: double **newm, ***newmm;
1.217 brouard 3298: double agexact;
3299: double agebegin, ageend;
1.222 brouard 3300: double **oldm, **savm;
1.217 brouard 3301:
1.266 brouard 3302: newmm=po; /* To be saved */
3303: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3304: /* Hstepm could be zero and should return the unit matrix */
3305: for (i=1;i<=nlstate+ndeath;i++)
3306: for (j=1;j<=nlstate+ndeath;j++){
3307: oldm[i][j]=(i==j ? 1.0 : 0.0);
3308: po[i][j][0]=(i==j ? 1.0 : 0.0);
3309: }
3310: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3311: for(h=1; h <=nhstepm; h++){
3312: for(d=1; d <=hstepm; d++){
3313: newm=savm;
3314: /* Covariates have to be included here again */
3315: cov[1]=1.;
1.271 brouard 3316: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3317: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3318: cov[2]=agexact;
3319: if(nagesqr==1)
1.222 brouard 3320: cov[3]= agexact*agexact;
1.266 brouard 3321: for (k=1; k<=cptcovn;k++){
3322: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3323: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3324: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3325: /* 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)); */
3326: }
1.267 brouard 3327: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3328: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3329: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3330: /* 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]); */
3331: }
3332: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3333: if(Dummy[Tvar[Tage[k]]]){
3334: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3335: } else{
3336: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3337: }
3338: /* 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]); */
3339: }
3340: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3341: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3342: }
1.217 brouard 3343: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3344: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3345:
1.218 brouard 3346: /* Careful transposed matrix */
1.266 brouard 3347: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3348: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3349: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3350: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3351: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3352: /* if((int)age == 70){ */
3353: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3354: /* for(i=1; i<=nlstate+ndeath; i++) { */
3355: /* printf("%d pmmij ",i); */
3356: /* for(j=1;j<=nlstate+ndeath;j++) { */
3357: /* printf("%f ",pmmij[i][j]); */
3358: /* } */
3359: /* printf(" oldm "); */
3360: /* for(j=1;j<=nlstate+ndeath;j++) { */
3361: /* printf("%f ",oldm[i][j]); */
3362: /* } */
3363: /* printf("\n"); */
3364: /* } */
3365: /* } */
3366: savm=oldm;
3367: oldm=newm;
3368: }
3369: for(i=1; i<=nlstate+ndeath; i++)
3370: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3371: po[i][j][h]=newm[i][j];
1.268 brouard 3372: /* if(h==nhstepm) */
3373: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3374: }
1.268 brouard 3375: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3376: } /* end h */
1.268 brouard 3377: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3378: return po;
3379: }
3380:
3381:
1.162 brouard 3382: #ifdef NLOPT
3383: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3384: double fret;
3385: double *xt;
3386: int j;
3387: myfunc_data *d2 = (myfunc_data *) pd;
3388: /* xt = (p1-1); */
3389: xt=vector(1,n);
3390: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3391:
3392: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3393: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3394: printf("Function = %.12lf ",fret);
3395: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3396: printf("\n");
3397: free_vector(xt,1,n);
3398: return fret;
3399: }
3400: #endif
1.126 brouard 3401:
3402: /*************** log-likelihood *************/
3403: double func( double *x)
3404: {
1.226 brouard 3405: int i, ii, j, k, mi, d, kk;
3406: int ioffset=0;
3407: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3408: double **out;
3409: double lli; /* Individual log likelihood */
3410: int s1, s2;
1.228 brouard 3411: 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 3412: double bbh, survp;
3413: long ipmx;
3414: double agexact;
3415: /*extern weight */
3416: /* We are differentiating ll according to initial status */
3417: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3418: /*for(i=1;i<imx;i++)
3419: printf(" %d\n",s[4][i]);
3420: */
1.162 brouard 3421:
1.226 brouard 3422: ++countcallfunc;
1.162 brouard 3423:
1.226 brouard 3424: cov[1]=1.;
1.126 brouard 3425:
1.226 brouard 3426: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3427: ioffset=0;
1.226 brouard 3428: if(mle==1){
3429: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3430: /* Computes the values of the ncovmodel covariates of the model
3431: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3432: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3433: to be observed in j being in i according to the model.
3434: */
1.243 brouard 3435: ioffset=2+nagesqr ;
1.233 brouard 3436: /* Fixed */
1.234 brouard 3437: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3438: 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)*/
3439: }
1.226 brouard 3440: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3441: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3442: has been calculated etc */
3443: /* For an individual i, wav[i] gives the number of effective waves */
3444: /* We compute the contribution to Likelihood of each effective transition
3445: mw[mi][i] is real wave of the mi th effectve wave */
3446: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3447: s2=s[mw[mi+1][i]][i];
3448: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3449: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3450: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3451: */
3452: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3453: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3454: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3455: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3456: }
3457: for (ii=1;ii<=nlstate+ndeath;ii++)
3458: for (j=1;j<=nlstate+ndeath;j++){
3459: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3460: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3461: }
3462: for(d=0; d<dh[mi][i]; d++){
3463: newm=savm;
3464: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3465: cov[2]=agexact;
3466: if(nagesqr==1)
3467: cov[3]= agexact*agexact; /* Should be changed here */
3468: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3469: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3470: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3471: else
3472: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3473: }
3474: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3475: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3476: savm=oldm;
3477: oldm=newm;
3478: } /* end mult */
3479:
3480: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3481: /* But now since version 0.9 we anticipate for bias at large stepm.
3482: * If stepm is larger than one month (smallest stepm) and if the exact delay
3483: * (in months) between two waves is not a multiple of stepm, we rounded to
3484: * the nearest (and in case of equal distance, to the lowest) interval but now
3485: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3486: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3487: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3488: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3489: * -stepm/2 to stepm/2 .
3490: * For stepm=1 the results are the same as for previous versions of Imach.
3491: * For stepm > 1 the results are less biased than in previous versions.
3492: */
1.234 brouard 3493: s1=s[mw[mi][i]][i];
3494: s2=s[mw[mi+1][i]][i];
3495: bbh=(double)bh[mi][i]/(double)stepm;
3496: /* bias bh is positive if real duration
3497: * is higher than the multiple of stepm and negative otherwise.
3498: */
3499: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3500: if( s2 > nlstate){
3501: /* i.e. if s2 is a death state and if the date of death is known
3502: then the contribution to the likelihood is the probability to
3503: die between last step unit time and current step unit time,
3504: which is also equal to probability to die before dh
3505: minus probability to die before dh-stepm .
3506: In version up to 0.92 likelihood was computed
3507: as if date of death was unknown. Death was treated as any other
3508: health state: the date of the interview describes the actual state
3509: and not the date of a change in health state. The former idea was
3510: to consider that at each interview the state was recorded
3511: (healthy, disable or death) and IMaCh was corrected; but when we
3512: introduced the exact date of death then we should have modified
3513: the contribution of an exact death to the likelihood. This new
3514: contribution is smaller and very dependent of the step unit
3515: stepm. It is no more the probability to die between last interview
3516: and month of death but the probability to survive from last
3517: interview up to one month before death multiplied by the
3518: probability to die within a month. Thanks to Chris
3519: Jackson for correcting this bug. Former versions increased
3520: mortality artificially. The bad side is that we add another loop
3521: which slows down the processing. The difference can be up to 10%
3522: lower mortality.
3523: */
3524: /* If, at the beginning of the maximization mostly, the
3525: cumulative probability or probability to be dead is
3526: constant (ie = 1) over time d, the difference is equal to
3527: 0. out[s1][3] = savm[s1][3]: probability, being at state
3528: s1 at precedent wave, to be dead a month before current
3529: wave is equal to probability, being at state s1 at
3530: precedent wave, to be dead at mont of the current
3531: wave. Then the observed probability (that this person died)
3532: is null according to current estimated parameter. In fact,
3533: it should be very low but not zero otherwise the log go to
3534: infinity.
3535: */
1.183 brouard 3536: /* #ifdef INFINITYORIGINAL */
3537: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3538: /* #else */
3539: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3540: /* lli=log(mytinydouble); */
3541: /* else */
3542: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3543: /* #endif */
1.226 brouard 3544: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3545:
1.226 brouard 3546: } else if ( s2==-1 ) { /* alive */
3547: for (j=1,survp=0. ; j<=nlstate; j++)
3548: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3549: /*survp += out[s1][j]; */
3550: lli= log(survp);
3551: }
3552: else if (s2==-4) {
3553: for (j=3,survp=0. ; j<=nlstate; j++)
3554: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3555: lli= log(survp);
3556: }
3557: else if (s2==-5) {
3558: for (j=1,survp=0. ; j<=2; j++)
3559: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3560: lli= log(survp);
3561: }
3562: else{
3563: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3564: /* 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 */
3565: }
3566: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3567: /*if(lli ==000.0)*/
3568: /*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); */
3569: ipmx +=1;
3570: sw += weight[i];
3571: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3572: /* if (lli < log(mytinydouble)){ */
3573: /* 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); */
3574: /* 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]); */
3575: /* } */
3576: } /* end of wave */
3577: } /* end of individual */
3578: } else if(mle==2){
3579: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3580: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3581: for(mi=1; mi<= wav[i]-1; mi++){
3582: for (ii=1;ii<=nlstate+ndeath;ii++)
3583: for (j=1;j<=nlstate+ndeath;j++){
3584: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3585: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3586: }
3587: for(d=0; d<=dh[mi][i]; d++){
3588: newm=savm;
3589: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3590: cov[2]=agexact;
3591: if(nagesqr==1)
3592: cov[3]= agexact*agexact;
3593: for (kk=1; kk<=cptcovage;kk++) {
3594: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3595: }
3596: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3597: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3598: savm=oldm;
3599: oldm=newm;
3600: } /* end mult */
3601:
3602: s1=s[mw[mi][i]][i];
3603: s2=s[mw[mi+1][i]][i];
3604: bbh=(double)bh[mi][i]/(double)stepm;
3605: 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 */
3606: ipmx +=1;
3607: sw += weight[i];
3608: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3609: } /* end of wave */
3610: } /* end of individual */
3611: } else if(mle==3){ /* exponential inter-extrapolation */
3612: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3613: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3614: for(mi=1; mi<= wav[i]-1; mi++){
3615: for (ii=1;ii<=nlstate+ndeath;ii++)
3616: for (j=1;j<=nlstate+ndeath;j++){
3617: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3618: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3619: }
3620: for(d=0; d<dh[mi][i]; d++){
3621: newm=savm;
3622: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3623: cov[2]=agexact;
3624: if(nagesqr==1)
3625: cov[3]= agexact*agexact;
3626: for (kk=1; kk<=cptcovage;kk++) {
3627: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3628: }
3629: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3630: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3631: savm=oldm;
3632: oldm=newm;
3633: } /* end mult */
3634:
3635: s1=s[mw[mi][i]][i];
3636: s2=s[mw[mi+1][i]][i];
3637: bbh=(double)bh[mi][i]/(double)stepm;
3638: 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 */
3639: ipmx +=1;
3640: sw += weight[i];
3641: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3642: } /* end of wave */
3643: } /* end of individual */
3644: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3645: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3646: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3647: for(mi=1; mi<= wav[i]-1; mi++){
3648: for (ii=1;ii<=nlstate+ndeath;ii++)
3649: for (j=1;j<=nlstate+ndeath;j++){
3650: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3651: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3652: }
3653: for(d=0; d<dh[mi][i]; d++){
3654: newm=savm;
3655: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3656: cov[2]=agexact;
3657: if(nagesqr==1)
3658: cov[3]= agexact*agexact;
3659: for (kk=1; kk<=cptcovage;kk++) {
3660: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3661: }
1.126 brouard 3662:
1.226 brouard 3663: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3664: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3665: savm=oldm;
3666: oldm=newm;
3667: } /* end mult */
3668:
3669: s1=s[mw[mi][i]][i];
3670: s2=s[mw[mi+1][i]][i];
3671: if( s2 > nlstate){
3672: lli=log(out[s1][s2] - savm[s1][s2]);
3673: } else if ( s2==-1 ) { /* alive */
3674: for (j=1,survp=0. ; j<=nlstate; j++)
3675: survp += out[s1][j];
3676: lli= log(survp);
3677: }else{
3678: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3679: }
3680: ipmx +=1;
3681: sw += weight[i];
3682: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3683: /* 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 3684: } /* end of wave */
3685: } /* end of individual */
3686: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3687: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3688: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3689: for(mi=1; mi<= wav[i]-1; mi++){
3690: for (ii=1;ii<=nlstate+ndeath;ii++)
3691: for (j=1;j<=nlstate+ndeath;j++){
3692: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3693: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3694: }
3695: for(d=0; d<dh[mi][i]; d++){
3696: newm=savm;
3697: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3698: cov[2]=agexact;
3699: if(nagesqr==1)
3700: cov[3]= agexact*agexact;
3701: for (kk=1; kk<=cptcovage;kk++) {
3702: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3703: }
1.126 brouard 3704:
1.226 brouard 3705: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3706: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3707: savm=oldm;
3708: oldm=newm;
3709: } /* end mult */
3710:
3711: s1=s[mw[mi][i]][i];
3712: s2=s[mw[mi+1][i]][i];
3713: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3714: ipmx +=1;
3715: sw += weight[i];
3716: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3717: /*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]);*/
3718: } /* end of wave */
3719: } /* end of individual */
3720: } /* End of if */
3721: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3722: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3723: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3724: return -l;
1.126 brouard 3725: }
3726:
3727: /*************** log-likelihood *************/
3728: double funcone( double *x)
3729: {
1.228 brouard 3730: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3731: int i, ii, j, k, mi, d, kk;
1.228 brouard 3732: int ioffset=0;
1.131 brouard 3733: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3734: double **out;
3735: double lli; /* Individual log likelihood */
3736: double llt;
3737: int s1, s2;
1.228 brouard 3738: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3739:
1.126 brouard 3740: double bbh, survp;
1.187 brouard 3741: double agexact;
1.214 brouard 3742: double agebegin, ageend;
1.126 brouard 3743: /*extern weight */
3744: /* We are differentiating ll according to initial status */
3745: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3746: /*for(i=1;i<imx;i++)
3747: printf(" %d\n",s[4][i]);
3748: */
3749: cov[1]=1.;
3750:
3751: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3752: ioffset=0;
3753: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3754: /* ioffset=2+nagesqr+cptcovage; */
3755: ioffset=2+nagesqr;
1.232 brouard 3756: /* Fixed */
1.224 brouard 3757: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3758: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3759: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3760: 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)*/
3761: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3762: /* cov[2+6]=covar[Tvar[6]][i]; */
3763: /* cov[2+6]=covar[2][i]; V2 */
3764: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3765: /* cov[2+7]=covar[Tvar[7]][i]; */
3766: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3767: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3768: /* cov[2+9]=covar[Tvar[9]][i]; */
3769: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3770: }
1.232 brouard 3771: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3772: /* 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?)*\/ */
3773: /* } */
1.231 brouard 3774: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3775: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3776: /* } */
1.225 brouard 3777:
1.233 brouard 3778:
3779: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3780: /* Wave varying (but not age varying) */
3781: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3782: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3783: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3784: }
1.232 brouard 3785: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3786: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3787: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3788: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3789: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3790: /* 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 3791: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3792: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3793: /* /\* 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]); *\/ */
3794: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3795: /* } */
1.126 brouard 3796: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3797: for (j=1;j<=nlstate+ndeath;j++){
3798: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3799: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3800: }
1.214 brouard 3801:
3802: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3803: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3804: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3805: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3806: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3807: and mw[mi+1][i]. dh depends on stepm.*/
3808: newm=savm;
1.247 brouard 3809: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3810: cov[2]=agexact;
3811: if(nagesqr==1)
3812: cov[3]= agexact*agexact;
3813: for (kk=1; kk<=cptcovage;kk++) {
3814: if(!FixedV[Tvar[Tage[kk]]])
3815: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3816: else
3817: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3818: }
3819: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3820: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3821: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3822: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3823: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3824: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3825: savm=oldm;
3826: oldm=newm;
1.126 brouard 3827: } /* end mult */
3828:
3829: s1=s[mw[mi][i]][i];
3830: s2=s[mw[mi+1][i]][i];
1.217 brouard 3831: /* if(s2==-1){ */
1.268 brouard 3832: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3833: /* /\* exit(1); *\/ */
3834: /* } */
1.126 brouard 3835: bbh=(double)bh[mi][i]/(double)stepm;
3836: /* bias is positive if real duration
3837: * is higher than the multiple of stepm and negative otherwise.
3838: */
3839: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3840: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3841: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3842: for (j=1,survp=0. ; j<=nlstate; j++)
3843: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3844: lli= log(survp);
1.126 brouard 3845: }else if (mle==1){
1.242 brouard 3846: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3847: } else if(mle==2){
1.242 brouard 3848: 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 3849: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3850: 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 3851: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3852: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3853: } else{ /* mle=0 back to 1 */
1.242 brouard 3854: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3855: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3856: } /* End of if */
3857: ipmx +=1;
3858: sw += weight[i];
3859: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3860: /*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 3861: if(globpr){
1.246 brouard 3862: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3863: %11.6f %11.6f %11.6f ", \
1.242 brouard 3864: 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 3865: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3866: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3867: llt +=ll[k]*gipmx/gsw;
3868: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3869: }
3870: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3871: }
1.232 brouard 3872: } /* end of wave */
3873: } /* end of individual */
3874: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3875: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3876: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3877: if(globpr==0){ /* First time we count the contributions and weights */
3878: gipmx=ipmx;
3879: gsw=sw;
3880: }
3881: return -l;
1.126 brouard 3882: }
3883:
3884:
3885: /*************** function likelione ***********/
3886: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*funcone)(double []))
3887: {
3888: /* This routine should help understanding what is done with
3889: the selection of individuals/waves and
3890: to check the exact contribution to the likelihood.
3891: Plotting could be done.
3892: */
3893: int k;
3894:
3895: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3896: strcpy(fileresilk,"ILK_");
1.202 brouard 3897: strcat(fileresilk,fileresu);
1.126 brouard 3898: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3899: printf("Problem with resultfile: %s\n", fileresilk);
3900: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3901: }
1.214 brouard 3902: 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");
3903: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3904: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3905: for(k=1; k<=nlstate; k++)
3906: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3907: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3908: }
3909:
3910: *fretone=(*funcone)(p);
3911: if(*globpri !=0){
3912: fclose(ficresilk);
1.205 brouard 3913: if (mle ==0)
3914: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3915: else if(mle >=1)
3916: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3917: 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 3918: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 3919:
3920: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3921: 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 3922: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3923: }
1.207 brouard 3924: 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 3925: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3926: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3927: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3928: fflush(fichtm);
1.205 brouard 3929: }
1.126 brouard 3930: return;
3931: }
3932:
3933:
3934: /*********** Maximum Likelihood Estimation ***************/
3935:
3936: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3937: {
1.165 brouard 3938: int i,j, iter=0;
1.126 brouard 3939: double **xi;
3940: double fret;
3941: double fretone; /* Only one call to likelihood */
3942: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3943:
3944: #ifdef NLOPT
3945: int creturn;
3946: nlopt_opt opt;
3947: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3948: double *lb;
3949: double minf; /* the minimum objective value, upon return */
3950: double * p1; /* Shifted parameters from 0 instead of 1 */
3951: myfunc_data dinst, *d = &dinst;
3952: #endif
3953:
3954:
1.126 brouard 3955: xi=matrix(1,npar,1,npar);
3956: for (i=1;i<=npar;i++)
3957: for (j=1;j<=npar;j++)
3958: xi[i][j]=(i==j ? 1.0 : 0.0);
3959: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3960: strcpy(filerespow,"POW_");
1.126 brouard 3961: strcat(filerespow,fileres);
3962: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3963: printf("Problem with resultfile: %s\n", filerespow);
3964: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3965: }
3966: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3967: for (i=1;i<=nlstate;i++)
3968: for(j=1;j<=nlstate+ndeath;j++)
3969: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3970: fprintf(ficrespow,"\n");
1.162 brouard 3971: #ifdef POWELL
1.126 brouard 3972: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3973: #endif
1.126 brouard 3974:
1.162 brouard 3975: #ifdef NLOPT
3976: #ifdef NEWUOA
3977: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
3978: #else
3979: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
3980: #endif
3981: lb=vector(0,npar-1);
3982: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
3983: nlopt_set_lower_bounds(opt, lb);
3984: nlopt_set_initial_step1(opt, 0.1);
3985:
3986: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
3987: d->function = func;
3988: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
3989: nlopt_set_min_objective(opt, myfunc, d);
3990: nlopt_set_xtol_rel(opt, ftol);
3991: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
3992: printf("nlopt failed! %d\n",creturn);
3993: }
3994: else {
3995: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
3996: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
3997: iter=1; /* not equal */
3998: }
3999: nlopt_destroy(opt);
4000: #endif
1.126 brouard 4001: free_matrix(xi,1,npar,1,npar);
4002: fclose(ficrespow);
1.203 brouard 4003: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4004: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4005: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4006:
4007: }
4008:
4009: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4010: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4011: {
4012: double **a,**y,*x,pd;
1.203 brouard 4013: /* double **hess; */
1.164 brouard 4014: int i, j;
1.126 brouard 4015: int *indx;
4016:
4017: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4018: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4019: void lubksb(double **a, int npar, int *indx, double b[]) ;
4020: void ludcmp(double **a, int npar, int *indx, double *d) ;
4021: double gompertz(double p[]);
1.203 brouard 4022: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4023:
4024: printf("\nCalculation of the hessian matrix. Wait...\n");
4025: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4026: for (i=1;i<=npar;i++){
1.203 brouard 4027: printf("%d-",i);fflush(stdout);
4028: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4029:
4030: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4031:
4032: /* printf(" %f ",p[i]);
4033: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4034: }
4035:
4036: for (i=1;i<=npar;i++) {
4037: for (j=1;j<=npar;j++) {
4038: if (j>i) {
1.203 brouard 4039: printf(".%d-%d",i,j);fflush(stdout);
4040: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4041: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4042:
4043: hess[j][i]=hess[i][j];
4044: /*printf(" %lf ",hess[i][j]);*/
4045: }
4046: }
4047: }
4048: printf("\n");
4049: fprintf(ficlog,"\n");
4050:
4051: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4052: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4053:
4054: a=matrix(1,npar,1,npar);
4055: y=matrix(1,npar,1,npar);
4056: x=vector(1,npar);
4057: indx=ivector(1,npar);
4058: for (i=1;i<=npar;i++)
4059: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4060: ludcmp(a,npar,indx,&pd);
4061:
4062: for (j=1;j<=npar;j++) {
4063: for (i=1;i<=npar;i++) x[i]=0;
4064: x[j]=1;
4065: lubksb(a,npar,indx,x);
4066: for (i=1;i<=npar;i++){
4067: matcov[i][j]=x[i];
4068: }
4069: }
4070:
4071: printf("\n#Hessian matrix#\n");
4072: fprintf(ficlog,"\n#Hessian matrix#\n");
4073: for (i=1;i<=npar;i++) {
4074: for (j=1;j<=npar;j++) {
1.203 brouard 4075: printf("%.6e ",hess[i][j]);
4076: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4077: }
4078: printf("\n");
4079: fprintf(ficlog,"\n");
4080: }
4081:
1.203 brouard 4082: /* printf("\n#Covariance matrix#\n"); */
4083: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4084: /* for (i=1;i<=npar;i++) { */
4085: /* for (j=1;j<=npar;j++) { */
4086: /* printf("%.6e ",matcov[i][j]); */
4087: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4088: /* } */
4089: /* printf("\n"); */
4090: /* fprintf(ficlog,"\n"); */
4091: /* } */
4092:
1.126 brouard 4093: /* Recompute Inverse */
1.203 brouard 4094: /* for (i=1;i<=npar;i++) */
4095: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4096: /* ludcmp(a,npar,indx,&pd); */
4097:
4098: /* printf("\n#Hessian matrix recomputed#\n"); */
4099:
4100: /* for (j=1;j<=npar;j++) { */
4101: /* for (i=1;i<=npar;i++) x[i]=0; */
4102: /* x[j]=1; */
4103: /* lubksb(a,npar,indx,x); */
4104: /* for (i=1;i<=npar;i++){ */
4105: /* y[i][j]=x[i]; */
4106: /* printf("%.3e ",y[i][j]); */
4107: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4108: /* } */
4109: /* printf("\n"); */
4110: /* fprintf(ficlog,"\n"); */
4111: /* } */
4112:
4113: /* Verifying the inverse matrix */
4114: #ifdef DEBUGHESS
4115: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4116:
1.203 brouard 4117: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4118: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4119:
4120: for (j=1;j<=npar;j++) {
4121: for (i=1;i<=npar;i++){
1.203 brouard 4122: printf("%.2f ",y[i][j]);
4123: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4124: }
4125: printf("\n");
4126: fprintf(ficlog,"\n");
4127: }
1.203 brouard 4128: #endif
1.126 brouard 4129:
4130: free_matrix(a,1,npar,1,npar);
4131: free_matrix(y,1,npar,1,npar);
4132: free_vector(x,1,npar);
4133: free_ivector(indx,1,npar);
1.203 brouard 4134: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4135:
4136:
4137: }
4138:
4139: /*************** hessian matrix ****************/
4140: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4141: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4142: int i;
4143: int l=1, lmax=20;
1.203 brouard 4144: double k1,k2, res, fx;
1.132 brouard 4145: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4146: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4147: int k=0,kmax=10;
4148: double l1;
4149:
4150: fx=func(x);
4151: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4152: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4153: l1=pow(10,l);
4154: delts=delt;
4155: for(k=1 ; k <kmax; k=k+1){
4156: delt = delta*(l1*k);
4157: p2[theta]=x[theta] +delt;
1.145 brouard 4158: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4159: p2[theta]=x[theta]-delt;
4160: k2=func(p2)-fx;
4161: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4162: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4163:
1.203 brouard 4164: #ifdef DEBUGHESSII
1.126 brouard 4165: 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);
4166: 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);
4167: #endif
4168: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4169: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4170: k=kmax;
4171: }
4172: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4173: k=kmax; l=lmax*10;
1.126 brouard 4174: }
4175: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4176: delts=delt;
4177: }
1.203 brouard 4178: } /* End loop k */
1.126 brouard 4179: }
4180: delti[theta]=delts;
4181: return res;
4182:
4183: }
4184:
1.203 brouard 4185: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4186: {
4187: int i;
1.164 brouard 4188: int l=1, lmax=20;
1.126 brouard 4189: double k1,k2,k3,k4,res,fx;
1.132 brouard 4190: double p2[MAXPARM+1];
1.203 brouard 4191: int k, kmax=1;
4192: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4193:
4194: int firstime=0;
1.203 brouard 4195:
1.126 brouard 4196: fx=func(x);
1.203 brouard 4197: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4198: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4199: p2[thetai]=x[thetai]+delti[thetai]*k;
4200: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4201: k1=func(p2)-fx;
4202:
1.203 brouard 4203: p2[thetai]=x[thetai]+delti[thetai]*k;
4204: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4205: k2=func(p2)-fx;
4206:
1.203 brouard 4207: p2[thetai]=x[thetai]-delti[thetai]*k;
4208: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4209: k3=func(p2)-fx;
4210:
1.203 brouard 4211: p2[thetai]=x[thetai]-delti[thetai]*k;
4212: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4213: k4=func(p2)-fx;
1.203 brouard 4214: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4215: if(k1*k2*k3*k4 <0.){
1.208 brouard 4216: firstime=1;
1.203 brouard 4217: kmax=kmax+10;
1.208 brouard 4218: }
4219: if(kmax >=10 || firstime ==1){
1.246 brouard 4220: 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);
4221: 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 4222: 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);
4223: 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);
4224: }
4225: #ifdef DEBUGHESSIJ
4226: v1=hess[thetai][thetai];
4227: v2=hess[thetaj][thetaj];
4228: cv12=res;
4229: /* Computing eigen value of Hessian matrix */
4230: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4231: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4232: if ((lc2 <0) || (lc1 <0) ){
4233: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4234: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4235: 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);
4236: 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);
4237: }
1.126 brouard 4238: #endif
4239: }
4240: return res;
4241: }
4242:
1.203 brouard 4243: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4244: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4245: /* { */
4246: /* int i; */
4247: /* int l=1, lmax=20; */
4248: /* double k1,k2,k3,k4,res,fx; */
4249: /* double p2[MAXPARM+1]; */
4250: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4251: /* int k=0,kmax=10; */
4252: /* double l1; */
4253:
4254: /* fx=func(x); */
4255: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4256: /* l1=pow(10,l); */
4257: /* delts=delt; */
4258: /* for(k=1 ; k <kmax; k=k+1){ */
4259: /* delt = delti*(l1*k); */
4260: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4261: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4262: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4263: /* k1=func(p2)-fx; */
4264:
4265: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4266: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4267: /* k2=func(p2)-fx; */
4268:
4269: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4270: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4271: /* k3=func(p2)-fx; */
4272:
4273: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4274: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4275: /* k4=func(p2)-fx; */
4276: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4277: /* #ifdef DEBUGHESSIJ */
4278: /* 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); */
4279: /* 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); */
4280: /* #endif */
4281: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4282: /* k=kmax; */
4283: /* } */
4284: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4285: /* k=kmax; l=lmax*10; */
4286: /* } */
4287: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4288: /* delts=delt; */
4289: /* } */
4290: /* } /\* End loop k *\/ */
4291: /* } */
4292: /* delti[theta]=delts; */
4293: /* return res; */
4294: /* } */
4295:
4296:
1.126 brouard 4297: /************** Inverse of matrix **************/
4298: void ludcmp(double **a, int n, int *indx, double *d)
4299: {
4300: int i,imax,j,k;
4301: double big,dum,sum,temp;
4302: double *vv;
4303:
4304: vv=vector(1,n);
4305: *d=1.0;
4306: for (i=1;i<=n;i++) {
4307: big=0.0;
4308: for (j=1;j<=n;j++)
4309: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4310: if (big == 0.0){
4311: printf(" Singular Hessian matrix at row %d:\n",i);
4312: for (j=1;j<=n;j++) {
4313: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4314: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4315: }
4316: fflush(ficlog);
4317: fclose(ficlog);
4318: nrerror("Singular matrix in routine ludcmp");
4319: }
1.126 brouard 4320: vv[i]=1.0/big;
4321: }
4322: for (j=1;j<=n;j++) {
4323: for (i=1;i<j;i++) {
4324: sum=a[i][j];
4325: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4326: a[i][j]=sum;
4327: }
4328: big=0.0;
4329: for (i=j;i<=n;i++) {
4330: sum=a[i][j];
4331: for (k=1;k<j;k++)
4332: sum -= a[i][k]*a[k][j];
4333: a[i][j]=sum;
4334: if ( (dum=vv[i]*fabs(sum)) >= big) {
4335: big=dum;
4336: imax=i;
4337: }
4338: }
4339: if (j != imax) {
4340: for (k=1;k<=n;k++) {
4341: dum=a[imax][k];
4342: a[imax][k]=a[j][k];
4343: a[j][k]=dum;
4344: }
4345: *d = -(*d);
4346: vv[imax]=vv[j];
4347: }
4348: indx[j]=imax;
4349: if (a[j][j] == 0.0) a[j][j]=TINY;
4350: if (j != n) {
4351: dum=1.0/(a[j][j]);
4352: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4353: }
4354: }
4355: free_vector(vv,1,n); /* Doesn't work */
4356: ;
4357: }
4358:
4359: void lubksb(double **a, int n, int *indx, double b[])
4360: {
4361: int i,ii=0,ip,j;
4362: double sum;
4363:
4364: for (i=1;i<=n;i++) {
4365: ip=indx[i];
4366: sum=b[ip];
4367: b[ip]=b[i];
4368: if (ii)
4369: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4370: else if (sum) ii=i;
4371: b[i]=sum;
4372: }
4373: for (i=n;i>=1;i--) {
4374: sum=b[i];
4375: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4376: b[i]=sum/a[i][i];
4377: }
4378: }
4379:
4380: void pstamp(FILE *fichier)
4381: {
1.196 brouard 4382: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4383: }
4384:
1.253 brouard 4385:
4386:
1.126 brouard 4387: /************ Frequencies ********************/
1.251 brouard 4388: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4389: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4390: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4391: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4392:
1.265 brouard 4393: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4394: int iind=0, iage=0;
4395: int mi; /* Effective wave */
4396: int first;
4397: double ***freq; /* Frequencies */
1.268 brouard 4398: 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 */
4399: 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 4400: double *meanq, *stdq, *idq;
1.226 brouard 4401: double **meanqt;
4402: double *pp, **prop, *posprop, *pospropt;
4403: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4404: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4405: double agebegin, ageend;
4406:
4407: pp=vector(1,nlstate);
1.251 brouard 4408: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4409: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4410: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4411: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4412: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4413: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4414: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4415: meanqt=matrix(1,lastpass,1,nqtveff);
4416: strcpy(fileresp,"P_");
4417: strcat(fileresp,fileresu);
4418: /*strcat(fileresphtm,fileresu);*/
4419: if((ficresp=fopen(fileresp,"w"))==NULL) {
4420: printf("Problem with prevalence resultfile: %s\n", fileresp);
4421: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4422: exit(0);
4423: }
1.240 brouard 4424:
1.226 brouard 4425: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4426: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4427: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4428: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4429: fflush(ficlog);
4430: exit(70);
4431: }
4432: else{
4433: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4434: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4435: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4436: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4437: }
1.237 brouard 4438: 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 4439:
1.226 brouard 4440: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4441: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4442: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4443: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4444: fflush(ficlog);
4445: exit(70);
1.240 brouard 4446: } else{
1.226 brouard 4447: 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 4448: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4449: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4450: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4451: }
1.240 brouard 4452: 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);
4453:
1.253 brouard 4454: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4455: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4456: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4457: j1=0;
1.126 brouard 4458:
1.227 brouard 4459: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4460: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4461: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4462:
4463:
1.226 brouard 4464: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4465: reference=low_education V1=0,V2=0
4466: med_educ V1=1 V2=0,
4467: high_educ V1=0 V2=1
4468: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4469: */
1.249 brouard 4470: dateintsum=0;
4471: k2cpt=0;
4472:
1.253 brouard 4473: if(cptcoveff == 0 )
1.265 brouard 4474: nl=1; /* Constant and age model only */
1.253 brouard 4475: else
4476: nl=2;
1.265 brouard 4477:
4478: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4479: /* Loop on nj=1 or 2 if dummy covariates j!=0
4480: * Loop on j1(1 to 2**cptcoveff) covariate combination
4481: * freq[s1][s2][iage] =0.
4482: * Loop on iind
4483: * ++freq[s1][s2][iage] weighted
4484: * end iind
4485: * if covariate and j!0
4486: * headers Variable on one line
4487: * endif cov j!=0
4488: * header of frequency table by age
4489: * Loop on age
4490: * pp[s1]+=freq[s1][s2][iage] weighted
4491: * pos+=freq[s1][s2][iage] weighted
4492: * Loop on s1 initial state
4493: * fprintf(ficresp
4494: * end s1
4495: * end age
4496: * if j!=0 computes starting values
4497: * end compute starting values
4498: * end j1
4499: * end nl
4500: */
1.253 brouard 4501: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4502: if(nj==1)
4503: j=0; /* First pass for the constant */
1.265 brouard 4504: else{
1.253 brouard 4505: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4506: }
1.251 brouard 4507: first=1;
1.265 brouard 4508: 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 4509: posproptt=0.;
4510: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4511: scanf("%d", i);*/
4512: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4513: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4514: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4515: freq[i][s2][m]=0;
1.251 brouard 4516:
4517: for (i=1; i<=nlstate; i++) {
1.240 brouard 4518: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4519: prop[i][m]=0;
4520: posprop[i]=0;
4521: pospropt[i]=0;
4522: }
1.283 brouard 4523: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4524: idq[z1]=0.;
4525: meanq[z1]=0.;
4526: stdq[z1]=0.;
1.283 brouard 4527: }
4528: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4529: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4530: /* meanqt[m][z1]=0.; */
4531: /* } */
4532: /* } */
1.251 brouard 4533: /* dateintsum=0; */
4534: /* k2cpt=0; */
4535:
1.265 brouard 4536: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4537: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4538: bool=1;
4539: if(j !=0){
4540: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4541: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4542: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4543: /* if(Tvaraff[z1] ==-20){ */
4544: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4545: /* }else if(Tvaraff[z1] ==-10){ */
4546: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4547: /* }else */
4548: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4549: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4550: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4551: /* 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",
4552: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4553: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4554: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4555: } /* Onlyf fixed */
4556: } /* end z1 */
4557: } /* cptcovn > 0 */
4558: } /* end any */
4559: }/* end j==0 */
1.265 brouard 4560: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4561: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4562: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4563: m=mw[mi][iind];
4564: if(j!=0){
4565: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4566: for (z1=1; z1<=cptcoveff; z1++) {
4567: if( Fixed[Tmodelind[z1]]==1){
4568: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4569: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4570: value is -1, we don't select. It differs from the
4571: constant and age model which counts them. */
4572: bool=0; /* not selected */
4573: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4574: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4575: bool=0;
4576: }
4577: }
4578: }
4579: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4580: } /* end j==0 */
4581: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4582: if(bool==1){ /*Selected */
1.251 brouard 4583: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4584: and mw[mi+1][iind]. dh depends on stepm. */
4585: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4586: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4587: if(m >=firstpass && m <=lastpass){
4588: k2=anint[m][iind]+(mint[m][iind]/12.);
4589: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4590: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4591: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4592: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4593: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4594: if (m<lastpass) {
4595: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4596: /* 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]); */
4597: if(s[m][iind]==-1)
4598: 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.));
4599: freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
1.284 brouard 4600: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean */
4601: idq[z1]=idq[z1]+weight[iind];
4602: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
4603: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
4604: }
1.251 brouard 4605: /* if((int)agev[m][iind] == 55) */
4606: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4607: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4608: 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 4609: }
1.251 brouard 4610: } /* end if between passes */
4611: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4612: dateintsum=dateintsum+k2; /* on all covariates ?*/
4613: k2cpt++;
4614: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4615: }
1.251 brouard 4616: }else{
4617: bool=1;
4618: }/* end bool 2 */
4619: } /* end m */
1.284 brouard 4620: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
4621: /* idq[z1]=idq[z1]+weight[iind]; */
4622: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
4623: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
4624: /* } */
1.251 brouard 4625: } /* end bool */
4626: } /* end iind = 1 to imx */
4627: /* prop[s][age] is feeded for any initial and valid live state as well as
4628: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4629:
4630:
4631: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4632: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4633: pstamp(ficresp);
1.251 brouard 4634: if (cptcoveff>0 && j!=0){
1.265 brouard 4635: pstamp(ficresp);
1.251 brouard 4636: printf( "\n#********** Variable ");
4637: fprintf(ficresp, "\n#********** Variable ");
4638: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4639: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4640: fprintf(ficlog, "\n#********** Variable ");
4641: for (z1=1; z1<=cptcoveff; z1++){
4642: if(!FixedV[Tvaraff[z1]]){
4643: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4644: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4645: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4646: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4647: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4648: }else{
1.251 brouard 4649: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4650: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4651: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4652: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4653: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4654: }
4655: }
4656: printf( "**********\n#");
4657: fprintf(ficresp, "**********\n#");
4658: fprintf(ficresphtm, "**********</h3>\n");
4659: fprintf(ficresphtmfr, "**********</h3>\n");
4660: fprintf(ficlog, "**********\n");
4661: }
1.284 brouard 4662: /*
4663: Printing means of quantitative variables if any
4664: */
4665: for (z1=1; z1<= nqfveff; z1++) {
1.285 brouard 4666: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.0f individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.284 brouard 4667: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
4668: if(weightopt==1){
4669: printf(" Weighted mean and standard deviation of");
4670: fprintf(ficlog," Weighted mean and standard deviation of");
4671: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
4672: }
1.285 brouard 4673: printf(" fixed quantitative variable V%d on %.0f representatives of the population : %6.3g (%6.3g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt((stdq[z1]-meanq[z1]*meanq[z1]/idq[z1])/idq[z1]));
4674: fprintf(ficlog," fixed quantitative variable V%d on %.0f representatives of the population : %6.3g (%6.3g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt((stdq[z1]-meanq[z1]*meanq[z1]/idq[z1])/idq[z1]));
4675: fprintf(ficresphtmfr," fixed quantitative variable V%d on %.0f representatives of the population : %6.3g (%6.3g)<p>\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt((stdq[z1]-meanq[z1]*meanq[z1]/idq[z1])/idq[z1]));
1.284 brouard 4676: }
4677: /* for (z1=1; z1<= nqtveff; z1++) { */
4678: /* for(m=1;m<=lastpass;m++){ */
4679: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
4680: /* } */
4681: /* } */
1.283 brouard 4682:
1.251 brouard 4683: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4684: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4685: fprintf(ficresp, " Age");
4686: 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 4687: for(i=1; i<=nlstate;i++) {
1.265 brouard 4688: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4689: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4690: }
1.265 brouard 4691: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4692: fprintf(ficresphtm, "\n");
4693:
4694: /* Header of frequency table by age */
4695: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4696: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4697: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4698: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4699: if(s2!=0 && m!=0)
4700: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4701: }
1.226 brouard 4702: }
1.251 brouard 4703: fprintf(ficresphtmfr, "\n");
4704:
4705: /* For each age */
4706: for(iage=iagemin; iage <= iagemax+3; iage++){
4707: fprintf(ficresphtm,"<tr>");
4708: if(iage==iagemax+1){
4709: fprintf(ficlog,"1");
4710: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4711: }else if(iage==iagemax+2){
4712: fprintf(ficlog,"0");
4713: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4714: }else if(iage==iagemax+3){
4715: fprintf(ficlog,"Total");
4716: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4717: }else{
1.240 brouard 4718: if(first==1){
1.251 brouard 4719: first=0;
4720: printf("See log file for details...\n");
4721: }
4722: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4723: fprintf(ficlog,"Age %d", iage);
4724: }
1.265 brouard 4725: for(s1=1; s1 <=nlstate ; s1++){
4726: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4727: pp[s1] += freq[s1][m][iage];
1.251 brouard 4728: }
1.265 brouard 4729: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4730: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4731: pos += freq[s1][m][iage];
4732: if(pp[s1]>=1.e-10){
1.251 brouard 4733: if(first==1){
1.265 brouard 4734: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4735: }
1.265 brouard 4736: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4737: }else{
4738: if(first==1)
1.265 brouard 4739: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4740: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4741: }
4742: }
4743:
1.265 brouard 4744: for(s1=1; s1 <=nlstate ; s1++){
4745: /* posprop[s1]=0; */
4746: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4747: pp[s1] += freq[s1][m][iage];
4748: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4749:
4750: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4751: pos += pp[s1]; /* pos is the total number of transitions until this age */
4752: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4753: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4754: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4755: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4756: }
4757:
4758: /* Writing ficresp */
4759: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4760: if( iage <= iagemax){
4761: fprintf(ficresp," %d",iage);
4762: }
4763: }else if( nj==2){
4764: if( iage <= iagemax){
4765: fprintf(ficresp," %d",iage);
4766: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4767: }
1.240 brouard 4768: }
1.265 brouard 4769: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4770: if(pos>=1.e-5){
1.251 brouard 4771: if(first==1)
1.265 brouard 4772: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4773: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4774: }else{
4775: if(first==1)
1.265 brouard 4776: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4777: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4778: }
4779: if( iage <= iagemax){
4780: if(pos>=1.e-5){
1.265 brouard 4781: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4782: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4783: }else if( nj==2){
4784: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4785: }
4786: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4787: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4788: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4789: } else{
4790: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4791: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4792: }
1.240 brouard 4793: }
1.265 brouard 4794: pospropt[s1] +=posprop[s1];
4795: } /* end loop s1 */
1.251 brouard 4796: /* pospropt=0.; */
1.265 brouard 4797: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4798: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4799: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4800: if(first==1){
1.265 brouard 4801: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4802: }
1.265 brouard 4803: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4804: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4805: }
1.265 brouard 4806: if(s1!=0 && m!=0)
4807: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4808: }
1.265 brouard 4809: } /* end loop s1 */
1.251 brouard 4810: posproptt=0.;
1.265 brouard 4811: for(s1=1; s1 <=nlstate; s1++){
4812: posproptt += pospropt[s1];
1.251 brouard 4813: }
4814: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4815: fprintf(ficresphtm,"</tr>\n");
4816: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4817: if(iage <= iagemax)
4818: fprintf(ficresp,"\n");
1.240 brouard 4819: }
1.251 brouard 4820: if(first==1)
4821: printf("Others in log...\n");
4822: fprintf(ficlog,"\n");
4823: } /* end loop age iage */
1.265 brouard 4824:
1.251 brouard 4825: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4826: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4827: if(posproptt < 1.e-5){
1.265 brouard 4828: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4829: }else{
1.265 brouard 4830: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4831: }
1.226 brouard 4832: }
1.251 brouard 4833: fprintf(ficresphtm,"</tr>\n");
4834: fprintf(ficresphtm,"</table>\n");
4835: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4836: if(posproptt < 1.e-5){
1.251 brouard 4837: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4838: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4839: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4840: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4841: invalidvarcomb[j1]=1;
1.226 brouard 4842: }else{
1.251 brouard 4843: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4844: invalidvarcomb[j1]=0;
1.226 brouard 4845: }
1.251 brouard 4846: fprintf(ficresphtmfr,"</table>\n");
4847: fprintf(ficlog,"\n");
4848: if(j!=0){
4849: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4850: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4851: for(k=1; k <=(nlstate+ndeath); k++){
4852: if (k != i) {
1.265 brouard 4853: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4854: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4855: if(j1==1){ /* All dummy covariates to zero */
4856: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4857: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4858: printf("%d%d ",i,k);
4859: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4860: 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]));
4861: 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]));
4862: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4863: }
1.253 brouard 4864: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4865: for(iage=iagemin; iage <= iagemax+3; iage++){
4866: x[iage]= (double)iage;
4867: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4868: /* 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 4869: }
1.268 brouard 4870: /* Some are not finite, but linreg will ignore these ages */
4871: no=0;
1.253 brouard 4872: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4873: pstart[s1]=b;
4874: pstart[s1-1]=a;
1.252 brouard 4875: }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 */
4876: 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]);
4877: 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 4878: 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 4879: printf("%d%d ",i,k);
4880: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4881: 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 4882: }else{ /* Other cases, like quantitative fixed or varying covariates */
4883: ;
4884: }
4885: /* printf("%12.7f )", param[i][jj][k]); */
4886: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4887: s1++;
1.251 brouard 4888: } /* end jj */
4889: } /* end k!= i */
4890: } /* end k */
1.265 brouard 4891: } /* end i, s1 */
1.251 brouard 4892: } /* end j !=0 */
4893: } /* end selected combination of covariate j1 */
4894: if(j==0){ /* We can estimate starting values from the occurences in each case */
4895: printf("#Freqsummary: Starting values for the constants:\n");
4896: fprintf(ficlog,"\n");
1.265 brouard 4897: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4898: for(k=1; k <=(nlstate+ndeath); k++){
4899: if (k != i) {
4900: printf("%d%d ",i,k);
4901: fprintf(ficlog,"%d%d ",i,k);
4902: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 4903: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 4904: if(jj==1){ /* Age has to be done */
1.265 brouard 4905: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
4906: 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]));
4907: 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 4908: }
4909: /* printf("%12.7f )", param[i][jj][k]); */
4910: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4911: s1++;
1.250 brouard 4912: }
1.251 brouard 4913: printf("\n");
4914: fprintf(ficlog,"\n");
1.250 brouard 4915: }
4916: }
1.284 brouard 4917: } /* end of state i */
1.251 brouard 4918: printf("#Freqsummary\n");
4919: fprintf(ficlog,"\n");
1.265 brouard 4920: for(s1=-1; s1 <=nlstate+ndeath; s1++){
4921: for(s2=-1; s2 <=nlstate+ndeath; s2++){
4922: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
4923: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4924: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4925: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
4926: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
4927: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 4928: /* } */
4929: }
1.265 brouard 4930: } /* end loop s1 */
1.251 brouard 4931:
4932: printf("\n");
4933: fprintf(ficlog,"\n");
4934: } /* end j=0 */
1.249 brouard 4935: } /* end j */
1.252 brouard 4936:
1.253 brouard 4937: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 4938: for(i=1, jk=1; i <=nlstate; i++){
4939: for(j=1; j <=nlstate+ndeath; j++){
4940: if(j!=i){
4941: /*ca[0]= k+'a'-1;ca[1]='\0';*/
4942: printf("%1d%1d",i,j);
4943: fprintf(ficparo,"%1d%1d",i,j);
4944: for(k=1; k<=ncovmodel;k++){
4945: /* printf(" %lf",param[i][j][k]); */
4946: /* fprintf(ficparo," %lf",param[i][j][k]); */
4947: p[jk]=pstart[jk];
4948: printf(" %f ",pstart[jk]);
4949: fprintf(ficparo," %f ",pstart[jk]);
4950: jk++;
4951: }
4952: printf("\n");
4953: fprintf(ficparo,"\n");
4954: }
4955: }
4956: }
4957: } /* end mle=-2 */
1.226 brouard 4958: dateintmean=dateintsum/k2cpt;
1.240 brouard 4959:
1.226 brouard 4960: fclose(ficresp);
4961: fclose(ficresphtm);
4962: fclose(ficresphtmfr);
1.283 brouard 4963: free_vector(idq,1,nqfveff);
1.226 brouard 4964: free_vector(meanq,1,nqfveff);
1.284 brouard 4965: free_vector(stdq,1,nqfveff);
1.226 brouard 4966: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 4967: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
4968: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 4969: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4970: free_vector(pospropt,1,nlstate);
4971: free_vector(posprop,1,nlstate);
1.251 brouard 4972: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4973: free_vector(pp,1,nlstate);
4974: /* End of freqsummary */
4975: }
1.126 brouard 4976:
1.268 brouard 4977: /* Simple linear regression */
4978: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
4979:
4980: /* y=a+bx regression */
4981: double sumx = 0.0; /* sum of x */
4982: double sumx2 = 0.0; /* sum of x**2 */
4983: double sumxy = 0.0; /* sum of x * y */
4984: double sumy = 0.0; /* sum of y */
4985: double sumy2 = 0.0; /* sum of y**2 */
4986: double sume2 = 0.0; /* sum of square or residuals */
4987: double yhat;
4988:
4989: double denom=0;
4990: int i;
4991: int ne=*no;
4992:
4993: for ( i=ifi, ne=0;i<=ila;i++) {
4994: if(!isfinite(x[i]) || !isfinite(y[i])){
4995: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
4996: continue;
4997: }
4998: ne=ne+1;
4999: sumx += x[i];
5000: sumx2 += x[i]*x[i];
5001: sumxy += x[i] * y[i];
5002: sumy += y[i];
5003: sumy2 += y[i]*y[i];
5004: denom = (ne * sumx2 - sumx*sumx);
5005: /* 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); */
5006: }
5007:
5008: denom = (ne * sumx2 - sumx*sumx);
5009: if (denom == 0) {
5010: // vertical, slope m is infinity
5011: *b = INFINITY;
5012: *a = 0;
5013: if (r) *r = 0;
5014: return 1;
5015: }
5016:
5017: *b = (ne * sumxy - sumx * sumy) / denom;
5018: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5019: if (r!=NULL) {
5020: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5021: sqrt((sumx2 - sumx*sumx/ne) *
5022: (sumy2 - sumy*sumy/ne));
5023: }
5024: *no=ne;
5025: for ( i=ifi, ne=0;i<=ila;i++) {
5026: if(!isfinite(x[i]) || !isfinite(y[i])){
5027: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5028: continue;
5029: }
5030: ne=ne+1;
5031: yhat = y[i] - *a -*b* x[i];
5032: sume2 += yhat * yhat ;
5033:
5034: denom = (ne * sumx2 - sumx*sumx);
5035: /* 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); */
5036: }
5037: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5038: *sa= *sb * sqrt(sumx2/ne);
5039:
5040: return 0;
5041: }
5042:
1.126 brouard 5043: /************ Prevalence ********************/
1.227 brouard 5044: 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)
5045: {
5046: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5047: in each health status at the date of interview (if between dateprev1 and dateprev2).
5048: We still use firstpass and lastpass as another selection.
5049: */
1.126 brouard 5050:
1.227 brouard 5051: int i, m, jk, j1, bool, z1,j, iv;
5052: int mi; /* Effective wave */
5053: int iage;
5054: double agebegin, ageend;
5055:
5056: double **prop;
5057: double posprop;
5058: double y2; /* in fractional years */
5059: int iagemin, iagemax;
5060: int first; /** to stop verbosity which is redirected to log file */
5061:
5062: iagemin= (int) agemin;
5063: iagemax= (int) agemax;
5064: /*pp=vector(1,nlstate);*/
1.251 brouard 5065: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5066: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5067: j1=0;
1.222 brouard 5068:
1.227 brouard 5069: /*j=cptcoveff;*/
5070: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5071:
1.288 brouard 5072: first=0;
1.227 brouard 5073: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5074: for (i=1; i<=nlstate; i++)
1.251 brouard 5075: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5076: prop[i][iage]=0.0;
5077: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5078: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5079: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5080:
5081: for (i=1; i<=imx; i++) { /* Each individual */
5082: bool=1;
5083: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5084: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5085: m=mw[mi][i];
5086: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5087: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5088: for (z1=1; z1<=cptcoveff; z1++){
5089: if( Fixed[Tmodelind[z1]]==1){
5090: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5091: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5092: bool=0;
5093: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5094: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5095: bool=0;
5096: }
5097: }
5098: if(bool==1){ /* Otherwise we skip that wave/person */
5099: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5100: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5101: if(m >=firstpass && m <=lastpass){
5102: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5103: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5104: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5105: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5106: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5107: 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);
5108: exit(1);
5109: }
5110: if (s[m][i]>0 && s[m][i]<=nlstate) {
5111: /*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]]);*/
5112: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5113: prop[s[m][i]][iagemax+3] += weight[i];
5114: } /* end valid statuses */
5115: } /* end selection of dates */
5116: } /* end selection of waves */
5117: } /* end bool */
5118: } /* end wave */
5119: } /* end individual */
5120: for(i=iagemin; i <= iagemax+3; i++){
5121: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5122: posprop += prop[jk][i];
5123: }
5124:
5125: for(jk=1; jk <=nlstate ; jk++){
5126: if( i <= iagemax){
5127: if(posprop>=1.e-5){
5128: probs[i][jk][j1]= prop[jk][i]/posprop;
5129: } else{
1.288 brouard 5130: if(!first){
5131: first=1;
1.266 brouard 5132: 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]);
5133: }else{
1.288 brouard 5134: 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 5135: }
5136: }
5137: }
5138: }/* end jk */
5139: }/* end i */
1.222 brouard 5140: /*} *//* end i1 */
1.227 brouard 5141: } /* end j1 */
1.222 brouard 5142:
1.227 brouard 5143: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5144: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5145: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5146: } /* End of prevalence */
1.126 brouard 5147:
5148: /************* Waves Concatenation ***************/
5149:
5150: 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)
5151: {
5152: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
5153: Death is a valid wave (if date is known).
5154: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5155: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
5156: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 5157: */
1.126 brouard 5158:
1.224 brouard 5159: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5160: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5161: double sum=0., jmean=0.;*/
1.224 brouard 5162: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5163: int j, k=0,jk, ju, jl;
5164: double sum=0.;
5165: first=0;
1.214 brouard 5166: firstwo=0;
1.217 brouard 5167: firsthree=0;
1.218 brouard 5168: firstfour=0;
1.164 brouard 5169: jmin=100000;
1.126 brouard 5170: jmax=-1;
5171: jmean=0.;
1.224 brouard 5172:
5173: /* Treating live states */
1.214 brouard 5174: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5175: mi=0; /* First valid wave */
1.227 brouard 5176: mli=0; /* Last valid wave */
1.126 brouard 5177: m=firstpass;
1.214 brouard 5178: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 5179: 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 */
5180: mli=m-1;/* mw[++mi][i]=m-1; */
5181: }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 */
5182: mw[++mi][i]=m;
5183: mli=m;
1.224 brouard 5184: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5185: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5186: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5187: }
1.227 brouard 5188: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 5189: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5190: break;
1.224 brouard 5191: #else
1.227 brouard 5192: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
5193: if(firsthree == 0){
1.262 brouard 5194: 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 5195: firsthree=1;
5196: }
1.262 brouard 5197: 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);
1.227 brouard 5198: mw[++mi][i]=m;
5199: mli=m;
5200: }
5201: if(s[m][i]==-2){ /* Vital status is really unknown */
5202: nbwarn++;
5203: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
5204: 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);
5205: 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);
5206: }
5207: break;
5208: }
5209: break;
1.224 brouard 5210: #endif
1.227 brouard 5211: }/* End m >= lastpass */
1.126 brouard 5212: }/* end while */
1.224 brouard 5213:
1.227 brouard 5214: /* 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 5215: /* After last pass */
1.224 brouard 5216: /* Treating death states */
1.214 brouard 5217: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5218: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5219: /* } */
1.126 brouard 5220: mi++; /* Death is another wave */
5221: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5222: /* Only death is a correct wave */
1.126 brouard 5223: mw[mi][i]=m;
1.257 brouard 5224: } /* else not in a death state */
1.224 brouard 5225: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5226: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5227: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 5228: if((andc[i]+moisdc[i]/12.) <=(anint[m][i]+mint[m][i]/12.)){ /* death occured before last wave and status should have been death instead of -1 */
5229: nbwarn++;
5230: if(firstfiv==0){
5231: printf("Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d interviewed at %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 );
5232: firstfiv=1;
5233: }else{
5234: fprintf(ficlog,"Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d interviewed at %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 );
5235: }
5236: }else{ /* Death occured afer last wave potential bias */
5237: nberr++;
5238: if(firstwo==0){
1.257 brouard 5239: printf("Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%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. Please add a new fictive wave at the date of last vital status scan, with a dead status or alive but unknown state status (-1). 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], i,m );
1.227 brouard 5240: firstwo=1;
5241: }
1.257 brouard 5242: fprintf(ficlog,"Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%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. Please add a new fictive wave at the date of last vital status scan, with a dead status or alive but unknown state status (-1). See documentation\n\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], i,m );
1.227 brouard 5243: }
1.257 brouard 5244: }else{ /* if date of interview is unknown */
1.227 brouard 5245: /* death is known but not confirmed by death status at any wave */
5246: if(firstfour==0){
5247: 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. 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], i,m );
5248: firstfour=1;
5249: }
5250: 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. 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], i,m );
1.214 brouard 5251: }
1.224 brouard 5252: } /* end if date of death is known */
5253: #endif
5254: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5255: /* wav[i]=mw[mi][i]; */
1.126 brouard 5256: if(mi==0){
5257: nbwarn++;
5258: if(first==0){
1.227 brouard 5259: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5260: first=1;
1.126 brouard 5261: }
5262: if(first==1){
1.227 brouard 5263: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5264: }
5265: } /* end mi==0 */
5266: } /* End individuals */
1.214 brouard 5267: /* wav and mw are no more changed */
1.223 brouard 5268:
1.214 brouard 5269:
1.126 brouard 5270: for(i=1; i<=imx; i++){
5271: for(mi=1; mi<wav[i];mi++){
5272: if (stepm <=0)
1.227 brouard 5273: dh[mi][i]=1;
1.126 brouard 5274: else{
1.260 brouard 5275: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5276: if (agedc[i] < 2*AGESUP) {
5277: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5278: if(j==0) j=1; /* Survives at least one month after exam */
5279: else if(j<0){
5280: nberr++;
5281: 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]);
5282: j=1; /* Temporary Dangerous patch */
5283: 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);
5284: 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]);
5285: 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);
5286: }
5287: k=k+1;
5288: if (j >= jmax){
5289: jmax=j;
5290: ijmax=i;
5291: }
5292: if (j <= jmin){
5293: jmin=j;
5294: ijmin=i;
5295: }
5296: sum=sum+j;
5297: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5298: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5299: }
5300: }
5301: else{
5302: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5303: /* 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 5304:
1.227 brouard 5305: k=k+1;
5306: if (j >= jmax) {
5307: jmax=j;
5308: ijmax=i;
5309: }
5310: else if (j <= jmin){
5311: jmin=j;
5312: ijmin=i;
5313: }
5314: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5315: /*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]);*/
5316: if(j<0){
5317: nberr++;
5318: 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]);
5319: 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]);
5320: }
5321: sum=sum+j;
5322: }
5323: jk= j/stepm;
5324: jl= j -jk*stepm;
5325: ju= j -(jk+1)*stepm;
5326: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5327: if(jl==0){
5328: dh[mi][i]=jk;
5329: bh[mi][i]=0;
5330: }else{ /* We want a negative bias in order to only have interpolation ie
5331: * to avoid the price of an extra matrix product in likelihood */
5332: dh[mi][i]=jk+1;
5333: bh[mi][i]=ju;
5334: }
5335: }else{
5336: if(jl <= -ju){
5337: dh[mi][i]=jk;
5338: bh[mi][i]=jl; /* bias is positive if real duration
5339: * is higher than the multiple of stepm and negative otherwise.
5340: */
5341: }
5342: else{
5343: dh[mi][i]=jk+1;
5344: bh[mi][i]=ju;
5345: }
5346: if(dh[mi][i]==0){
5347: dh[mi][i]=1; /* At least one step */
5348: bh[mi][i]=ju; /* At least one step */
5349: /* 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);*/
5350: }
5351: } /* end if mle */
1.126 brouard 5352: }
5353: } /* end wave */
5354: }
5355: jmean=sum/k;
5356: 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 5357: 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 5358: }
1.126 brouard 5359:
5360: /*********** Tricode ****************************/
1.220 brouard 5361: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5362: {
5363: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5364: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5365: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5366: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5367: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5368: */
1.130 brouard 5369:
1.242 brouard 5370: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5371: int modmaxcovj=0; /* Modality max of covariates j */
5372: int cptcode=0; /* Modality max of covariates j */
5373: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5374:
5375:
1.242 brouard 5376: /* cptcoveff=0; */
5377: /* *cptcov=0; */
1.126 brouard 5378:
1.242 brouard 5379: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5380: for (k=1; k <= maxncov; k++)
5381: for(j=1; j<=2; j++)
5382: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5383:
1.242 brouard 5384: /* Loop on covariates without age and products and no quantitative variable */
5385: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5386: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5387: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5388: switch(Fixed[k]) {
5389: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5390: 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*/
5391: ij=(int)(covar[Tvar[k]][i]);
5392: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5393: * If product of Vn*Vm, still boolean *:
5394: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5395: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5396: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5397: modality of the nth covariate of individual i. */
5398: if (ij > modmaxcovj)
5399: modmaxcovj=ij;
5400: else if (ij < modmincovj)
5401: modmincovj=ij;
1.287 brouard 5402: if (ij <0 || ij >1 ){
5403: printf("Information, IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5404: fprintf(ficlog,"Information, currently IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5405: }
5406: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5407: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5408: exit(1);
5409: }else
5410: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5411: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5412: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5413: /* getting the maximum value of the modality of the covariate
5414: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5415: female ies 1, then modmaxcovj=1.
5416: */
5417: } /* end for loop on individuals i */
5418: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5419: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5420: cptcode=modmaxcovj;
5421: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5422: /*for (i=0; i<=cptcode; i++) {*/
5423: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5424: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5425: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5426: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5427: if( j != -1){
5428: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5429: covariate for which somebody answered excluding
5430: undefined. Usually 2: 0 and 1. */
5431: }
5432: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5433: covariate for which somebody answered including
5434: undefined. Usually 3: -1, 0 and 1. */
5435: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5436: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5437: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5438:
1.242 brouard 5439: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5440: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5441: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5442: /* modmincovj=3; modmaxcovj = 7; */
5443: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5444: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5445: /* defining two dummy variables: variables V1_1 and V1_2.*/
5446: /* nbcode[Tvar[j]][ij]=k; */
5447: /* nbcode[Tvar[j]][1]=0; */
5448: /* nbcode[Tvar[j]][2]=1; */
5449: /* nbcode[Tvar[j]][3]=2; */
5450: /* To be continued (not working yet). */
5451: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5452:
5453: /* 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*/
5454: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5455: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5456: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5457: /*, could be restored in the future */
5458: 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 5459: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5460: break;
5461: }
5462: ij++;
1.287 brouard 5463: 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 5464: cptcode = ij; /* New max modality for covar j */
5465: } /* end of loop on modality i=-1 to 1 or more */
5466: break;
5467: case 1: /* Testing on varying covariate, could be simple and
5468: * should look at waves or product of fixed *
5469: * varying. No time to test -1, assuming 0 and 1 only */
5470: ij=0;
5471: for(i=0; i<=1;i++){
5472: nbcode[Tvar[k]][++ij]=i;
5473: }
5474: break;
5475: default:
5476: break;
5477: } /* end switch */
5478: } /* end dummy test */
1.287 brouard 5479: } /* 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 5480:
5481: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5482: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5483: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5484: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5485: 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 */
5486: 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 */
5487: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5488: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5489:
5490: ij=0;
5491: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5492: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5493: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5494: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5495: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5496: /* If product not in single variable we don't print results */
5497: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5498: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5499: 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*/
5500: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5501: 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 */
5502: if(Fixed[k]!=0)
5503: anyvaryingduminmodel=1;
5504: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5505: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5506: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5507: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5508: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5509: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5510: }
5511: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5512: /* ij--; */
5513: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5514: *cptcov=ij; /*Number of total real effective covariates: effective
5515: * because they can be excluded from the model and real
5516: * if in the model but excluded because missing values, but how to get k from ij?*/
5517: for(j=ij+1; j<= cptcovt; j++){
5518: Tvaraff[j]=0;
5519: Tmodelind[j]=0;
5520: }
5521: for(j=ntveff+1; j<= cptcovt; j++){
5522: TmodelInvind[j]=0;
5523: }
5524: /* To be sorted */
5525: ;
5526: }
1.126 brouard 5527:
1.145 brouard 5528:
1.126 brouard 5529: /*********** Health Expectancies ****************/
5530:
1.235 brouard 5531: 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 5532:
5533: {
5534: /* Health expectancies, no variances */
1.164 brouard 5535: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5536: int nhstepma, nstepma; /* Decreasing with age */
5537: double age, agelim, hf;
5538: double ***p3mat;
5539: double eip;
5540:
1.238 brouard 5541: /* pstamp(ficreseij); */
1.126 brouard 5542: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5543: fprintf(ficreseij,"# Age");
5544: for(i=1; i<=nlstate;i++){
5545: for(j=1; j<=nlstate;j++){
5546: fprintf(ficreseij," e%1d%1d ",i,j);
5547: }
5548: fprintf(ficreseij," e%1d. ",i);
5549: }
5550: fprintf(ficreseij,"\n");
5551:
5552:
5553: if(estepm < stepm){
5554: printf ("Problem %d lower than %d\n",estepm, stepm);
5555: }
5556: else hstepm=estepm;
5557: /* We compute the life expectancy from trapezoids spaced every estepm months
5558: * This is mainly to measure the difference between two models: for example
5559: * if stepm=24 months pijx are given only every 2 years and by summing them
5560: * we are calculating an estimate of the Life Expectancy assuming a linear
5561: * progression in between and thus overestimating or underestimating according
5562: * to the curvature of the survival function. If, for the same date, we
5563: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5564: * to compare the new estimate of Life expectancy with the same linear
5565: * hypothesis. A more precise result, taking into account a more precise
5566: * curvature will be obtained if estepm is as small as stepm. */
5567:
5568: /* For example we decided to compute the life expectancy with the smallest unit */
5569: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5570: nhstepm is the number of hstepm from age to agelim
5571: nstepm is the number of stepm from age to agelin.
1.270 brouard 5572: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5573: and note for a fixed period like estepm months */
5574: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5575: survival function given by stepm (the optimization length). Unfortunately it
5576: means that if the survival funtion is printed only each two years of age and if
5577: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5578: results. So we changed our mind and took the option of the best precision.
5579: */
5580: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5581:
5582: agelim=AGESUP;
5583: /* If stepm=6 months */
5584: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5585: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5586:
5587: /* nhstepm age range expressed in number of stepm */
5588: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5589: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5590: /* if (stepm >= YEARM) hstepm=1;*/
5591: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5592: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5593:
5594: for (age=bage; age<=fage; age ++){
5595: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5596: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5597: /* if (stepm >= YEARM) hstepm=1;*/
5598: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5599:
5600: /* If stepm=6 months */
5601: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5602: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5603:
1.235 brouard 5604: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5605:
5606: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5607:
5608: printf("%d|",(int)age);fflush(stdout);
5609: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5610:
5611: /* Computing expectancies */
5612: for(i=1; i<=nlstate;i++)
5613: for(j=1; j<=nlstate;j++)
5614: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5615: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5616:
5617: /* 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]);*/
5618:
5619: }
5620:
5621: fprintf(ficreseij,"%3.0f",age );
5622: for(i=1; i<=nlstate;i++){
5623: eip=0;
5624: for(j=1; j<=nlstate;j++){
5625: eip +=eij[i][j][(int)age];
5626: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5627: }
5628: fprintf(ficreseij,"%9.4f", eip );
5629: }
5630: fprintf(ficreseij,"\n");
5631:
5632: }
5633: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5634: printf("\n");
5635: fprintf(ficlog,"\n");
5636:
5637: }
5638:
1.235 brouard 5639: 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 5640:
5641: {
5642: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5643: to initial status i, ei. .
1.126 brouard 5644: */
5645: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5646: int nhstepma, nstepma; /* Decreasing with age */
5647: double age, agelim, hf;
5648: double ***p3matp, ***p3matm, ***varhe;
5649: double **dnewm,**doldm;
5650: double *xp, *xm;
5651: double **gp, **gm;
5652: double ***gradg, ***trgradg;
5653: int theta;
5654:
5655: double eip, vip;
5656:
5657: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5658: xp=vector(1,npar);
5659: xm=vector(1,npar);
5660: dnewm=matrix(1,nlstate*nlstate,1,npar);
5661: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5662:
5663: pstamp(ficresstdeij);
5664: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5665: fprintf(ficresstdeij,"# Age");
5666: for(i=1; i<=nlstate;i++){
5667: for(j=1; j<=nlstate;j++)
5668: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5669: fprintf(ficresstdeij," e%1d. ",i);
5670: }
5671: fprintf(ficresstdeij,"\n");
5672:
5673: pstamp(ficrescveij);
5674: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5675: fprintf(ficrescveij,"# Age");
5676: for(i=1; i<=nlstate;i++)
5677: for(j=1; j<=nlstate;j++){
5678: cptj= (j-1)*nlstate+i;
5679: for(i2=1; i2<=nlstate;i2++)
5680: for(j2=1; j2<=nlstate;j2++){
5681: cptj2= (j2-1)*nlstate+i2;
5682: if(cptj2 <= cptj)
5683: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5684: }
5685: }
5686: fprintf(ficrescveij,"\n");
5687:
5688: if(estepm < stepm){
5689: printf ("Problem %d lower than %d\n",estepm, stepm);
5690: }
5691: else hstepm=estepm;
5692: /* We compute the life expectancy from trapezoids spaced every estepm months
5693: * This is mainly to measure the difference between two models: for example
5694: * if stepm=24 months pijx are given only every 2 years and by summing them
5695: * we are calculating an estimate of the Life Expectancy assuming a linear
5696: * progression in between and thus overestimating or underestimating according
5697: * to the curvature of the survival function. If, for the same date, we
5698: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5699: * to compare the new estimate of Life expectancy with the same linear
5700: * hypothesis. A more precise result, taking into account a more precise
5701: * curvature will be obtained if estepm is as small as stepm. */
5702:
5703: /* For example we decided to compute the life expectancy with the smallest unit */
5704: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5705: nhstepm is the number of hstepm from age to agelim
5706: nstepm is the number of stepm from age to agelin.
5707: Look at hpijx to understand the reason of that which relies in memory size
5708: and note for a fixed period like estepm months */
5709: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5710: survival function given by stepm (the optimization length). Unfortunately it
5711: means that if the survival funtion is printed only each two years of age and if
5712: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5713: results. So we changed our mind and took the option of the best precision.
5714: */
5715: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5716:
5717: /* If stepm=6 months */
5718: /* nhstepm age range expressed in number of stepm */
5719: agelim=AGESUP;
5720: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5721: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5722: /* if (stepm >= YEARM) hstepm=1;*/
5723: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5724:
5725: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5726: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5727: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5728: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5729: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5730: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5731:
5732: for (age=bage; age<=fage; age ++){
5733: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5734: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5735: /* if (stepm >= YEARM) hstepm=1;*/
5736: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5737:
1.126 brouard 5738: /* If stepm=6 months */
5739: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5740: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5741:
5742: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5743:
1.126 brouard 5744: /* Computing Variances of health expectancies */
5745: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5746: decrease memory allocation */
5747: for(theta=1; theta <=npar; theta++){
5748: for(i=1; i<=npar; i++){
1.222 brouard 5749: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5750: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5751: }
1.235 brouard 5752: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5753: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5754:
1.126 brouard 5755: for(j=1; j<= nlstate; j++){
1.222 brouard 5756: for(i=1; i<=nlstate; i++){
5757: for(h=0; h<=nhstepm-1; h++){
5758: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5759: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5760: }
5761: }
1.126 brouard 5762: }
1.218 brouard 5763:
1.126 brouard 5764: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5765: for(h=0; h<=nhstepm-1; h++){
5766: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5767: }
1.126 brouard 5768: }/* End theta */
5769:
5770:
5771: for(h=0; h<=nhstepm-1; h++)
5772: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5773: for(theta=1; theta <=npar; theta++)
5774: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5775:
1.218 brouard 5776:
1.222 brouard 5777: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5778: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5779: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5780:
1.222 brouard 5781: printf("%d|",(int)age);fflush(stdout);
5782: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5783: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5784: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5785: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5786: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5787: for(ij=1;ij<=nlstate*nlstate;ij++)
5788: for(ji=1;ji<=nlstate*nlstate;ji++)
5789: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5790: }
5791: }
1.218 brouard 5792:
1.126 brouard 5793: /* Computing expectancies */
1.235 brouard 5794: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5795: for(i=1; i<=nlstate;i++)
5796: for(j=1; j<=nlstate;j++)
1.222 brouard 5797: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5798: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5799:
1.222 brouard 5800: /* 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 5801:
1.222 brouard 5802: }
1.269 brouard 5803:
5804: /* Standard deviation of expectancies ij */
1.126 brouard 5805: fprintf(ficresstdeij,"%3.0f",age );
5806: for(i=1; i<=nlstate;i++){
5807: eip=0.;
5808: vip=0.;
5809: for(j=1; j<=nlstate;j++){
1.222 brouard 5810: eip += eij[i][j][(int)age];
5811: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5812: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5813: 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 5814: }
5815: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5816: }
5817: fprintf(ficresstdeij,"\n");
1.218 brouard 5818:
1.269 brouard 5819: /* Variance of expectancies ij */
1.126 brouard 5820: fprintf(ficrescveij,"%3.0f",age );
5821: for(i=1; i<=nlstate;i++)
5822: for(j=1; j<=nlstate;j++){
1.222 brouard 5823: cptj= (j-1)*nlstate+i;
5824: for(i2=1; i2<=nlstate;i2++)
5825: for(j2=1; j2<=nlstate;j2++){
5826: cptj2= (j2-1)*nlstate+i2;
5827: if(cptj2 <= cptj)
5828: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5829: }
1.126 brouard 5830: }
5831: fprintf(ficrescveij,"\n");
1.218 brouard 5832:
1.126 brouard 5833: }
5834: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5835: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5836: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5837: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5838: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5839: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5840: printf("\n");
5841: fprintf(ficlog,"\n");
1.218 brouard 5842:
1.126 brouard 5843: free_vector(xm,1,npar);
5844: free_vector(xp,1,npar);
5845: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5846: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5847: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5848: }
1.218 brouard 5849:
1.126 brouard 5850: /************ Variance ******************/
1.235 brouard 5851: 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 5852: {
1.279 brouard 5853: /** Variance of health expectancies
5854: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
5855: * double **newm;
5856: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
5857: */
1.218 brouard 5858:
5859: /* int movingaverage(); */
5860: double **dnewm,**doldm;
5861: double **dnewmp,**doldmp;
5862: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 5863: int first=0;
1.218 brouard 5864: int k;
5865: double *xp;
1.279 brouard 5866: double **gp, **gm; /**< for var eij */
5867: double ***gradg, ***trgradg; /**< for var eij */
5868: double **gradgp, **trgradgp; /**< for var p point j */
5869: double *gpp, *gmp; /**< for var p point j */
5870: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 5871: double ***p3mat;
5872: double age,agelim, hf;
5873: /* double ***mobaverage; */
5874: int theta;
5875: char digit[4];
5876: char digitp[25];
5877:
5878: char fileresprobmorprev[FILENAMELENGTH];
5879:
5880: if(popbased==1){
5881: if(mobilav!=0)
5882: strcpy(digitp,"-POPULBASED-MOBILAV_");
5883: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5884: }
5885: else
5886: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5887:
1.218 brouard 5888: /* if (mobilav!=0) { */
5889: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5890: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5891: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5892: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5893: /* } */
5894: /* } */
5895:
5896: strcpy(fileresprobmorprev,"PRMORPREV-");
5897: sprintf(digit,"%-d",ij);
5898: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5899: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5900: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5901: strcat(fileresprobmorprev,fileresu);
5902: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5903: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5904: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5905: }
5906: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5907: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5908: pstamp(ficresprobmorprev);
5909: 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 5910: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5911: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5912: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5913: }
5914: for(j=1;j<=cptcoveff;j++)
5915: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5916: fprintf(ficresprobmorprev,"\n");
5917:
1.218 brouard 5918: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5919: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5920: fprintf(ficresprobmorprev," p.%-d SE",j);
5921: for(i=1; i<=nlstate;i++)
5922: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5923: }
5924: fprintf(ficresprobmorprev,"\n");
5925:
5926: fprintf(ficgp,"\n# Routine varevsij");
5927: fprintf(ficgp,"\nunset title \n");
5928: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5929: 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");
5930: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 5931:
1.218 brouard 5932: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5933: pstamp(ficresvij);
5934: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5935: if(popbased==1)
5936: 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);
5937: else
5938: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5939: fprintf(ficresvij,"# Age");
5940: for(i=1; i<=nlstate;i++)
5941: for(j=1; j<=nlstate;j++)
5942: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5943: fprintf(ficresvij,"\n");
5944:
5945: xp=vector(1,npar);
5946: dnewm=matrix(1,nlstate,1,npar);
5947: doldm=matrix(1,nlstate,1,nlstate);
5948: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5949: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5950:
5951: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5952: gpp=vector(nlstate+1,nlstate+ndeath);
5953: gmp=vector(nlstate+1,nlstate+ndeath);
5954: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5955:
1.218 brouard 5956: if(estepm < stepm){
5957: printf ("Problem %d lower than %d\n",estepm, stepm);
5958: }
5959: else hstepm=estepm;
5960: /* For example we decided to compute the life expectancy with the smallest unit */
5961: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5962: nhstepm is the number of hstepm from age to agelim
5963: nstepm is the number of stepm from age to agelim.
5964: Look at function hpijx to understand why because of memory size limitations,
5965: we decided (b) to get a life expectancy respecting the most precise curvature of the
5966: survival function given by stepm (the optimization length). Unfortunately it
5967: means that if the survival funtion is printed every two years of age and if
5968: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5969: results. So we changed our mind and took the option of the best precision.
5970: */
5971: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5972: agelim = AGESUP;
5973: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5974: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5975: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5976: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5977: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
5978: gp=matrix(0,nhstepm,1,nlstate);
5979: gm=matrix(0,nhstepm,1,nlstate);
5980:
5981:
5982: for(theta=1; theta <=npar; theta++){
5983: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
5984: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5985: }
1.279 brouard 5986: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
5987: * returns into prlim .
1.288 brouard 5988: */
1.242 brouard 5989: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 5990:
5991: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 5992: if (popbased==1) {
5993: if(mobilav ==0){
5994: for(i=1; i<=nlstate;i++)
5995: prlim[i][i]=probs[(int)age][i][ij];
5996: }else{ /* mobilav */
5997: for(i=1; i<=nlstate;i++)
5998: prlim[i][i]=mobaverage[(int)age][i][ij];
5999: }
6000: }
1.279 brouard 6001: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}_x\f$ at horizon h.
6002: */
6003: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Returns p3mat[i][j][h] for h=0 to nhstepm */
6004: /**< And for each alive state j, sums over i \f$ w^i_x {}{h}_p^{ij}_x\f$, which are the probability
6005: * at horizon h in state j including mortality.
6006: */
1.218 brouard 6007: for(j=1; j<= nlstate; j++){
6008: for(h=0; h<=nhstepm; h++){
6009: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6010: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6011: }
6012: }
1.279 brouard 6013: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6014: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6015: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6016: */
6017: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6018: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6019: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6020: }
6021:
6022: /* Again with minus shift */
1.218 brouard 6023:
6024: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6025: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6026:
1.242 brouard 6027: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6028:
6029: if (popbased==1) {
6030: if(mobilav ==0){
6031: for(i=1; i<=nlstate;i++)
6032: prlim[i][i]=probs[(int)age][i][ij];
6033: }else{ /* mobilav */
6034: for(i=1; i<=nlstate;i++)
6035: prlim[i][i]=mobaverage[(int)age][i][ij];
6036: }
6037: }
6038:
1.235 brouard 6039: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6040:
6041: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6042: for(h=0; h<=nhstepm; h++){
6043: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6044: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6045: }
6046: }
6047: /* This for computing probability of death (h=1 means
6048: computed over hstepm matrices product = hstepm*stepm months)
6049: as a weighted average of prlim.
6050: */
6051: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6052: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6053: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6054: }
1.279 brouard 6055: /* end shifting computations */
6056:
6057: /**< Computing gradient matrix at horizon h
6058: */
1.218 brouard 6059: for(j=1; j<= nlstate; j++) /* vareij */
6060: for(h=0; h<=nhstepm; h++){
6061: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6062: }
1.279 brouard 6063: /**< Gradient of overall mortality p.3 (or p.j)
6064: */
6065: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6066: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6067: }
6068:
6069: } /* End theta */
1.279 brouard 6070:
6071: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6072: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6073:
6074: for(h=0; h<=nhstepm; h++) /* veij */
6075: for(j=1; j<=nlstate;j++)
6076: for(theta=1; theta <=npar; theta++)
6077: trgradg[h][j][theta]=gradg[h][theta][j];
6078:
6079: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6080: for(theta=1; theta <=npar; theta++)
6081: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6082: /**< as well as its transposed matrix
6083: */
1.218 brouard 6084:
6085: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6086: for(i=1;i<=nlstate;i++)
6087: for(j=1;j<=nlstate;j++)
6088: vareij[i][j][(int)age] =0.;
1.279 brouard 6089:
6090: /* Computing trgradg by matcov by gradg at age and summing over h
6091: * and k (nhstepm) formula 15 of article
6092: * Lievre-Brouard-Heathcote
6093: */
6094:
1.218 brouard 6095: for(h=0;h<=nhstepm;h++){
6096: for(k=0;k<=nhstepm;k++){
6097: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6098: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6099: for(i=1;i<=nlstate;i++)
6100: for(j=1;j<=nlstate;j++)
6101: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6102: }
6103: }
6104:
1.279 brouard 6105: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6106: * p.j overall mortality formula 49 but computed directly because
6107: * we compute the grad (wix pijx) instead of grad (pijx),even if
6108: * wix is independent of theta.
6109: */
1.218 brouard 6110: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6111: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6112: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6113: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6114: varppt[j][i]=doldmp[j][i];
6115: /* end ppptj */
6116: /* x centered again */
6117:
1.242 brouard 6118: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6119:
6120: if (popbased==1) {
6121: if(mobilav ==0){
6122: for(i=1; i<=nlstate;i++)
6123: prlim[i][i]=probs[(int)age][i][ij];
6124: }else{ /* mobilav */
6125: for(i=1; i<=nlstate;i++)
6126: prlim[i][i]=mobaverage[(int)age][i][ij];
6127: }
6128: }
6129:
6130: /* This for computing probability of death (h=1 means
6131: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6132: as a weighted average of prlim.
6133: */
1.235 brouard 6134: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6135: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6136: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6137: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6138: }
6139: /* end probability of death */
6140:
6141: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6142: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6143: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6144: for(i=1; i<=nlstate;i++){
6145: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6146: }
6147: }
6148: fprintf(ficresprobmorprev,"\n");
6149:
6150: fprintf(ficresvij,"%.0f ",age );
6151: for(i=1; i<=nlstate;i++)
6152: for(j=1; j<=nlstate;j++){
6153: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6154: }
6155: fprintf(ficresvij,"\n");
6156: free_matrix(gp,0,nhstepm,1,nlstate);
6157: free_matrix(gm,0,nhstepm,1,nlstate);
6158: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6159: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6160: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6161: } /* End age */
6162: free_vector(gpp,nlstate+1,nlstate+ndeath);
6163: free_vector(gmp,nlstate+1,nlstate+ndeath);
6164: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6165: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6166: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6167: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6168: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6169: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6170: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6171: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6172: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6173: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6174: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6175: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6176: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6177: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6178: 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);
6179: /* 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 6180: */
1.218 brouard 6181: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6182: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6183:
1.218 brouard 6184: free_vector(xp,1,npar);
6185: free_matrix(doldm,1,nlstate,1,nlstate);
6186: free_matrix(dnewm,1,nlstate,1,npar);
6187: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6188: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6189: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6190: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6191: fclose(ficresprobmorprev);
6192: fflush(ficgp);
6193: fflush(fichtm);
6194: } /* end varevsij */
1.126 brouard 6195:
6196: /************ Variance of prevlim ******************/
1.269 brouard 6197: 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 6198: {
1.205 brouard 6199: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6200: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6201:
1.268 brouard 6202: double **dnewmpar,**doldm;
1.126 brouard 6203: int i, j, nhstepm, hstepm;
6204: double *xp;
6205: double *gp, *gm;
6206: double **gradg, **trgradg;
1.208 brouard 6207: double **mgm, **mgp;
1.126 brouard 6208: double age,agelim;
6209: int theta;
6210:
6211: pstamp(ficresvpl);
1.288 brouard 6212: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6213: fprintf(ficresvpl,"# Age ");
6214: if(nresult >=1)
6215: fprintf(ficresvpl," Result# ");
1.126 brouard 6216: for(i=1; i<=nlstate;i++)
6217: fprintf(ficresvpl," %1d-%1d",i,i);
6218: fprintf(ficresvpl,"\n");
6219:
6220: xp=vector(1,npar);
1.268 brouard 6221: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6222: doldm=matrix(1,nlstate,1,nlstate);
6223:
6224: hstepm=1*YEARM; /* Every year of age */
6225: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6226: agelim = AGESUP;
6227: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6228: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6229: if (stepm >= YEARM) hstepm=1;
6230: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6231: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6232: mgp=matrix(1,npar,1,nlstate);
6233: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6234: gp=vector(1,nlstate);
6235: gm=vector(1,nlstate);
6236:
6237: for(theta=1; theta <=npar; theta++){
6238: for(i=1; i<=npar; i++){ /* Computes gradient */
6239: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6240: }
1.288 brouard 6241: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6242: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6243: /* else */
6244: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6245: for(i=1;i<=nlstate;i++){
1.126 brouard 6246: gp[i] = prlim[i][i];
1.208 brouard 6247: mgp[theta][i] = prlim[i][i];
6248: }
1.126 brouard 6249: for(i=1; i<=npar; i++) /* Computes gradient */
6250: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6251: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6252: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6253: /* else */
6254: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6255: for(i=1;i<=nlstate;i++){
1.126 brouard 6256: gm[i] = prlim[i][i];
1.208 brouard 6257: mgm[theta][i] = prlim[i][i];
6258: }
1.126 brouard 6259: for(i=1;i<=nlstate;i++)
6260: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6261: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6262: } /* End theta */
6263:
6264: trgradg =matrix(1,nlstate,1,npar);
6265:
6266: for(j=1; j<=nlstate;j++)
6267: for(theta=1; theta <=npar; theta++)
6268: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6269: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6270: /* printf("\nmgm mgp %d ",(int)age); */
6271: /* for(j=1; j<=nlstate;j++){ */
6272: /* printf(" %d ",j); */
6273: /* for(theta=1; theta <=npar; theta++) */
6274: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6275: /* printf("\n "); */
6276: /* } */
6277: /* } */
6278: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6279: /* printf("\n gradg %d ",(int)age); */
6280: /* for(j=1; j<=nlstate;j++){ */
6281: /* printf("%d ",j); */
6282: /* for(theta=1; theta <=npar; theta++) */
6283: /* printf("%d %lf ",theta,gradg[theta][j]); */
6284: /* printf("\n "); */
6285: /* } */
6286: /* } */
1.126 brouard 6287:
6288: for(i=1;i<=nlstate;i++)
6289: varpl[i][(int)age] =0.;
1.209 brouard 6290: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6291: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6292: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6293: }else{
1.268 brouard 6294: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6295: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6296: }
1.126 brouard 6297: for(i=1;i<=nlstate;i++)
6298: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6299:
6300: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6301: if(nresult >=1)
6302: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6303: for(i=1; i<=nlstate;i++){
1.126 brouard 6304: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6305: /* for(j=1;j<=nlstate;j++) */
6306: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6307: }
1.126 brouard 6308: fprintf(ficresvpl,"\n");
6309: free_vector(gp,1,nlstate);
6310: free_vector(gm,1,nlstate);
1.208 brouard 6311: free_matrix(mgm,1,npar,1,nlstate);
6312: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6313: free_matrix(gradg,1,npar,1,nlstate);
6314: free_matrix(trgradg,1,nlstate,1,npar);
6315: } /* End age */
6316:
6317: free_vector(xp,1,npar);
6318: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6319: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6320:
6321: }
6322:
6323:
6324: /************ Variance of backprevalence limit ******************/
1.269 brouard 6325: 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 6326: {
6327: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6328: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6329:
6330: double **dnewmpar,**doldm;
6331: int i, j, nhstepm, hstepm;
6332: double *xp;
6333: double *gp, *gm;
6334: double **gradg, **trgradg;
6335: double **mgm, **mgp;
6336: double age,agelim;
6337: int theta;
6338:
6339: pstamp(ficresvbl);
6340: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6341: fprintf(ficresvbl,"# Age ");
6342: if(nresult >=1)
6343: fprintf(ficresvbl," Result# ");
6344: for(i=1; i<=nlstate;i++)
6345: fprintf(ficresvbl," %1d-%1d",i,i);
6346: fprintf(ficresvbl,"\n");
6347:
6348: xp=vector(1,npar);
6349: dnewmpar=matrix(1,nlstate,1,npar);
6350: doldm=matrix(1,nlstate,1,nlstate);
6351:
6352: hstepm=1*YEARM; /* Every year of age */
6353: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6354: agelim = AGEINF;
6355: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6356: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6357: if (stepm >= YEARM) hstepm=1;
6358: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6359: gradg=matrix(1,npar,1,nlstate);
6360: mgp=matrix(1,npar,1,nlstate);
6361: mgm=matrix(1,npar,1,nlstate);
6362: gp=vector(1,nlstate);
6363: gm=vector(1,nlstate);
6364:
6365: for(theta=1; theta <=npar; theta++){
6366: for(i=1; i<=npar; i++){ /* Computes gradient */
6367: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6368: }
6369: if(mobilavproj > 0 )
6370: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6371: else
6372: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6373: for(i=1;i<=nlstate;i++){
6374: gp[i] = bprlim[i][i];
6375: mgp[theta][i] = bprlim[i][i];
6376: }
6377: for(i=1; i<=npar; i++) /* Computes gradient */
6378: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6379: if(mobilavproj > 0 )
6380: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6381: else
6382: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6383: for(i=1;i<=nlstate;i++){
6384: gm[i] = bprlim[i][i];
6385: mgm[theta][i] = bprlim[i][i];
6386: }
6387: for(i=1;i<=nlstate;i++)
6388: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6389: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6390: } /* End theta */
6391:
6392: trgradg =matrix(1,nlstate,1,npar);
6393:
6394: for(j=1; j<=nlstate;j++)
6395: for(theta=1; theta <=npar; theta++)
6396: trgradg[j][theta]=gradg[theta][j];
6397: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6398: /* printf("\nmgm mgp %d ",(int)age); */
6399: /* for(j=1; j<=nlstate;j++){ */
6400: /* printf(" %d ",j); */
6401: /* for(theta=1; theta <=npar; theta++) */
6402: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6403: /* printf("\n "); */
6404: /* } */
6405: /* } */
6406: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6407: /* printf("\n gradg %d ",(int)age); */
6408: /* for(j=1; j<=nlstate;j++){ */
6409: /* printf("%d ",j); */
6410: /* for(theta=1; theta <=npar; theta++) */
6411: /* printf("%d %lf ",theta,gradg[theta][j]); */
6412: /* printf("\n "); */
6413: /* } */
6414: /* } */
6415:
6416: for(i=1;i<=nlstate;i++)
6417: varbpl[i][(int)age] =0.;
6418: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6419: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6420: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6421: }else{
6422: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6423: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6424: }
6425: for(i=1;i<=nlstate;i++)
6426: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6427:
6428: fprintf(ficresvbl,"%.0f ",age );
6429: if(nresult >=1)
6430: fprintf(ficresvbl,"%d ",nres );
6431: for(i=1; i<=nlstate;i++)
6432: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6433: fprintf(ficresvbl,"\n");
6434: free_vector(gp,1,nlstate);
6435: free_vector(gm,1,nlstate);
6436: free_matrix(mgm,1,npar,1,nlstate);
6437: free_matrix(mgp,1,npar,1,nlstate);
6438: free_matrix(gradg,1,npar,1,nlstate);
6439: free_matrix(trgradg,1,nlstate,1,npar);
6440: } /* End age */
6441:
6442: free_vector(xp,1,npar);
6443: free_matrix(doldm,1,nlstate,1,npar);
6444: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6445:
6446: }
6447:
6448: /************ Variance of one-step probabilities ******************/
6449: 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 6450: {
6451: int i, j=0, k1, l1, tj;
6452: int k2, l2, j1, z1;
6453: int k=0, l;
6454: int first=1, first1, first2;
6455: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6456: double **dnewm,**doldm;
6457: double *xp;
6458: double *gp, *gm;
6459: double **gradg, **trgradg;
6460: double **mu;
6461: double age, cov[NCOVMAX+1];
6462: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6463: int theta;
6464: char fileresprob[FILENAMELENGTH];
6465: char fileresprobcov[FILENAMELENGTH];
6466: char fileresprobcor[FILENAMELENGTH];
6467: double ***varpij;
6468:
6469: strcpy(fileresprob,"PROB_");
6470: strcat(fileresprob,fileres);
6471: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6472: printf("Problem with resultfile: %s\n", fileresprob);
6473: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6474: }
6475: strcpy(fileresprobcov,"PROBCOV_");
6476: strcat(fileresprobcov,fileresu);
6477: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6478: printf("Problem with resultfile: %s\n", fileresprobcov);
6479: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6480: }
6481: strcpy(fileresprobcor,"PROBCOR_");
6482: strcat(fileresprobcor,fileresu);
6483: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6484: printf("Problem with resultfile: %s\n", fileresprobcor);
6485: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6486: }
6487: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6488: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6489: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6490: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6491: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6492: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6493: pstamp(ficresprob);
6494: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6495: fprintf(ficresprob,"# Age");
6496: pstamp(ficresprobcov);
6497: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6498: fprintf(ficresprobcov,"# Age");
6499: pstamp(ficresprobcor);
6500: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6501: fprintf(ficresprobcor,"# Age");
1.126 brouard 6502:
6503:
1.222 brouard 6504: for(i=1; i<=nlstate;i++)
6505: for(j=1; j<=(nlstate+ndeath);j++){
6506: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6507: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6508: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6509: }
6510: /* fprintf(ficresprob,"\n");
6511: fprintf(ficresprobcov,"\n");
6512: fprintf(ficresprobcor,"\n");
6513: */
6514: xp=vector(1,npar);
6515: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6516: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6517: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6518: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6519: first=1;
6520: fprintf(ficgp,"\n# Routine varprob");
6521: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6522: fprintf(fichtm,"\n");
6523:
1.288 brouard 6524: 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 6525: 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);
6526: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6527: and drawn. It helps understanding how is the covariance between two incidences.\
6528: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6529: 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 6530: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6531: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6532: standard deviations wide on each axis. <br>\
6533: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6534: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6535: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6536:
1.222 brouard 6537: cov[1]=1;
6538: /* tj=cptcoveff; */
1.225 brouard 6539: tj = (int) pow(2,cptcoveff);
1.222 brouard 6540: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6541: j1=0;
1.224 brouard 6542: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6543: if (cptcovn>0) {
6544: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6545: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6546: fprintf(ficresprob, "**********\n#\n");
6547: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6548: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6549: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6550:
1.222 brouard 6551: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6552: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6553: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6554:
6555:
1.222 brouard 6556: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6557: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6558: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6559:
1.222 brouard 6560: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6561: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6562: fprintf(ficresprobcor, "**********\n#");
6563: if(invalidvarcomb[j1]){
6564: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6565: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6566: continue;
6567: }
6568: }
6569: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6570: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6571: gp=vector(1,(nlstate)*(nlstate+ndeath));
6572: gm=vector(1,(nlstate)*(nlstate+ndeath));
6573: for (age=bage; age<=fage; age ++){
6574: cov[2]=age;
6575: if(nagesqr==1)
6576: cov[3]= age*age;
6577: for (k=1; k<=cptcovn;k++) {
6578: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6579: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6580: * 1 1 1 1 1
6581: * 2 2 1 1 1
6582: * 3 1 2 1 1
6583: */
6584: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6585: }
6586: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6587: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6588: for (k=1; k<=cptcovprod;k++)
6589: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6590:
6591:
1.222 brouard 6592: for(theta=1; theta <=npar; theta++){
6593: for(i=1; i<=npar; i++)
6594: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6595:
1.222 brouard 6596: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6597:
1.222 brouard 6598: k=0;
6599: for(i=1; i<= (nlstate); i++){
6600: for(j=1; j<=(nlstate+ndeath);j++){
6601: k=k+1;
6602: gp[k]=pmmij[i][j];
6603: }
6604: }
1.220 brouard 6605:
1.222 brouard 6606: for(i=1; i<=npar; i++)
6607: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6608:
1.222 brouard 6609: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6610: k=0;
6611: for(i=1; i<=(nlstate); i++){
6612: for(j=1; j<=(nlstate+ndeath);j++){
6613: k=k+1;
6614: gm[k]=pmmij[i][j];
6615: }
6616: }
1.220 brouard 6617:
1.222 brouard 6618: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6619: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6620: }
1.126 brouard 6621:
1.222 brouard 6622: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6623: for(theta=1; theta <=npar; theta++)
6624: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6625:
1.222 brouard 6626: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6627: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6628:
1.222 brouard 6629: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6630:
1.222 brouard 6631: k=0;
6632: for(i=1; i<=(nlstate); i++){
6633: for(j=1; j<=(nlstate+ndeath);j++){
6634: k=k+1;
6635: mu[k][(int) age]=pmmij[i][j];
6636: }
6637: }
6638: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6639: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6640: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6641:
1.222 brouard 6642: /*printf("\n%d ",(int)age);
6643: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6644: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6645: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6646: }*/
1.220 brouard 6647:
1.222 brouard 6648: fprintf(ficresprob,"\n%d ",(int)age);
6649: fprintf(ficresprobcov,"\n%d ",(int)age);
6650: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6651:
1.222 brouard 6652: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6653: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6654: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6655: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6656: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6657: }
6658: i=0;
6659: for (k=1; k<=(nlstate);k++){
6660: for (l=1; l<=(nlstate+ndeath);l++){
6661: i++;
6662: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6663: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6664: for (j=1; j<=i;j++){
6665: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6666: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6667: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6668: }
6669: }
6670: }/* end of loop for state */
6671: } /* end of loop for age */
6672: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6673: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6674: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6675: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6676:
6677: /* Confidence intervalle of pij */
6678: /*
6679: fprintf(ficgp,"\nunset parametric;unset label");
6680: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6681: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6682: 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);
6683: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6684: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6685: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6686: */
6687:
6688: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6689: first1=1;first2=2;
6690: for (k2=1; k2<=(nlstate);k2++){
6691: for (l2=1; l2<=(nlstate+ndeath);l2++){
6692: if(l2==k2) continue;
6693: j=(k2-1)*(nlstate+ndeath)+l2;
6694: for (k1=1; k1<=(nlstate);k1++){
6695: for (l1=1; l1<=(nlstate+ndeath);l1++){
6696: if(l1==k1) continue;
6697: i=(k1-1)*(nlstate+ndeath)+l1;
6698: if(i<=j) continue;
6699: for (age=bage; age<=fage; age ++){
6700: if ((int)age %5==0){
6701: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6702: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6703: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6704: mu1=mu[i][(int) age]/stepm*YEARM ;
6705: mu2=mu[j][(int) age]/stepm*YEARM;
6706: c12=cv12/sqrt(v1*v2);
6707: /* Computing eigen value of matrix of covariance */
6708: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6709: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6710: if ((lc2 <0) || (lc1 <0) ){
6711: if(first2==1){
6712: first1=0;
6713: 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);
6714: }
6715: 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);
6716: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6717: /* lc2=fabs(lc2); */
6718: }
1.220 brouard 6719:
1.222 brouard 6720: /* Eigen vectors */
1.280 brouard 6721: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
6722: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6723: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6724: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
6725: }else
6726: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 6727: /*v21=sqrt(1.-v11*v11); *//* error */
6728: v21=(lc1-v1)/cv12*v11;
6729: v12=-v21;
6730: v22=v11;
6731: tnalp=v21/v11;
6732: if(first1==1){
6733: first1=0;
6734: 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);
6735: }
6736: 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);
6737: /*printf(fignu*/
6738: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6739: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6740: if(first==1){
6741: first=0;
6742: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6743: fprintf(ficgp,"\nset parametric;unset label");
6744: 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);
6745: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6746: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6747: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6748: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6749: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6750: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6751: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6752: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6753: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6754: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6755: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6756: 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 6757: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
6758: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6759: }else{
6760: first=0;
6761: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6762: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6763: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6764: 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 6765: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6766: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6767: }/* if first */
6768: } /* age mod 5 */
6769: } /* end loop age */
6770: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6771: first=1;
6772: } /*l12 */
6773: } /* k12 */
6774: } /*l1 */
6775: }/* k1 */
6776: } /* loop on combination of covariates j1 */
6777: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6778: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6779: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6780: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6781: free_vector(xp,1,npar);
6782: fclose(ficresprob);
6783: fclose(ficresprobcov);
6784: fclose(ficresprobcor);
6785: fflush(ficgp);
6786: fflush(fichtmcov);
6787: }
1.126 brouard 6788:
6789:
6790: /******************* Printing html file ***********/
1.201 brouard 6791: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6792: int lastpass, int stepm, int weightopt, char model[],\
6793: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.258 brouard 6794: int popforecast, int mobilav, int prevfcast, int mobilavproj, int backcast, int estepm , \
1.273 brouard 6795: double jprev1, double mprev1,double anprev1, double dateprev1, double dateproj1, double dateback1, \
6796: double jprev2, double mprev2,double anprev2, double dateprev2, double dateproj2, double dateback2){
1.237 brouard 6797: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6798:
6799: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6800: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6801: </ul>");
1.237 brouard 6802: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6803: </ul>", model);
1.214 brouard 6804: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6805: 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",
6806: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6807: 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 6808: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6809: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6810: fprintf(fichtm,"\
6811: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6812: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6813: fprintf(fichtm,"\
1.217 brouard 6814: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6815: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6816: fprintf(fichtm,"\
1.288 brouard 6817: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6818: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6819: fprintf(fichtm,"\
1.288 brouard 6820: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 6821: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6822: fprintf(fichtm,"\
1.211 brouard 6823: - (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 6824: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6825: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6826: if(prevfcast==1){
6827: fprintf(fichtm,"\
6828: - Prevalence projections by age and states: \
1.201 brouard 6829: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6830: }
1.126 brouard 6831:
6832:
1.225 brouard 6833: m=pow(2,cptcoveff);
1.222 brouard 6834: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6835:
1.264 brouard 6836: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6837:
6838: jj1=0;
6839:
6840: fprintf(fichtm," \n<ul>");
6841: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6842: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6843: if(m != 1 && TKresult[nres]!= k1)
6844: continue;
6845: jj1++;
6846: if (cptcovn > 0) {
6847: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6848: for (cpt=1; cpt<=cptcoveff;cpt++){
6849: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6850: }
6851: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6852: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6853: }
6854: fprintf(fichtm,"\">");
6855:
6856: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6857: fprintf(fichtm,"************ Results for covariates");
6858: for (cpt=1; cpt<=cptcoveff;cpt++){
6859: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6860: }
6861: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6862: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6863: }
6864: if(invalidvarcomb[k1]){
6865: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
6866: continue;
6867: }
6868: fprintf(fichtm,"</a></li>");
6869: } /* cptcovn >0 */
6870: }
6871: fprintf(fichtm," \n</ul>");
6872:
1.222 brouard 6873: jj1=0;
1.237 brouard 6874:
6875: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6876: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6877: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6878: continue;
1.220 brouard 6879:
1.222 brouard 6880: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6881: jj1++;
6882: if (cptcovn > 0) {
1.264 brouard 6883: fprintf(fichtm,"\n<p><a name=\"rescov");
6884: for (cpt=1; cpt<=cptcoveff;cpt++){
6885: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6886: }
6887: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6888: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6889: }
6890: fprintf(fichtm,"\"</a>");
6891:
1.222 brouard 6892: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6893: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6894: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6895: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6896: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6897: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6898: }
1.237 brouard 6899: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6900: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6901: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6902: }
6903:
1.230 brouard 6904: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6905: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6906: if(invalidvarcomb[k1]){
6907: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6908: printf("\nCombination (%d) ignored because no cases \n",k1);
6909: continue;
6910: }
6911: }
6912: /* aij, bij */
1.259 brouard 6913: 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 6914: <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 6915: /* Pij */
1.241 brouard 6916: 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> \
6917: <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 6918: /* Quasi-incidences */
6919: 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 6920: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6921: 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 6922: 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> \
6923: <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 6924: /* Survival functions (period) in state j */
6925: for(cpt=1; cpt<=nlstate;cpt++){
1.241 brouard 6926: fprintf(fichtm,"<br>\n- Survival functions in state %d. Or probability to survive 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> \
6927: <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 6928: }
6929: /* State specific survival functions (period) */
6930: for(cpt=1; cpt<=nlstate;cpt++){
6931: fprintf(fichtm,"<br>\n- Survival functions from state %d in each live state and total.\
1.220 brouard 6932: Or probability to survive in various states (1 to %d) being in state %d at different ages. \
1.283 brouard 6933: <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 6934: }
1.288 brouard 6935: /* Period (forward stable) prevalence in each health state */
1.222 brouard 6936: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6937: 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> \
6938: <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 6939: }
6940: if(backcast==1){
1.288 brouard 6941: /* Backward prevalence in each health state */
1.222 brouard 6942: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6943: 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 6944: <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 6945: }
1.217 brouard 6946: }
1.222 brouard 6947: if(prevfcast==1){
1.288 brouard 6948: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 6949: for(cpt=1; cpt<=nlstate;cpt++){
1.288 brouard 6950: 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> \
1.273 brouard 6951: <img src=\"%s_%d-%d-%d.svg\">", dateprev1, dateprev2, mobilavproj, dateproj1, dateproj2, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 6952: }
6953: }
1.268 brouard 6954: if(backcast==1){
6955: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
6956: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 6957: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
6958: 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 \
6959: 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) \
6960: with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
6961: <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 6962: }
6963: }
1.220 brouard 6964:
1.222 brouard 6965: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 6966: 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> \
6967: <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 6968: }
6969: /* } /\* end i1 *\/ */
6970: }/* End k1 */
6971: fprintf(fichtm,"</ul>");
1.126 brouard 6972:
1.222 brouard 6973: fprintf(fichtm,"\
1.126 brouard 6974: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 6975: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 6976: - 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 6977: But because parameters are usually highly correlated (a higher incidence of disability \
6978: and a higher incidence of recovery can give very close observed transition) it might \
6979: be very useful to look not only at linear confidence intervals estimated from the \
6980: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
6981: (parameters) of the logistic regression, it might be more meaningful to visualize the \
6982: covariance matrix of the one-step probabilities. \
6983: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 6984:
1.222 brouard 6985: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
6986: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
6987: fprintf(fichtm,"\
1.126 brouard 6988: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6989: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 6990:
1.222 brouard 6991: fprintf(fichtm,"\
1.126 brouard 6992: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6993: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
6994: fprintf(fichtm,"\
1.126 brouard 6995: - 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): \
6996: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6997: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 6998: fprintf(fichtm,"\
1.126 brouard 6999: - (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): \
7000: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 7001: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 7002: fprintf(fichtm,"\
1.288 brouard 7003: - 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 7004: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7005: fprintf(fichtm,"\
1.128 brouard 7006: - 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 7007: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7008: fprintf(fichtm,"\
1.288 brouard 7009: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7010: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7011:
7012: /* if(popforecast==1) fprintf(fichtm,"\n */
7013: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7014: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7015: /* <br>",fileres,fileres,fileres,fileres); */
7016: /* else */
7017: /* 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 7018: fflush(fichtm);
7019: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 7020:
1.225 brouard 7021: m=pow(2,cptcoveff);
1.222 brouard 7022: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7023:
1.222 brouard 7024: jj1=0;
1.237 brouard 7025:
1.241 brouard 7026: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7027: for(k1=1; k1<=m;k1++){
1.253 brouard 7028: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7029: continue;
1.222 brouard 7030: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7031: jj1++;
1.126 brouard 7032: if (cptcovn > 0) {
7033: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7034: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 7035: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
7036: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7037: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7038: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7039: }
7040:
1.126 brouard 7041: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 7042:
1.222 brouard 7043: if(invalidvarcomb[k1]){
7044: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7045: continue;
7046: }
1.126 brouard 7047: }
7048: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7049: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 7050: 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 7051: <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 7052: }
7053: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 7054: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
7055: true period expectancies (those weighted with period prevalences are also\
7056: drawn in addition to the population based expectancies computed using\
1.241 brouard 7057: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
7058: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7059: /* } /\* end i1 *\/ */
7060: }/* End k1 */
1.241 brouard 7061: }/* End nres */
1.222 brouard 7062: fprintf(fichtm,"</ul>");
7063: fflush(fichtm);
1.126 brouard 7064: }
7065:
7066: /******************* Gnuplot file **************/
1.270 brouard 7067: void printinggnuplot(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double bage, double fage , int prevfcast, int backcast, char pathc[], double p[], int offyear, int offbyear){
1.126 brouard 7068:
7069: char dirfileres[132],optfileres[132];
1.264 brouard 7070: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7071: 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 7072: int lv=0, vlv=0, kl=0;
1.130 brouard 7073: int ng=0;
1.201 brouard 7074: int vpopbased;
1.223 brouard 7075: int ioffset; /* variable offset for columns */
1.270 brouard 7076: int iyearc=1; /* variable column for year of projection */
7077: int iagec=1; /* variable column for age of projection */
1.235 brouard 7078: int nres=0; /* Index of resultline */
1.266 brouard 7079: int istart=1; /* For starting graphs in projections */
1.219 brouard 7080:
1.126 brouard 7081: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7082: /* printf("Problem with file %s",optionfilegnuplot); */
7083: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7084: /* } */
7085:
7086: /*#ifdef windows */
7087: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7088: /*#endif */
1.225 brouard 7089: m=pow(2,cptcoveff);
1.126 brouard 7090:
1.274 brouard 7091: /* diagram of the model */
7092: fprintf(ficgp,"\n#Diagram of the model \n");
7093: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7094: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7095: 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);
7096:
7097: 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);
7098: fprintf(ficgp,"\n#show arrow\nunset label\n");
7099: 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);
7100: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7101: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7102: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7103: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7104:
1.202 brouard 7105: /* Contribution to likelihood */
7106: /* Plot the probability implied in the likelihood */
1.223 brouard 7107: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7108: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7109: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7110: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7111: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7112: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7113: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7114: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7115: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7116: 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));
7117: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7118: 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));
7119: for (i=1; i<= nlstate ; i ++) {
7120: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7121: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7122: 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);
7123: for (j=2; j<= nlstate+ndeath ; j ++) {
7124: 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);
7125: }
7126: fprintf(ficgp,";\nset out; unset ylabel;\n");
7127: }
7128: /* 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 */
7129: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7130: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7131: fprintf(ficgp,"\nset out;unset log\n");
7132: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7133:
1.126 brouard 7134: strcpy(dirfileres,optionfilefiname);
7135: strcpy(optfileres,"vpl");
1.223 brouard 7136: /* 1eme*/
1.238 brouard 7137: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7138: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7139: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7140: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7141: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7142: continue;
7143: /* We are interested in selected combination by the resultline */
1.246 brouard 7144: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7145: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7146: strcpy(gplotlabel,"(");
1.238 brouard 7147: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7148: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7149: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7150: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7151: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7152: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7153: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7154: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7155: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7156: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7157: }
7158: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7159: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7160: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7161: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7162: }
7163: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7164: /* printf("\n#\n"); */
1.238 brouard 7165: fprintf(ficgp,"\n#\n");
7166: if(invalidvarcomb[k1]){
1.260 brouard 7167: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7168: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7169: continue;
7170: }
1.235 brouard 7171:
1.241 brouard 7172: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7173: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7174: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
7175: fprintf(ficgp,"set title \"Alive state %d %s\" font \"Helvetica,12\"\n",cpt,gplotlabel);
1.260 brouard 7176: 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);
7177: /* 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); */
7178: /* k1-1 error should be nres-1*/
1.238 brouard 7179: for (i=1; i<= nlstate ; i ++) {
7180: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7181: else fprintf(ficgp," %%*lf (%%*lf)");
7182: }
1.288 brouard 7183: 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 7184: for (i=1; i<= nlstate ; i ++) {
7185: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7186: else fprintf(ficgp," %%*lf (%%*lf)");
7187: }
1.260 brouard 7188: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7189: for (i=1; i<= nlstate ; i ++) {
7190: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7191: else fprintf(ficgp," %%*lf (%%*lf)");
7192: }
1.265 brouard 7193: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7194:
7195: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7196: if(cptcoveff ==0){
1.271 brouard 7197: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7198: }else{
7199: kl=0;
7200: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7201: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7202: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7203: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7204: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7205: vlv= nbcode[Tvaraff[k]][lv];
7206: kl++;
7207: /* 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 *\/ */
7208: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7209: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7210: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7211: if(k==cptcoveff){
7212: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7213: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7214: }else{
7215: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7216: kl++;
7217: }
7218: } /* end covariate */
7219: } /* end if no covariate */
7220:
1.238 brouard 7221: if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
7222: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7223: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7224: if(cptcoveff ==0){
1.245 brouard 7225: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7226: }else{
7227: kl=0;
7228: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7229: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7230: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7231: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7232: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7233: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7234: kl++;
1.238 brouard 7235: /* 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 *\/ */
7236: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7237: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7238: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7239: if(k==cptcoveff){
1.245 brouard 7240: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7241: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7242: }else{
7243: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7244: kl++;
7245: }
7246: } /* end covariate */
7247: } /* end if no covariate */
1.268 brouard 7248: if(backcast == 1){
7249: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7250: /* k1-1 error should be nres-1*/
7251: for (i=1; i<= nlstate ; i ++) {
7252: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7253: else fprintf(ficgp," %%*lf (%%*lf)");
7254: }
1.271 brouard 7255: 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 7256: for (i=1; i<= nlstate ; i ++) {
7257: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7258: else fprintf(ficgp," %%*lf (%%*lf)");
7259: }
1.276 brouard 7260: 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 7261: for (i=1; i<= nlstate ; i ++) {
7262: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7263: else fprintf(ficgp," %%*lf (%%*lf)");
7264: }
1.274 brouard 7265: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7266: } /* end if backprojcast */
1.238 brouard 7267: } /* end if backcast */
1.276 brouard 7268: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7269: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7270: } /* nres */
1.201 brouard 7271: } /* k1 */
7272: } /* cpt */
1.235 brouard 7273:
7274:
1.126 brouard 7275: /*2 eme*/
1.238 brouard 7276: for (k1=1; k1<= m ; k1 ++){
7277: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7278: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7279: continue;
7280: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7281: strcpy(gplotlabel,"(");
1.238 brouard 7282: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7283: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7284: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7285: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7286: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7287: vlv= nbcode[Tvaraff[k]][lv];
7288: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7289: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7290: }
1.237 brouard 7291: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7292: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7293: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7294: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7295: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7296: }
1.264 brouard 7297: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7298: fprintf(ficgp,"\n#\n");
1.223 brouard 7299: if(invalidvarcomb[k1]){
7300: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7301: continue;
7302: }
1.219 brouard 7303:
1.241 brouard 7304: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7305: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7306: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7307: if(vpopbased==0){
1.238 brouard 7308: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7309: }else
1.238 brouard 7310: fprintf(ficgp,"\nreplot ");
7311: for (i=1; i<= nlstate+1 ; i ++) {
7312: k=2*i;
1.261 brouard 7313: 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 7314: for (j=1; j<= nlstate+1 ; j ++) {
7315: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7316: else fprintf(ficgp," %%*lf (%%*lf)");
7317: }
7318: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7319: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7320: 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 7321: for (j=1; j<= nlstate+1 ; j ++) {
7322: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7323: else fprintf(ficgp," %%*lf (%%*lf)");
7324: }
7325: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7326: 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 7327: for (j=1; j<= nlstate+1 ; j ++) {
7328: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7329: else fprintf(ficgp," %%*lf (%%*lf)");
7330: }
7331: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7332: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7333: } /* state */
7334: } /* vpopbased */
1.264 brouard 7335: 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 7336: } /* end nres */
7337: } /* k1 end 2 eme*/
7338:
7339:
7340: /*3eme*/
7341: for (k1=1; k1<= m ; k1 ++){
7342: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7343: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7344: continue;
7345:
7346: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7347: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7348: strcpy(gplotlabel,"(");
1.238 brouard 7349: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7350: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7351: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7352: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7353: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7354: vlv= nbcode[Tvaraff[k]][lv];
7355: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7356: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7357: }
7358: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7359: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7360: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7361: }
1.264 brouard 7362: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7363: fprintf(ficgp,"\n#\n");
7364: if(invalidvarcomb[k1]){
7365: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7366: continue;
7367: }
7368:
7369: /* k=2+nlstate*(2*cpt-2); */
7370: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7371: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7372: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7373: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7374: 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 7375: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7376: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7377: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7378: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7379: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7380: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7381:
1.238 brouard 7382: */
7383: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7384: 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 7385: /* 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 7386:
1.238 brouard 7387: }
1.261 brouard 7388: 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 7389: }
1.264 brouard 7390: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7391: } /* end nres */
7392: } /* end kl 3eme */
1.126 brouard 7393:
1.223 brouard 7394: /* 4eme */
1.201 brouard 7395: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7396: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7397: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7398: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7399: continue;
1.238 brouard 7400: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7401: strcpy(gplotlabel,"(");
1.238 brouard 7402: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7403: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7404: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7405: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7406: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7407: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7408: vlv= nbcode[Tvaraff[k]][lv];
7409: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7410: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7411: }
7412: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7413: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7414: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7415: }
1.264 brouard 7416: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7417: fprintf(ficgp,"\n#\n");
7418: if(invalidvarcomb[k1]){
7419: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7420: continue;
1.223 brouard 7421: }
1.238 brouard 7422:
1.241 brouard 7423: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7424: 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 7425: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7426: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7427: k=3;
7428: for (i=1; i<= nlstate ; i ++){
7429: if(i==1){
7430: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7431: }else{
7432: fprintf(ficgp,", '' ");
7433: }
7434: l=(nlstate+ndeath)*(i-1)+1;
7435: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7436: for (j=2; j<= nlstate+ndeath ; j ++)
7437: fprintf(ficgp,"+$%d",k+l+j-1);
7438: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7439: } /* nlstate */
1.264 brouard 7440: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7441: } /* end cpt state*/
7442: } /* end nres */
7443: } /* end covariate k1 */
7444:
1.220 brouard 7445: /* 5eme */
1.201 brouard 7446: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7447: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7448: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7449: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7450: continue;
1.238 brouard 7451: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7452: strcpy(gplotlabel,"(");
1.238 brouard 7453: 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);
7454: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7455: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7456: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7457: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7458: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7459: vlv= nbcode[Tvaraff[k]][lv];
7460: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7461: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7462: }
7463: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7464: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7465: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7466: }
1.264 brouard 7467: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7468: fprintf(ficgp,"\n#\n");
7469: if(invalidvarcomb[k1]){
7470: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7471: continue;
7472: }
1.227 brouard 7473:
1.241 brouard 7474: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7475: 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 7476: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7477: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7478: k=3;
7479: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7480: if(j==1)
7481: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7482: else
7483: fprintf(ficgp,", '' ");
7484: l=(nlstate+ndeath)*(cpt-1) +j;
7485: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7486: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7487: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7488: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7489: } /* nlstate */
7490: fprintf(ficgp,", '' ");
7491: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7492: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7493: l=(nlstate+ndeath)*(cpt-1) +j;
7494: if(j < nlstate)
7495: fprintf(ficgp,"$%d +",k+l);
7496: else
7497: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7498: }
1.264 brouard 7499: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7500: } /* end cpt state*/
7501: } /* end covariate */
7502: } /* end nres */
1.227 brouard 7503:
1.220 brouard 7504: /* 6eme */
1.202 brouard 7505: /* CV preval stable (period) for each covariate */
1.237 brouard 7506: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7507: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7508: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7509: continue;
1.255 brouard 7510: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7511: strcpy(gplotlabel,"(");
1.288 brouard 7512: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7513: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7514: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7515: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7516: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7517: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7518: vlv= nbcode[Tvaraff[k]][lv];
7519: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7520: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7521: }
1.237 brouard 7522: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7523: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7524: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7525: }
1.264 brouard 7526: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7527: fprintf(ficgp,"\n#\n");
1.223 brouard 7528: if(invalidvarcomb[k1]){
1.227 brouard 7529: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7530: continue;
1.223 brouard 7531: }
1.227 brouard 7532:
1.241 brouard 7533: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7534: 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 7535: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7536: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7537: k=3; /* Offset */
1.255 brouard 7538: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7539: if(i==1)
7540: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7541: else
7542: fprintf(ficgp,", '' ");
1.255 brouard 7543: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7544: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7545: for (j=2; j<= nlstate ; j ++)
7546: fprintf(ficgp,"+$%d",k+l+j-1);
7547: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7548: } /* nlstate */
1.264 brouard 7549: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7550: } /* end cpt state*/
7551: } /* end covariate */
1.227 brouard 7552:
7553:
1.220 brouard 7554: /* 7eme */
1.218 brouard 7555: if(backcast == 1){
1.288 brouard 7556: /* CV backward prevalence for each covariate */
1.237 brouard 7557: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7558: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7559: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7560: continue;
1.268 brouard 7561: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7562: strcpy(gplotlabel,"(");
1.288 brouard 7563: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7564: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7565: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7566: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7567: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7568: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7569: vlv= nbcode[Tvaraff[k]][lv];
7570: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7571: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7572: }
1.237 brouard 7573: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7574: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7575: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7576: }
1.264 brouard 7577: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7578: fprintf(ficgp,"\n#\n");
7579: if(invalidvarcomb[k1]){
7580: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7581: continue;
7582: }
7583:
1.241 brouard 7584: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7585: 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 7586: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7587: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7588: k=3; /* Offset */
1.268 brouard 7589: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7590: if(i==1)
7591: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7592: else
7593: fprintf(ficgp,", '' ");
7594: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7595: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7596: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7597: /* 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 7598: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7599: /* for (j=2; j<= nlstate ; j ++) */
7600: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7601: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7602: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7603: } /* nlstate */
1.264 brouard 7604: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7605: } /* end cpt state*/
7606: } /* end covariate */
7607: } /* End if backcast */
7608:
1.223 brouard 7609: /* 8eme */
1.218 brouard 7610: if(prevfcast==1){
1.288 brouard 7611: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 7612:
1.237 brouard 7613: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7614: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7615: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7616: continue;
1.211 brouard 7617: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7618: strcpy(gplotlabel,"(");
1.288 brouard 7619: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7620: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7621: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7622: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7623: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7624: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7625: vlv= nbcode[Tvaraff[k]][lv];
7626: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7627: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7628: }
1.237 brouard 7629: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7630: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7631: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7632: }
1.264 brouard 7633: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7634: fprintf(ficgp,"\n#\n");
7635: if(invalidvarcomb[k1]){
7636: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7637: continue;
7638: }
7639:
7640: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7641: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7642: 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 7643: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7644: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7645:
7646: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7647: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7648: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7649: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7650: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7651: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7652: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7653: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7654: if(i==istart){
1.227 brouard 7655: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7656: }else{
7657: fprintf(ficgp,",\\\n '' ");
7658: }
7659: if(cptcoveff ==0){ /* No covariate */
7660: ioffset=2; /* Age is in 2 */
7661: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7662: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7663: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7664: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7665: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7666: if(i==nlstate+1){
1.270 brouard 7667: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 7668: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7669: fprintf(ficgp,",\\\n '' ");
7670: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7671: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 7672: offyear, \
1.268 brouard 7673: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7674: }else
1.227 brouard 7675: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7676: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7677: }else{ /* more than 2 covariates */
1.270 brouard 7678: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7679: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7680: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7681: iyearc=ioffset-1;
7682: iagec=ioffset;
1.227 brouard 7683: fprintf(ficgp," u %d:(",ioffset);
7684: kl=0;
7685: strcpy(gplotcondition,"(");
7686: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7687: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7688: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7689: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7690: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7691: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7692: kl++;
7693: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7694: kl++;
7695: if(k <cptcoveff && cptcoveff>1)
7696: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7697: }
7698: strcpy(gplotcondition+strlen(gplotcondition),")");
7699: /* 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 *\/ */
7700: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7701: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7702: /* '' 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*/
7703: if(i==nlstate+1){
1.270 brouard 7704: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
7705: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 7706: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7707: fprintf(ficgp," u %d:(",iagec);
7708: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
7709: iyearc, iagec, offyear, \
7710: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 7711: /* '' 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 7712: }else{
7713: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7714: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7715: }
7716: } /* end if covariate */
7717: } /* nlstate */
1.264 brouard 7718: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7719: } /* end cpt state*/
7720: } /* end covariate */
7721: } /* End if prevfcast */
1.227 brouard 7722:
1.268 brouard 7723: if(backcast==1){
7724: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7725:
7726: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7727: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7728: if(m != 1 && TKresult[nres]!= k1)
7729: continue;
7730: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7731: strcpy(gplotlabel,"(");
7732: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7733: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7734: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7735: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7736: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7737: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7738: vlv= nbcode[Tvaraff[k]][lv];
7739: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7740: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7741: }
7742: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7743: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7744: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7745: }
7746: strcpy(gplotlabel+strlen(gplotlabel),")");
7747: fprintf(ficgp,"\n#\n");
7748: if(invalidvarcomb[k1]){
7749: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7750: continue;
7751: }
7752:
7753: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7754: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7755: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7756: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7757: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7758:
7759: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7760: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7761: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7762: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7763: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7764: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7765: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7766: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7767: if(i==istart){
7768: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
7769: }else{
7770: fprintf(ficgp,",\\\n '' ");
7771: }
7772: if(cptcoveff ==0){ /* No covariate */
7773: ioffset=2; /* Age is in 2 */
7774: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7775: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7776: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7777: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7778: fprintf(ficgp," u %d:(", ioffset);
7779: if(i==nlstate+1){
1.270 brouard 7780: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 7781: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7782: fprintf(ficgp,",\\\n '' ");
7783: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7784: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 7785: offbyear, \
7786: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7787: }else
7788: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
7789: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
7790: }else{ /* more than 2 covariates */
1.270 brouard 7791: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7792: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7793: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7794: iyearc=ioffset-1;
7795: iagec=ioffset;
1.268 brouard 7796: fprintf(ficgp," u %d:(",ioffset);
7797: kl=0;
7798: strcpy(gplotcondition,"(");
7799: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7800: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7801: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7802: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7803: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7804: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7805: kl++;
7806: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7807: kl++;
7808: if(k <cptcoveff && cptcoveff>1)
7809: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7810: }
7811: strcpy(gplotcondition+strlen(gplotcondition),")");
7812: /* 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 *\/ */
7813: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7814: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7815: /* '' 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*/
7816: if(i==nlstate+1){
1.270 brouard 7817: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
7818: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 7819: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7820: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 7821: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 7822: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
7823: iyearc,iagec,offbyear, \
7824: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 7825: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
7826: }else{
7827: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
7828: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
7829: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
7830: }
7831: } /* end if covariate */
7832: } /* nlstate */
7833: fprintf(ficgp,"\nset out; unset label;\n");
7834: } /* end cpt state*/
7835: } /* end covariate */
7836: } /* End if backcast */
7837:
1.227 brouard 7838:
1.238 brouard 7839: /* 9eme writing MLE parameters */
7840: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7841: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7842: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7843: for(k=1; k <=(nlstate+ndeath); k++){
7844: if (k != i) {
1.227 brouard 7845: fprintf(ficgp,"# current state %d\n",k);
7846: for(j=1; j <=ncovmodel; j++){
7847: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7848: jk++;
7849: }
7850: fprintf(ficgp,"\n");
1.126 brouard 7851: }
7852: }
1.223 brouard 7853: }
1.187 brouard 7854: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7855:
1.145 brouard 7856: /*goto avoid;*/
1.238 brouard 7857: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7858: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7859: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7860: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7861: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7862: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7863: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7864: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7865: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7866: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7867: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7868: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7869: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7870: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7871: fprintf(ficgp,"#\n");
1.223 brouard 7872: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7873: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7874: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7875: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 7876: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
7877: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7878: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 7879: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7880: continue;
1.264 brouard 7881: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
7882: strcpy(gplotlabel,"(");
1.276 brouard 7883: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 7884: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7885: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7886: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7887: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7888: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7889: vlv= nbcode[Tvaraff[k]][lv];
7890: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7891: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7892: }
1.237 brouard 7893: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7894: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7895: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7896: }
1.264 brouard 7897: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7898: fprintf(ficgp,"\n#\n");
1.264 brouard 7899: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 7900: fprintf(ficgp,"\nset key outside ");
7901: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
7902: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7903: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7904: if (ng==1){
7905: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7906: fprintf(ficgp,"\nunset log y");
7907: }else if (ng==2){
7908: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7909: fprintf(ficgp,"\nset log y");
7910: }else if (ng==3){
7911: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7912: fprintf(ficgp,"\nset log y");
7913: }else
7914: fprintf(ficgp,"\nunset title ");
7915: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7916: i=1;
7917: for(k2=1; k2<=nlstate; k2++) {
7918: k3=i;
7919: for(k=1; k<=(nlstate+ndeath); k++) {
7920: if (k != k2){
7921: switch( ng) {
7922: case 1:
7923: if(nagesqr==0)
7924: fprintf(ficgp," p%d+p%d*x",i,i+1);
7925: else /* nagesqr =1 */
7926: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7927: break;
7928: case 2: /* ng=2 */
7929: if(nagesqr==0)
7930: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
7931: else /* nagesqr =1 */
7932: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7933: break;
7934: case 3:
7935: if(nagesqr==0)
7936: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
7937: else /* nagesqr =1 */
7938: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
7939: break;
7940: }
7941: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 7942: ijp=1; /* product no age */
7943: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
7944: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 7945: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 7946: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7947: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
7948: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7949: if(DummyV[j]==0){
7950: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
7951: }else{ /* quantitative */
7952: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
7953: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7954: }
7955: ij++;
1.237 brouard 7956: }
1.268 brouard 7957: }
7958: }else if(cptcovprod >0){
7959: if(j==Tprod[ijp]) { /* */
7960: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
7961: if(ijp <=cptcovprod) { /* Product */
7962: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
7963: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
7964: /* 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)]); */
7965: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
7966: }else{ /* Vn is dummy and Vm is quanti */
7967: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
7968: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7969: }
7970: }else{ /* Vn*Vm Vn is quanti */
7971: if(DummyV[Tvard[ijp][2]]==0){
7972: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
7973: }else{ /* Both quanti */
7974: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7975: }
1.237 brouard 7976: }
1.268 brouard 7977: ijp++;
1.237 brouard 7978: }
1.268 brouard 7979: } /* end Tprod */
1.237 brouard 7980: } else{ /* simple covariate */
1.264 brouard 7981: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 7982: if(Dummy[j]==0){
7983: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
7984: }else{ /* quantitative */
7985: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 7986: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 7987: }
1.237 brouard 7988: } /* end simple */
7989: } /* end j */
1.223 brouard 7990: }else{
7991: i=i-ncovmodel;
7992: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
7993: fprintf(ficgp," (1.");
7994: }
1.227 brouard 7995:
1.223 brouard 7996: if(ng != 1){
7997: fprintf(ficgp,")/(1");
1.227 brouard 7998:
1.264 brouard 7999: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 8000: if(nagesqr==0)
1.264 brouard 8001: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 8002: else /* nagesqr =1 */
1.264 brouard 8003: 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 8004:
1.223 brouard 8005: ij=1;
8006: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 8007: if(cptcovage >0){
8008: if((j-2)==Tage[ij]) { /* Bug valgrind */
8009: if(ij <=cptcovage) { /* Bug valgrind */
8010: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
8011: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8012: ij++;
8013: }
8014: }
8015: }else
8016: 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 8017: }
8018: fprintf(ficgp,")");
8019: }
8020: fprintf(ficgp,")");
8021: if(ng ==2)
1.276 brouard 8022: 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 8023: else /* ng= 3 */
1.276 brouard 8024: 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 8025: }else{ /* end ng <> 1 */
8026: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8027: 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 8028: }
8029: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8030: fprintf(ficgp,",");
8031: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8032: fprintf(ficgp,",");
8033: i=i+ncovmodel;
8034: } /* end k */
8035: } /* end k2 */
1.276 brouard 8036: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8037: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8038: } /* end k1 */
1.223 brouard 8039: } /* end ng */
8040: /* avoid: */
8041: fflush(ficgp);
1.126 brouard 8042: } /* end gnuplot */
8043:
8044:
8045: /*************** Moving average **************/
1.219 brouard 8046: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8047: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8048:
1.222 brouard 8049: int i, cpt, cptcod;
8050: int modcovmax =1;
8051: int mobilavrange, mob;
8052: int iage=0;
1.288 brouard 8053: int firstA1=0, firstA2=0;
1.222 brouard 8054:
1.266 brouard 8055: double sum=0., sumr=0.;
1.222 brouard 8056: double age;
1.266 brouard 8057: double *sumnewp, *sumnewm, *sumnewmr;
8058: double *agemingood, *agemaxgood;
8059: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8060:
8061:
1.278 brouard 8062: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8063: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8064:
8065: sumnewp = vector(1,ncovcombmax);
8066: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8067: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8068: agemingood = vector(1,ncovcombmax);
1.266 brouard 8069: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8070: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8071: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8072:
8073: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8074: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8075: sumnewp[cptcod]=0.;
1.266 brouard 8076: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8077: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8078: }
8079: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8080:
1.266 brouard 8081: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8082: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8083: else mobilavrange=mobilav;
8084: for (age=bage; age<=fage; age++)
8085: for (i=1; i<=nlstate;i++)
8086: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8087: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8088: /* We keep the original values on the extreme ages bage, fage and for
8089: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8090: we use a 5 terms etc. until the borders are no more concerned.
8091: */
8092: for (mob=3;mob <=mobilavrange;mob=mob+2){
8093: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8094: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8095: sumnewm[cptcod]=0.;
8096: for (i=1; i<=nlstate;i++){
1.222 brouard 8097: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8098: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8099: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8100: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8101: }
8102: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8103: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8104: } /* end i */
8105: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8106: } /* end cptcod */
1.222 brouard 8107: }/* end age */
8108: }/* end mob */
1.266 brouard 8109: }else{
8110: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8111: return -1;
1.266 brouard 8112: }
8113:
8114: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8115: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8116: if(invalidvarcomb[cptcod]){
8117: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8118: continue;
8119: }
1.219 brouard 8120:
1.266 brouard 8121: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8122: sumnewm[cptcod]=0.;
8123: sumnewmr[cptcod]=0.;
8124: for (i=1; i<=nlstate;i++){
8125: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8126: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8127: }
8128: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8129: agemingoodr[cptcod]=age;
8130: }
8131: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8132: agemingood[cptcod]=age;
8133: }
8134: } /* age */
8135: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8136: sumnewm[cptcod]=0.;
1.266 brouard 8137: sumnewmr[cptcod]=0.;
1.222 brouard 8138: for (i=1; i<=nlstate;i++){
8139: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8140: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8141: }
8142: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8143: agemaxgoodr[cptcod]=age;
1.222 brouard 8144: }
8145: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8146: agemaxgood[cptcod]=age;
8147: }
8148: } /* age */
8149: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8150: /* but they will change */
1.288 brouard 8151: firstA1=0;firstA2=0;
1.266 brouard 8152: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8153: sumnewm[cptcod]=0.;
8154: sumnewmr[cptcod]=0.;
8155: for (i=1; i<=nlstate;i++){
8156: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8157: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8158: }
8159: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8160: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8161: agemaxgoodr[cptcod]=age; /* age min */
8162: for (i=1; i<=nlstate;i++)
8163: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8164: }else{ /* bad we change the value with the values of good ages */
8165: for (i=1; i<=nlstate;i++){
8166: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8167: } /* i */
8168: } /* end bad */
8169: }else{
8170: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8171: agemaxgood[cptcod]=age;
8172: }else{ /* bad we change the value with the values of good ages */
8173: for (i=1; i<=nlstate;i++){
8174: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8175: } /* i */
8176: } /* end bad */
8177: }/* end else */
8178: sum=0.;sumr=0.;
8179: for (i=1; i<=nlstate;i++){
8180: sum+=mobaverage[(int)age][i][cptcod];
8181: sumr+=probs[(int)age][i][cptcod];
8182: }
8183: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8184: if(!firstA1){
8185: firstA1=1;
8186: 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);
8187: }
8188: 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 8189: } /* end bad */
8190: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8191: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 8192: if(!firstA2){
8193: firstA2=1;
8194: 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);
8195: }
8196: 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 8197: } /* end bad */
8198: }/* age */
1.266 brouard 8199:
8200: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8201: sumnewm[cptcod]=0.;
1.266 brouard 8202: sumnewmr[cptcod]=0.;
1.222 brouard 8203: for (i=1; i<=nlstate;i++){
8204: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8205: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8206: }
8207: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8208: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8209: agemingoodr[cptcod]=age;
8210: for (i=1; i<=nlstate;i++)
8211: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8212: }else{ /* bad we change the value with the values of good ages */
8213: for (i=1; i<=nlstate;i++){
8214: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8215: } /* i */
8216: } /* end bad */
8217: }else{
8218: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8219: agemingood[cptcod]=age;
8220: }else{ /* bad */
8221: for (i=1; i<=nlstate;i++){
8222: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8223: } /* i */
8224: } /* end bad */
8225: }/* end else */
8226: sum=0.;sumr=0.;
8227: for (i=1; i<=nlstate;i++){
8228: sum+=mobaverage[(int)age][i][cptcod];
8229: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8230: }
1.266 brouard 8231: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8232: 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 8233: } /* end bad */
8234: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8235: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8236: 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 8237: } /* end bad */
8238: }/* age */
1.266 brouard 8239:
1.222 brouard 8240:
8241: for (age=bage; age<=fage; age++){
1.235 brouard 8242: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8243: sumnewp[cptcod]=0.;
8244: sumnewm[cptcod]=0.;
8245: for (i=1; i<=nlstate;i++){
8246: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8247: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8248: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8249: }
8250: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8251: }
8252: /* printf("\n"); */
8253: /* } */
1.266 brouard 8254:
1.222 brouard 8255: /* brutal averaging */
1.266 brouard 8256: /* for (i=1; i<=nlstate;i++){ */
8257: /* for (age=1; age<=bage; age++){ */
8258: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8259: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8260: /* } */
8261: /* for (age=fage; age<=AGESUP; age++){ */
8262: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8263: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8264: /* } */
8265: /* } /\* end i status *\/ */
8266: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8267: /* for (age=1; age<=AGESUP; age++){ */
8268: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8269: /* mobaverage[(int)age][i][cptcod]=0.; */
8270: /* } */
8271: /* } */
1.222 brouard 8272: }/* end cptcod */
1.266 brouard 8273: free_vector(agemaxgoodr,1, ncovcombmax);
8274: free_vector(agemaxgood,1, ncovcombmax);
8275: free_vector(agemingood,1, ncovcombmax);
8276: free_vector(agemingoodr,1, ncovcombmax);
8277: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8278: free_vector(sumnewm,1, ncovcombmax);
8279: free_vector(sumnewp,1, ncovcombmax);
8280: return 0;
8281: }/* End movingaverage */
1.218 brouard 8282:
1.126 brouard 8283:
8284: /************** Forecasting ******************/
1.269 brouard 8285: void prevforecast(char fileres[], double anproj1, double mproj1, double jproj1, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double ***prev, double bage, double fage, int firstpass, int lastpass, double anproj2, double p[], int cptcoveff){
1.126 brouard 8286: /* proj1, year, month, day of starting projection
8287: agemin, agemax range of age
8288: dateprev1 dateprev2 range of dates during which prevalence is computed
8289: anproj2 year of en of projection (same day and month as proj1).
8290: */
1.267 brouard 8291: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8292: double agec; /* generic age */
8293: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
8294: double *popeffectif,*popcount;
8295: double ***p3mat;
1.218 brouard 8296: /* double ***mobaverage; */
1.126 brouard 8297: char fileresf[FILENAMELENGTH];
8298:
8299: agelim=AGESUP;
1.211 brouard 8300: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8301: in each health status at the date of interview (if between dateprev1 and dateprev2).
8302: We still use firstpass and lastpass as another selection.
8303: */
1.214 brouard 8304: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8305: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8306:
1.201 brouard 8307: strcpy(fileresf,"F_");
8308: strcat(fileresf,fileresu);
1.126 brouard 8309: if((ficresf=fopen(fileresf,"w"))==NULL) {
8310: printf("Problem with forecast resultfile: %s\n", fileresf);
8311: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8312: }
1.235 brouard 8313: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8314: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8315:
1.225 brouard 8316: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8317:
8318:
8319: stepsize=(int) (stepm+YEARM-1)/YEARM;
8320: if (stepm<=12) stepsize=1;
8321: if(estepm < stepm){
8322: printf ("Problem %d lower than %d\n",estepm, stepm);
8323: }
1.270 brouard 8324: else{
8325: hstepm=estepm;
8326: }
8327: if(estepm > stepm){ /* Yes every two year */
8328: stepsize=2;
8329: }
1.126 brouard 8330:
8331: hstepm=hstepm/stepm;
8332: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8333: fractional in yp1 */
8334: anprojmean=yp;
8335: yp2=modf((yp1*12),&yp);
8336: mprojmean=yp;
8337: yp1=modf((yp2*30.5),&yp);
8338: jprojmean=yp;
8339: if(jprojmean==0) jprojmean=1;
8340: if(mprojmean==0) jprojmean=1;
8341:
1.227 brouard 8342: i1=pow(2,cptcoveff);
1.126 brouard 8343: if (cptcovn < 1){i1=1;}
8344:
8345: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
8346:
8347: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8348:
1.126 brouard 8349: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8350: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8351: for(k=1; k<=i1;k++){
1.253 brouard 8352: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8353: continue;
1.227 brouard 8354: if(invalidvarcomb[k]){
8355: printf("\nCombination (%d) projection ignored because no cases \n",k);
8356: continue;
8357: }
8358: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8359: for(j=1;j<=cptcoveff;j++) {
8360: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8361: }
1.235 brouard 8362: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8363: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8364: }
1.227 brouard 8365: fprintf(ficresf," yearproj age");
8366: for(j=1; j<=nlstate+ndeath;j++){
8367: for(i=1; i<=nlstate;i++)
8368: fprintf(ficresf," p%d%d",i,j);
8369: fprintf(ficresf," wp.%d",j);
8370: }
8371: for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {
8372: fprintf(ficresf,"\n");
8373: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
1.270 brouard 8374: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8375: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8376: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8377: nhstepm = nhstepm/hstepm;
8378: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8379: oldm=oldms;savm=savms;
1.268 brouard 8380: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8381: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8382: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8383: for (h=0; h<=nhstepm; h++){
8384: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8385: break;
8386: }
8387: }
8388: fprintf(ficresf,"\n");
8389: for(j=1;j<=cptcoveff;j++)
8390: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8391: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
8392:
8393: for(j=1; j<=nlstate+ndeath;j++) {
8394: ppij=0.;
8395: for(i=1; i<=nlstate;i++) {
1.278 brouard 8396: if (mobilav>=1)
8397: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8398: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8399: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8400: }
1.268 brouard 8401: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8402: } /* end i */
8403: fprintf(ficresf," %.3f", ppij);
8404: }/* end j */
1.227 brouard 8405: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8406: } /* end agec */
1.266 brouard 8407: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8408: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8409: } /* end yearp */
8410: } /* end k */
1.219 brouard 8411:
1.126 brouard 8412: fclose(ficresf);
1.215 brouard 8413: printf("End of Computing forecasting \n");
8414: fprintf(ficlog,"End of Computing forecasting\n");
8415:
1.126 brouard 8416: }
8417:
1.269 brouard 8418: /************** Back Forecasting ******************/
8419: 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){
1.267 brouard 8420: /* back1, year, month, day of starting backection
8421: agemin, agemax range of age
8422: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8423: anback2 year of end of backprojection (same day and month as back1).
8424: prevacurrent and prev are prevalences.
1.267 brouard 8425: */
8426: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8427: double agec; /* generic age */
1.268 brouard 8428: double agelim, ppij, ppi, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
1.267 brouard 8429: double *popeffectif,*popcount;
8430: double ***p3mat;
8431: /* double ***mobaverage; */
8432: char fileresfb[FILENAMELENGTH];
8433:
1.268 brouard 8434: agelim=AGEINF;
1.267 brouard 8435: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8436: in each health status at the date of interview (if between dateprev1 and dateprev2).
8437: We still use firstpass and lastpass as another selection.
8438: */
8439: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8440: /* firstpass, lastpass, stepm, weightopt, model); */
8441:
8442: /*Do we need to compute prevalence again?*/
8443:
8444: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8445:
8446: strcpy(fileresfb,"FB_");
8447: strcat(fileresfb,fileresu);
8448: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8449: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8450: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8451: }
8452: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8453: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8454:
8455: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8456:
8457:
8458: stepsize=(int) (stepm+YEARM-1)/YEARM;
8459: if (stepm<=12) stepsize=1;
8460: if(estepm < stepm){
8461: printf ("Problem %d lower than %d\n",estepm, stepm);
8462: }
1.270 brouard 8463: else{
8464: hstepm=estepm;
8465: }
8466: if(estepm >= stepm){ /* Yes every two year */
8467: stepsize=2;
8468: }
1.267 brouard 8469:
8470: hstepm=hstepm/stepm;
8471: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8472: fractional in yp1 */
8473: anprojmean=yp;
8474: yp2=modf((yp1*12),&yp);
8475: mprojmean=yp;
8476: yp1=modf((yp2*30.5),&yp);
8477: jprojmean=yp;
8478: if(jprojmean==0) jprojmean=1;
8479: if(mprojmean==0) jprojmean=1;
8480:
8481: i1=pow(2,cptcoveff);
8482: if (cptcovn < 1){i1=1;}
8483:
8484: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.268 brouard 8485: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8486:
8487: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8488:
8489: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8490: for(k=1; k<=i1;k++){
8491: if(i1 != 1 && TKresult[nres]!= k)
8492: continue;
8493: if(invalidvarcomb[k]){
8494: printf("\nCombination (%d) projection ignored because no cases \n",k);
8495: continue;
8496: }
1.268 brouard 8497: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8498: for(j=1;j<=cptcoveff;j++) {
8499: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8500: }
8501: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8502: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8503: }
8504: fprintf(ficresfb," yearbproj age");
8505: for(j=1; j<=nlstate+ndeath;j++){
8506: for(i=1; i<=nlstate;i++)
1.268 brouard 8507: fprintf(ficresfb," b%d%d",i,j);
8508: fprintf(ficresfb," b.%d",j);
1.267 brouard 8509: }
8510: for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) {
8511: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8512: fprintf(ficresfb,"\n");
8513: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp);
1.273 brouard 8514: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8515: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8516: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8517: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8518: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8519: nhstepm = nhstepm/hstepm;
8520: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8521: oldm=oldms;savm=savms;
1.268 brouard 8522: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8523: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8524: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8525: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8526: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8527: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8528: for (h=0; h<=nhstepm; h++){
1.268 brouard 8529: if (h*hstepm/YEARM*stepm ==-yearp) {
8530: break;
8531: }
8532: }
8533: fprintf(ficresfb,"\n");
8534: for(j=1;j<=cptcoveff;j++)
8535: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8536: fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec-h*hstepm/YEARM*stepm);
8537: for(i=1; i<=nlstate+ndeath;i++) {
8538: ppij=0.;ppi=0.;
8539: for(j=1; j<=nlstate;j++) {
8540: /* if (mobilav==1) */
1.269 brouard 8541: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8542: ppi=ppi+prevacurrent[(int)agec][j][k];
8543: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8544: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8545: /* else { */
8546: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8547: /* } */
1.268 brouard 8548: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8549: } /* end j */
8550: if(ppi <0.99){
8551: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8552: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8553: }
8554: fprintf(ficresfb," %.3f", ppij);
8555: }/* end j */
1.267 brouard 8556: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8557: } /* end agec */
8558: } /* end yearp */
8559: } /* end k */
1.217 brouard 8560:
1.267 brouard 8561: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8562:
1.267 brouard 8563: fclose(ficresfb);
8564: printf("End of Computing Back forecasting \n");
8565: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8566:
1.267 brouard 8567: }
1.217 brouard 8568:
1.269 brouard 8569: /* Variance of prevalence limit: varprlim */
8570: 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 8571: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 8572:
8573: char fileresvpl[FILENAMELENGTH];
8574: FILE *ficresvpl;
8575: double **oldm, **savm;
8576: double **varpl; /* Variances of prevalence limits by age */
8577: int i1, k, nres, j ;
8578:
8579: strcpy(fileresvpl,"VPL_");
8580: strcat(fileresvpl,fileresu);
8581: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 8582: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 8583: exit(0);
8584: }
1.288 brouard 8585: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8586: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 8587:
8588: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8589: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8590:
8591: i1=pow(2,cptcoveff);
8592: if (cptcovn < 1){i1=1;}
8593:
8594: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8595: for(k=1; k<=i1;k++){
8596: if(i1 != 1 && TKresult[nres]!= k)
8597: continue;
8598: fprintf(ficresvpl,"\n#****** ");
8599: printf("\n#****** ");
8600: fprintf(ficlog,"\n#****** ");
8601: for(j=1;j<=cptcoveff;j++) {
8602: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8603: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8604: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8605: }
8606: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8607: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8608: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8609: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8610: }
8611: fprintf(ficresvpl,"******\n");
8612: printf("******\n");
8613: fprintf(ficlog,"******\n");
8614:
8615: varpl=matrix(1,nlstate,(int) bage, (int) fage);
8616: oldm=oldms;savm=savms;
8617: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
8618: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
8619: /*}*/
8620: }
8621:
8622: fclose(ficresvpl);
1.288 brouard 8623: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
8624: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 8625:
8626: }
8627: /* Variance of back prevalence: varbprlim */
8628: 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){
8629: /*------- Variance of back (stable) prevalence------*/
8630:
8631: char fileresvbl[FILENAMELENGTH];
8632: FILE *ficresvbl;
8633:
8634: double **oldm, **savm;
8635: double **varbpl; /* Variances of back prevalence limits by age */
8636: int i1, k, nres, j ;
8637:
8638: strcpy(fileresvbl,"VBL_");
8639: strcat(fileresvbl,fileresu);
8640: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
8641: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
8642: exit(0);
8643: }
8644: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
8645: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
8646:
8647:
8648: i1=pow(2,cptcoveff);
8649: if (cptcovn < 1){i1=1;}
8650:
8651: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8652: for(k=1; k<=i1;k++){
8653: if(i1 != 1 && TKresult[nres]!= k)
8654: continue;
8655: fprintf(ficresvbl,"\n#****** ");
8656: printf("\n#****** ");
8657: fprintf(ficlog,"\n#****** ");
8658: for(j=1;j<=cptcoveff;j++) {
8659: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8660: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8661: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8662: }
8663: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8664: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8665: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8666: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8667: }
8668: fprintf(ficresvbl,"******\n");
8669: printf("******\n");
8670: fprintf(ficlog,"******\n");
8671:
8672: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
8673: oldm=oldms;savm=savms;
8674:
8675: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
8676: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
8677: /*}*/
8678: }
8679:
8680: fclose(ficresvbl);
8681: printf("done variance-covariance of back prevalence\n");fflush(stdout);
8682: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
8683:
8684: } /* End of varbprlim */
8685:
1.126 brouard 8686: /************** Forecasting *****not tested NB*************/
1.227 brouard 8687: /* 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 8688:
1.227 brouard 8689: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8690: /* int *popage; */
8691: /* double calagedatem, agelim, kk1, kk2; */
8692: /* double *popeffectif,*popcount; */
8693: /* double ***p3mat,***tabpop,***tabpopprev; */
8694: /* /\* double ***mobaverage; *\/ */
8695: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8696:
1.227 brouard 8697: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8698: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8699: /* agelim=AGESUP; */
8700: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8701:
1.227 brouard 8702: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8703:
8704:
1.227 brouard 8705: /* strcpy(filerespop,"POP_"); */
8706: /* strcat(filerespop,fileresu); */
8707: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8708: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8709: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8710: /* } */
8711: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8712: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8713:
1.227 brouard 8714: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8715:
1.227 brouard 8716: /* /\* if (mobilav!=0) { *\/ */
8717: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8718: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8719: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8720: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8721: /* /\* } *\/ */
8722: /* /\* } *\/ */
1.126 brouard 8723:
1.227 brouard 8724: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8725: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8726:
1.227 brouard 8727: /* agelim=AGESUP; */
1.126 brouard 8728:
1.227 brouard 8729: /* hstepm=1; */
8730: /* hstepm=hstepm/stepm; */
1.218 brouard 8731:
1.227 brouard 8732: /* if (popforecast==1) { */
8733: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8734: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8735: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8736: /* } */
8737: /* popage=ivector(0,AGESUP); */
8738: /* popeffectif=vector(0,AGESUP); */
8739: /* popcount=vector(0,AGESUP); */
1.126 brouard 8740:
1.227 brouard 8741: /* i=1; */
8742: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8743:
1.227 brouard 8744: /* imx=i; */
8745: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8746: /* } */
1.218 brouard 8747:
1.227 brouard 8748: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8749: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8750: /* k=k+1; */
8751: /* fprintf(ficrespop,"\n#******"); */
8752: /* for(j=1;j<=cptcoveff;j++) { */
8753: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8754: /* } */
8755: /* fprintf(ficrespop,"******\n"); */
8756: /* fprintf(ficrespop,"# Age"); */
8757: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8758: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8759:
1.227 brouard 8760: /* for (cpt=0; cpt<=0;cpt++) { */
8761: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8762:
1.227 brouard 8763: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8764: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8765: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8766:
1.227 brouard 8767: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8768: /* oldm=oldms;savm=savms; */
8769: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8770:
1.227 brouard 8771: /* for (h=0; h<=nhstepm; h++){ */
8772: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8773: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8774: /* } */
8775: /* for(j=1; j<=nlstate+ndeath;j++) { */
8776: /* kk1=0.;kk2=0; */
8777: /* for(i=1; i<=nlstate;i++) { */
8778: /* if (mobilav==1) */
8779: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8780: /* else { */
8781: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8782: /* } */
8783: /* } */
8784: /* if (h==(int)(calagedatem+12*cpt)){ */
8785: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8786: /* /\*fprintf(ficrespop," %.3f", kk1); */
8787: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8788: /* } */
8789: /* } */
8790: /* for(i=1; i<=nlstate;i++){ */
8791: /* kk1=0.; */
8792: /* for(j=1; j<=nlstate;j++){ */
8793: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8794: /* } */
8795: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8796: /* } */
1.218 brouard 8797:
1.227 brouard 8798: /* if (h==(int)(calagedatem+12*cpt)) */
8799: /* for(j=1; j<=nlstate;j++) */
8800: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8801: /* } */
8802: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8803: /* } */
8804: /* } */
1.218 brouard 8805:
1.227 brouard 8806: /* /\******\/ */
1.218 brouard 8807:
1.227 brouard 8808: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8809: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8810: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8811: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8812: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8813:
1.227 brouard 8814: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8815: /* oldm=oldms;savm=savms; */
8816: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8817: /* for (h=0; h<=nhstepm; h++){ */
8818: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8819: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8820: /* } */
8821: /* for(j=1; j<=nlstate+ndeath;j++) { */
8822: /* kk1=0.;kk2=0; */
8823: /* for(i=1; i<=nlstate;i++) { */
8824: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8825: /* } */
8826: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8827: /* } */
8828: /* } */
8829: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8830: /* } */
8831: /* } */
8832: /* } */
8833: /* } */
1.218 brouard 8834:
1.227 brouard 8835: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8836:
1.227 brouard 8837: /* if (popforecast==1) { */
8838: /* free_ivector(popage,0,AGESUP); */
8839: /* free_vector(popeffectif,0,AGESUP); */
8840: /* free_vector(popcount,0,AGESUP); */
8841: /* } */
8842: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8843: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8844: /* fclose(ficrespop); */
8845: /* } /\* End of popforecast *\/ */
1.218 brouard 8846:
1.126 brouard 8847: int fileappend(FILE *fichier, char *optionfich)
8848: {
8849: if((fichier=fopen(optionfich,"a"))==NULL) {
8850: printf("Problem with file: %s\n", optionfich);
8851: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8852: return (0);
8853: }
8854: fflush(fichier);
8855: return (1);
8856: }
8857:
8858:
8859: /**************** function prwizard **********************/
8860: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8861: {
8862:
8863: /* Wizard to print covariance matrix template */
8864:
1.164 brouard 8865: char ca[32], cb[32];
8866: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8867: int numlinepar;
8868:
8869: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8870: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8871: for(i=1; i <=nlstate; i++){
8872: jj=0;
8873: for(j=1; j <=nlstate+ndeath; j++){
8874: if(j==i) continue;
8875: jj++;
8876: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8877: printf("%1d%1d",i,j);
8878: fprintf(ficparo,"%1d%1d",i,j);
8879: for(k=1; k<=ncovmodel;k++){
8880: /* printf(" %lf",param[i][j][k]); */
8881: /* fprintf(ficparo," %lf",param[i][j][k]); */
8882: printf(" 0.");
8883: fprintf(ficparo," 0.");
8884: }
8885: printf("\n");
8886: fprintf(ficparo,"\n");
8887: }
8888: }
8889: printf("# Scales (for hessian or gradient estimation)\n");
8890: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8891: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8892: for(i=1; i <=nlstate; i++){
8893: jj=0;
8894: for(j=1; j <=nlstate+ndeath; j++){
8895: if(j==i) continue;
8896: jj++;
8897: fprintf(ficparo,"%1d%1d",i,j);
8898: printf("%1d%1d",i,j);
8899: fflush(stdout);
8900: for(k=1; k<=ncovmodel;k++){
8901: /* printf(" %le",delti3[i][j][k]); */
8902: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8903: printf(" 0.");
8904: fprintf(ficparo," 0.");
8905: }
8906: numlinepar++;
8907: printf("\n");
8908: fprintf(ficparo,"\n");
8909: }
8910: }
8911: printf("# Covariance matrix\n");
8912: /* # 121 Var(a12)\n\ */
8913: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8914: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
8915: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
8916: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
8917: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
8918: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
8919: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8920: fflush(stdout);
8921: fprintf(ficparo,"# Covariance matrix\n");
8922: /* # 121 Var(a12)\n\ */
8923: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8924: /* # ...\n\ */
8925: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8926:
8927: for(itimes=1;itimes<=2;itimes++){
8928: jj=0;
8929: for(i=1; i <=nlstate; i++){
8930: for(j=1; j <=nlstate+ndeath; j++){
8931: if(j==i) continue;
8932: for(k=1; k<=ncovmodel;k++){
8933: jj++;
8934: ca[0]= k+'a'-1;ca[1]='\0';
8935: if(itimes==1){
8936: printf("#%1d%1d%d",i,j,k);
8937: fprintf(ficparo,"#%1d%1d%d",i,j,k);
8938: }else{
8939: printf("%1d%1d%d",i,j,k);
8940: fprintf(ficparo,"%1d%1d%d",i,j,k);
8941: /* printf(" %.5le",matcov[i][j]); */
8942: }
8943: ll=0;
8944: for(li=1;li <=nlstate; li++){
8945: for(lj=1;lj <=nlstate+ndeath; lj++){
8946: if(lj==li) continue;
8947: for(lk=1;lk<=ncovmodel;lk++){
8948: ll++;
8949: if(ll<=jj){
8950: cb[0]= lk +'a'-1;cb[1]='\0';
8951: if(ll<jj){
8952: if(itimes==1){
8953: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8954: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8955: }else{
8956: printf(" 0.");
8957: fprintf(ficparo," 0.");
8958: }
8959: }else{
8960: if(itimes==1){
8961: printf(" Var(%s%1d%1d)",ca,i,j);
8962: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
8963: }else{
8964: printf(" 0.");
8965: fprintf(ficparo," 0.");
8966: }
8967: }
8968: }
8969: } /* end lk */
8970: } /* end lj */
8971: } /* end li */
8972: printf("\n");
8973: fprintf(ficparo,"\n");
8974: numlinepar++;
8975: } /* end k*/
8976: } /*end j */
8977: } /* end i */
8978: } /* end itimes */
8979:
8980: } /* end of prwizard */
8981: /******************* Gompertz Likelihood ******************************/
8982: double gompertz(double x[])
8983: {
8984: double A,B,L=0.0,sump=0.,num=0.;
8985: int i,n=0; /* n is the size of the sample */
8986:
1.220 brouard 8987: for (i=1;i<=imx ; i++) {
1.126 brouard 8988: sump=sump+weight[i];
8989: /* sump=sump+1;*/
8990: num=num+1;
8991: }
8992:
8993:
8994: /* for (i=0; i<=imx; i++)
8995: 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]);*/
8996:
8997: for (i=1;i<=imx ; i++)
8998: {
8999: if (cens[i] == 1 && wav[i]>1)
9000: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
9001:
9002: if (cens[i] == 0 && wav[i]>1)
9003: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
9004: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
9005:
9006: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9007: if (wav[i] > 1 ) { /* ??? */
9008: L=L+A*weight[i];
9009: /* 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]);*/
9010: }
9011: }
9012:
9013: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9014:
9015: return -2*L*num/sump;
9016: }
9017:
1.136 brouard 9018: #ifdef GSL
9019: /******************* Gompertz_f Likelihood ******************************/
9020: double gompertz_f(const gsl_vector *v, void *params)
9021: {
9022: double A,B,LL=0.0,sump=0.,num=0.;
9023: double *x= (double *) v->data;
9024: int i,n=0; /* n is the size of the sample */
9025:
9026: for (i=0;i<=imx-1 ; i++) {
9027: sump=sump+weight[i];
9028: /* sump=sump+1;*/
9029: num=num+1;
9030: }
9031:
9032:
9033: /* for (i=0; i<=imx; i++)
9034: 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]);*/
9035: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9036: for (i=1;i<=imx ; i++)
9037: {
9038: if (cens[i] == 1 && wav[i]>1)
9039: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9040:
9041: if (cens[i] == 0 && wav[i]>1)
9042: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9043: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9044:
9045: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9046: if (wav[i] > 1 ) { /* ??? */
9047: LL=LL+A*weight[i];
9048: /* 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]);*/
9049: }
9050: }
9051:
9052: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9053: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9054:
9055: return -2*LL*num/sump;
9056: }
9057: #endif
9058:
1.126 brouard 9059: /******************* Printing html file ***********/
1.201 brouard 9060: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9061: int lastpass, int stepm, int weightopt, char model[],\
9062: int imx, double p[],double **matcov,double agemortsup){
9063: int i,k;
9064:
9065: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9066: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9067: for (i=1;i<=2;i++)
9068: 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 9069: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9070: fprintf(fichtm,"</ul>");
9071:
9072: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9073:
9074: 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>");
9075:
9076: for (k=agegomp;k<(agemortsup-2);k++)
9077: 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]);
9078:
9079:
9080: fflush(fichtm);
9081: }
9082:
9083: /******************* Gnuplot file **************/
1.201 brouard 9084: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9085:
9086: char dirfileres[132],optfileres[132];
1.164 brouard 9087:
1.126 brouard 9088: int ng;
9089:
9090:
9091: /*#ifdef windows */
9092: fprintf(ficgp,"cd \"%s\" \n",pathc);
9093: /*#endif */
9094:
9095:
9096: strcpy(dirfileres,optionfilefiname);
9097: strcpy(optfileres,"vpl");
1.199 brouard 9098: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9099: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9100: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9101: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9102: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9103:
9104: }
9105:
1.136 brouard 9106: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9107: {
1.126 brouard 9108:
1.136 brouard 9109: /*-------- data file ----------*/
9110: FILE *fic;
9111: char dummy[]=" ";
1.240 brouard 9112: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9113: int lstra;
1.136 brouard 9114: int linei, month, year,iout;
9115: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9116: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9117: char *stratrunc;
1.223 brouard 9118:
1.240 brouard 9119: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9120: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9121:
1.240 brouard 9122: for(v=1; v <=ncovcol;v++){
9123: DummyV[v]=0;
9124: FixedV[v]=0;
9125: }
9126: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9127: DummyV[v]=1;
9128: FixedV[v]=0;
9129: }
9130: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9131: DummyV[v]=0;
9132: FixedV[v]=1;
9133: }
9134: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9135: DummyV[v]=1;
9136: FixedV[v]=1;
9137: }
9138: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9139: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9140: 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]);
9141: }
1.126 brouard 9142:
1.136 brouard 9143: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9144: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9145: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9146: }
1.126 brouard 9147:
1.136 brouard 9148: i=1;
9149: linei=0;
9150: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9151: linei=linei+1;
9152: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9153: if(line[j] == '\t')
9154: line[j] = ' ';
9155: }
9156: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9157: ;
9158: };
9159: line[j+1]=0; /* Trims blanks at end of line */
9160: if(line[0]=='#'){
9161: fprintf(ficlog,"Comment line\n%s\n",line);
9162: printf("Comment line\n%s\n",line);
9163: continue;
9164: }
9165: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9166: strcpy(line, linetmp);
1.223 brouard 9167:
9168: /* Loops on waves */
9169: for (j=maxwav;j>=1;j--){
9170: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9171: cutv(stra, strb, line, ' ');
9172: if(strb[0]=='.') { /* Missing value */
9173: lval=-1;
9174: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9175: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9176: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9177: 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);
9178: 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);
9179: return 1;
9180: }
9181: }else{
9182: errno=0;
9183: /* what_kind_of_number(strb); */
9184: dval=strtod(strb,&endptr);
9185: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9186: /* if(strb != endptr && *endptr == '\0') */
9187: /* dval=dlval; */
9188: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9189: if( strb[0]=='\0' || (*endptr != '\0')){
9190: 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);
9191: 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);
9192: return 1;
9193: }
9194: cotqvar[j][iv][i]=dval;
9195: cotvar[j][ntv+iv][i]=dval;
9196: }
9197: strcpy(line,stra);
1.223 brouard 9198: }/* end loop ntqv */
1.225 brouard 9199:
1.223 brouard 9200: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9201: cutv(stra, strb, line, ' ');
9202: if(strb[0]=='.') { /* Missing value */
9203: lval=-1;
9204: }else{
9205: errno=0;
9206: lval=strtol(strb,&endptr,10);
9207: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9208: if( strb[0]=='\0' || (*endptr != '\0')){
9209: 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);
9210: 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);
9211: return 1;
9212: }
9213: }
9214: if(lval <-1 || lval >1){
9215: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9216: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9217: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9218: For example, for multinomial values like 1, 2 and 3,\n \
9219: build V1=0 V2=0 for the reference value (1),\n \
9220: V1=1 V2=0 for (2) \n \
1.223 brouard 9221: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9222: output of IMaCh is often meaningless.\n \
1.223 brouard 9223: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9224: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9225: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9226: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9227: For example, for multinomial values like 1, 2 and 3,\n \
9228: build V1=0 V2=0 for the reference value (1),\n \
9229: V1=1 V2=0 for (2) \n \
1.223 brouard 9230: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9231: output of IMaCh is often meaningless.\n \
1.223 brouard 9232: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 9233: return 1;
9234: }
9235: cotvar[j][iv][i]=(double)(lval);
9236: strcpy(line,stra);
1.223 brouard 9237: }/* end loop ntv */
1.225 brouard 9238:
1.223 brouard 9239: /* Statuses at wave */
1.137 brouard 9240: cutv(stra, strb, line, ' ');
1.223 brouard 9241: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9242: lval=-1;
1.136 brouard 9243: }else{
1.238 brouard 9244: errno=0;
9245: lval=strtol(strb,&endptr,10);
9246: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9247: if( strb[0]=='\0' || (*endptr != '\0')){
9248: 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);
9249: 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);
9250: return 1;
9251: }
1.136 brouard 9252: }
1.225 brouard 9253:
1.136 brouard 9254: s[j][i]=lval;
1.225 brouard 9255:
1.223 brouard 9256: /* Date of Interview */
1.136 brouard 9257: strcpy(line,stra);
9258: cutv(stra, strb,line,' ');
1.169 brouard 9259: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9260: }
1.169 brouard 9261: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9262: month=99;
9263: year=9999;
1.136 brouard 9264: }else{
1.225 brouard 9265: 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);
9266: 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);
9267: return 1;
1.136 brouard 9268: }
9269: anint[j][i]= (double) year;
9270: mint[j][i]= (double)month;
9271: strcpy(line,stra);
1.223 brouard 9272: } /* End loop on waves */
1.225 brouard 9273:
1.223 brouard 9274: /* Date of death */
1.136 brouard 9275: cutv(stra, strb,line,' ');
1.169 brouard 9276: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9277: }
1.169 brouard 9278: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9279: month=99;
9280: year=9999;
9281: }else{
1.141 brouard 9282: 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 9283: 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);
9284: return 1;
1.136 brouard 9285: }
9286: andc[i]=(double) year;
9287: moisdc[i]=(double) month;
9288: strcpy(line,stra);
9289:
1.223 brouard 9290: /* Date of birth */
1.136 brouard 9291: cutv(stra, strb,line,' ');
1.169 brouard 9292: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9293: }
1.169 brouard 9294: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9295: month=99;
9296: year=9999;
9297: }else{
1.141 brouard 9298: 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);
9299: 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 9300: return 1;
1.136 brouard 9301: }
9302: if (year==9999) {
1.141 brouard 9303: 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);
9304: 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 9305: return 1;
9306:
1.136 brouard 9307: }
9308: annais[i]=(double)(year);
9309: moisnais[i]=(double)(month);
9310: strcpy(line,stra);
1.225 brouard 9311:
1.223 brouard 9312: /* Sample weight */
1.136 brouard 9313: cutv(stra, strb,line,' ');
9314: errno=0;
9315: dval=strtod(strb,&endptr);
9316: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9317: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9318: 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 9319: fflush(ficlog);
9320: return 1;
9321: }
9322: weight[i]=dval;
9323: strcpy(line,stra);
1.225 brouard 9324:
1.223 brouard 9325: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9326: cutv(stra, strb, line, ' ');
9327: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9328: lval=-1;
1.223 brouard 9329: }else{
1.225 brouard 9330: errno=0;
9331: /* what_kind_of_number(strb); */
9332: dval=strtod(strb,&endptr);
9333: /* if(strb != endptr && *endptr == '\0') */
9334: /* dval=dlval; */
9335: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9336: if( strb[0]=='\0' || (*endptr != '\0')){
9337: 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);
9338: 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);
9339: return 1;
9340: }
9341: coqvar[iv][i]=dval;
1.226 brouard 9342: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9343: }
9344: strcpy(line,stra);
9345: }/* end loop nqv */
1.136 brouard 9346:
1.223 brouard 9347: /* Covariate values */
1.136 brouard 9348: for (j=ncovcol;j>=1;j--){
9349: cutv(stra, strb,line,' ');
1.223 brouard 9350: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9351: lval=-1;
1.136 brouard 9352: }else{
1.225 brouard 9353: errno=0;
9354: lval=strtol(strb,&endptr,10);
9355: if( strb[0]=='\0' || (*endptr != '\0')){
9356: 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);
9357: 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);
9358: return 1;
9359: }
1.136 brouard 9360: }
9361: if(lval <-1 || lval >1){
1.225 brouard 9362: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9363: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9364: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9365: For example, for multinomial values like 1, 2 and 3,\n \
9366: build V1=0 V2=0 for the reference value (1),\n \
9367: V1=1 V2=0 for (2) \n \
1.136 brouard 9368: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9369: output of IMaCh is often meaningless.\n \
1.136 brouard 9370: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9371: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9372: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9373: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9374: For example, for multinomial values like 1, 2 and 3,\n \
9375: build V1=0 V2=0 for the reference value (1),\n \
9376: V1=1 V2=0 for (2) \n \
1.136 brouard 9377: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9378: output of IMaCh is often meaningless.\n \
1.136 brouard 9379: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9380: return 1;
1.136 brouard 9381: }
9382: covar[j][i]=(double)(lval);
9383: strcpy(line,stra);
9384: }
9385: lstra=strlen(stra);
1.225 brouard 9386:
1.136 brouard 9387: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9388: stratrunc = &(stra[lstra-9]);
9389: num[i]=atol(stratrunc);
9390: }
9391: else
9392: num[i]=atol(stra);
9393: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9394: 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;}*/
9395:
9396: i=i+1;
9397: } /* End loop reading data */
1.225 brouard 9398:
1.136 brouard 9399: *imax=i-1; /* Number of individuals */
9400: fclose(fic);
1.225 brouard 9401:
1.136 brouard 9402: return (0);
1.164 brouard 9403: /* endread: */
1.225 brouard 9404: printf("Exiting readdata: ");
9405: fclose(fic);
9406: return (1);
1.223 brouard 9407: }
1.126 brouard 9408:
1.234 brouard 9409: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9410: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9411: while (*p2 == ' ')
1.234 brouard 9412: p2++;
9413: /* while ((*p1++ = *p2++) !=0) */
9414: /* ; */
9415: /* do */
9416: /* while (*p2 == ' ') */
9417: /* p2++; */
9418: /* while (*p1++ == *p2++); */
9419: *stri=p2;
1.145 brouard 9420: }
9421:
1.235 brouard 9422: int decoderesult ( char resultline[], int nres)
1.230 brouard 9423: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9424: {
1.235 brouard 9425: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9426: char resultsav[MAXLINE];
1.234 brouard 9427: int resultmodel[MAXLINE];
9428: int modelresult[MAXLINE];
1.230 brouard 9429: char stra[80], strb[80], strc[80], strd[80],stre[80];
9430:
1.234 brouard 9431: removefirstspace(&resultline);
1.233 brouard 9432: printf("decoderesult:%s\n",resultline);
1.230 brouard 9433:
9434: if (strstr(resultline,"v") !=0){
9435: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9436: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9437: return 1;
9438: }
9439: trimbb(resultsav, resultline);
9440: if (strlen(resultsav) >1){
9441: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9442: }
1.253 brouard 9443: if(j == 0){ /* Resultline but no = */
9444: TKresult[nres]=0; /* Combination for the nresult and the model */
9445: return (0);
9446: }
9447:
1.234 brouard 9448: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
9449: printf("ERROR: the number of variable in the resultline, %d, differs from the number of variable used in the model line, %d.\n",j, cptcovs);
9450: fprintf(ficlog,"ERROR: the number of variable in the resultline, %d, differs from the number of variable used in the model line, %d.\n",j, cptcovs);
9451: }
9452: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9453: if(nbocc(resultsav,'=') >1){
9454: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
9455: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
9456: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9457: }else
9458: cutl(strc,strd,resultsav,'=');
1.230 brouard 9459: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9460:
1.230 brouard 9461: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9462: Tvarsel[k]=atoi(strc);
9463: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9464: /* cptcovsel++; */
9465: if (nbocc(stra,'=') >0)
9466: strcpy(resultsav,stra); /* and analyzes it */
9467: }
1.235 brouard 9468: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9469: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9470: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9471: match=0;
1.236 brouard 9472: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9473: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9474: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9475: match=1;
9476: break;
9477: }
9478: }
9479: if(match == 0){
9480: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9481: }
9482: }
9483: }
1.235 brouard 9484: /* Checking for missing or useless values in comparison of current model needs */
9485: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9486: match=0;
1.235 brouard 9487: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9488: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9489: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9490: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9491: ++match;
9492: }
9493: }
9494: }
9495: if(match == 0){
9496: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9497: }else if(match > 1){
9498: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9499: }
9500: }
1.235 brouard 9501:
1.234 brouard 9502: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9503: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9504: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9505: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9506: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9507: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9508: /* 1 0 0 0 */
9509: /* 2 1 0 0 */
9510: /* 3 0 1 0 */
9511: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9512: /* 5 0 0 1 */
9513: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9514: /* 7 0 1 1 */
9515: /* 8 1 1 1 */
1.237 brouard 9516: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9517: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9518: /* V5*age V5 known which value for nres? */
9519: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9520: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9521: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9522: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9523: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9524: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9525: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9526: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9527: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9528: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9529: k4++;;
9530: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9531: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9532: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9533: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9534: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9535: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9536: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9537: k4q++;;
9538: }
9539: }
1.234 brouard 9540:
1.235 brouard 9541: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9542: return (0);
9543: }
1.235 brouard 9544:
1.230 brouard 9545: int decodemodel( char model[], int lastobs)
9546: /**< This routine decodes the model and returns:
1.224 brouard 9547: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9548: * - nagesqr = 1 if age*age in the model, otherwise 0.
9549: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9550: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9551: * - cptcovage number of covariates with age*products =2
9552: * - cptcovs number of simple covariates
9553: * - 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
9554: * which is a new column after the 9 (ncovcol) variables.
9555: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9556: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9557: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9558: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9559: */
1.136 brouard 9560: {
1.238 brouard 9561: int i, j, k, ks, v;
1.227 brouard 9562: int j1, k1, k2, k3, k4;
1.136 brouard 9563: char modelsav[80];
1.145 brouard 9564: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9565: char *strpt;
1.136 brouard 9566:
1.145 brouard 9567: /*removespace(model);*/
1.136 brouard 9568: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9569: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9570: if (strstr(model,"AGE") !=0){
1.192 brouard 9571: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9572: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9573: return 1;
9574: }
1.141 brouard 9575: if (strstr(model,"v") !=0){
9576: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9577: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9578: return 1;
9579: }
1.187 brouard 9580: strcpy(modelsav,model);
9581: if ((strpt=strstr(model,"age*age")) !=0){
9582: printf(" strpt=%s, model=%s\n",strpt, model);
9583: if(strpt != model){
1.234 brouard 9584: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9585: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9586: corresponding column of parameters.\n",model);
1.234 brouard 9587: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9588: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9589: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9590: return 1;
1.225 brouard 9591: }
1.187 brouard 9592: nagesqr=1;
9593: if (strstr(model,"+age*age") !=0)
1.234 brouard 9594: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9595: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9596: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9597: else
1.234 brouard 9598: substrchaine(modelsav, model, "age*age");
1.187 brouard 9599: }else
9600: nagesqr=0;
9601: if (strlen(modelsav) >1){
9602: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9603: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9604: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9605: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9606: * cst, age and age*age
9607: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9608: /* including age products which are counted in cptcovage.
9609: * but the covariates which are products must be treated
9610: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9611: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9612: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9613:
9614:
1.187 brouard 9615: /* Design
9616: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9617: * < ncovcol=8 >
9618: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9619: * k= 1 2 3 4 5 6 7 8
9620: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9621: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9622: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9623: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9624: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9625: * Tage[++cptcovage]=k
9626: * if products, new covar are created after ncovcol with k1
9627: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9628: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9629: * 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
9630: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9631: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9632: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9633: * < ncovcol=8 >
9634: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9635: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9636: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9637: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9638: * p Tprod[1]@2={ 6, 5}
9639: *p Tvard[1][1]@4= {7, 8, 5, 6}
9640: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9641: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9642: *How to reorganize?
9643: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9644: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9645: * {2, 1, 4, 8, 5, 6, 3, 7}
9646: * Struct []
9647: */
1.225 brouard 9648:
1.187 brouard 9649: /* This loop fills the array Tvar from the string 'model'.*/
9650: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9651: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9652: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9653: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9654: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9655: /* k=1 Tvar[1]=2 (from V2) */
9656: /* k=5 Tvar[5] */
9657: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9658: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9659: /* } */
1.198 brouard 9660: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9661: /*
9662: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9663: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9664: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9665: }
1.187 brouard 9666: cptcovage=0;
9667: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9668: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9669: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9670: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9671: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9672: /*scanf("%d",i);*/
9673: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9674: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9675: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9676: /* covar is not filled and then is empty */
9677: cptcovprod--;
9678: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9679: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9680: Typevar[k]=1; /* 1 for age product */
9681: cptcovage++; /* Sums the number of covariates which include age as a product */
9682: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9683: /*printf("stre=%s ", stre);*/
9684: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9685: cptcovprod--;
9686: cutl(stre,strb,strc,'V');
9687: Tvar[k]=atoi(stre);
9688: Typevar[k]=1; /* 1 for age product */
9689: cptcovage++;
9690: Tage[cptcovage]=k;
9691: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9692: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9693: cptcovn++;
9694: cptcovprodnoage++;k1++;
9695: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9696: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9697: because this model-covariate is a construction we invent a new column
9698: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9699: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9700: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9701: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9702: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9703: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9704: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9705: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9706: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9707: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9708: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9709: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9710: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9711: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9712: for (i=1; i<=lastobs;i++){
9713: /* Computes the new covariate which is a product of
9714: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9715: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9716: }
9717: } /* End age is not in the model */
9718: } /* End if model includes a product */
9719: else { /* no more sum */
9720: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9721: /* scanf("%d",i);*/
9722: cutl(strd,strc,strb,'V');
9723: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9724: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9725: Tvar[k]=atoi(strd);
9726: Typevar[k]=0; /* 0 for simple covariates */
9727: }
9728: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9729: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9730: scanf("%d",i);*/
1.187 brouard 9731: } /* end of loop + on total covariates */
9732: } /* end if strlen(modelsave == 0) age*age might exist */
9733: } /* end if strlen(model == 0) */
1.136 brouard 9734:
9735: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9736: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9737:
1.136 brouard 9738: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9739: printf("cptcovprod=%d ", cptcovprod);
9740: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9741: scanf("%d ",i);*/
9742:
9743:
1.230 brouard 9744: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9745: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9746: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9747: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9748: k = 1 2 3 4 5 6 7 8 9
9749: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9750: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9751: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9752: Dummy[k] 1 0 0 0 3 1 1 2 3
9753: Tmodelind[combination of covar]=k;
1.225 brouard 9754: */
9755: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9756: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9757: /* 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 9758: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9759: printf("Model=%s\n\
9760: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9761: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9762: 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);
9763: fprintf(ficlog,"Model=%s\n\
9764: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9765: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9766: 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 9767: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9768: 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 */
9769: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9770: Fixed[k]= 0;
9771: Dummy[k]= 0;
1.225 brouard 9772: ncoveff++;
1.232 brouard 9773: ncovf++;
1.234 brouard 9774: nsd++;
9775: modell[k].maintype= FTYPE;
9776: TvarsD[nsd]=Tvar[k];
9777: TvarsDind[nsd]=k;
9778: TvarF[ncovf]=Tvar[k];
9779: TvarFind[ncovf]=k;
9780: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9781: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9782: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
9783: Fixed[k]= 0;
9784: Dummy[k]= 0;
9785: ncoveff++;
9786: ncovf++;
9787: modell[k].maintype= FTYPE;
9788: TvarF[ncovf]=Tvar[k];
9789: TvarFind[ncovf]=k;
1.230 brouard 9790: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 9791: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 9792: }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 9793: Fixed[k]= 0;
9794: Dummy[k]= 1;
1.230 brouard 9795: nqfveff++;
1.234 brouard 9796: modell[k].maintype= FTYPE;
9797: modell[k].subtype= FQ;
9798: nsq++;
9799: TvarsQ[nsq]=Tvar[k];
9800: TvarsQind[nsq]=k;
1.232 brouard 9801: ncovf++;
1.234 brouard 9802: TvarF[ncovf]=Tvar[k];
9803: TvarFind[ncovf]=k;
1.231 brouard 9804: 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 9805: 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 9806: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 9807: Fixed[k]= 1;
9808: Dummy[k]= 0;
1.225 brouard 9809: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 9810: modell[k].maintype= VTYPE;
9811: modell[k].subtype= VD;
9812: nsd++;
9813: TvarsD[nsd]=Tvar[k];
9814: TvarsDind[nsd]=k;
9815: ncovv++; /* Only simple time varying variables */
9816: TvarV[ncovv]=Tvar[k];
1.242 brouard 9817: 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 9818: 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 */
9819: 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 9820: 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);
9821: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 9822: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 9823: Fixed[k]= 1;
9824: Dummy[k]= 1;
9825: nqtveff++;
9826: modell[k].maintype= VTYPE;
9827: modell[k].subtype= VQ;
9828: ncovv++; /* Only simple time varying variables */
9829: nsq++;
9830: TvarsQ[nsq]=Tvar[k];
9831: TvarsQind[nsq]=k;
9832: TvarV[ncovv]=Tvar[k];
1.242 brouard 9833: 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 9834: 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 */
9835: 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 9836: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9837: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9838: 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 9839: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9840: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9841: ncova++;
9842: TvarA[ncova]=Tvar[k];
9843: TvarAind[ncova]=k;
1.231 brouard 9844: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9845: Fixed[k]= 2;
9846: Dummy[k]= 2;
9847: modell[k].maintype= ATYPE;
9848: modell[k].subtype= APFD;
9849: /* ncoveff++; */
1.227 brouard 9850: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 9851: Fixed[k]= 2;
9852: Dummy[k]= 3;
9853: modell[k].maintype= ATYPE;
9854: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
9855: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 9856: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 9857: Fixed[k]= 3;
9858: Dummy[k]= 2;
9859: modell[k].maintype= ATYPE;
9860: modell[k].subtype= APVD; /* Product age * varying dummy */
9861: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 9862: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9863: Fixed[k]= 3;
9864: Dummy[k]= 3;
9865: modell[k].maintype= ATYPE;
9866: modell[k].subtype= APVQ; /* Product age * varying quantitative */
9867: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 9868: }
9869: }else if (Typevar[k] == 2) { /* product without age */
9870: k1=Tposprod[k];
9871: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 9872: if(Tvard[k1][2] <=ncovcol){
9873: Fixed[k]= 1;
9874: Dummy[k]= 0;
9875: modell[k].maintype= FTYPE;
9876: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
9877: ncovf++; /* Fixed variables without age */
9878: TvarF[ncovf]=Tvar[k];
9879: TvarFind[ncovf]=k;
9880: }else if(Tvard[k1][2] <=ncovcol+nqv){
9881: Fixed[k]= 0; /* or 2 ?*/
9882: Dummy[k]= 1;
9883: modell[k].maintype= FTYPE;
9884: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
9885: ncovf++; /* Varying variables without age */
9886: TvarF[ncovf]=Tvar[k];
9887: TvarFind[ncovf]=k;
9888: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9889: Fixed[k]= 1;
9890: Dummy[k]= 0;
9891: modell[k].maintype= VTYPE;
9892: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
9893: ncovv++; /* Varying variables without age */
9894: TvarV[ncovv]=Tvar[k];
9895: TvarVind[ncovv]=k;
9896: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9897: Fixed[k]= 1;
9898: Dummy[k]= 1;
9899: modell[k].maintype= VTYPE;
9900: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
9901: ncovv++; /* Varying variables without age */
9902: TvarV[ncovv]=Tvar[k];
9903: TvarVind[ncovv]=k;
9904: }
1.227 brouard 9905: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 9906: if(Tvard[k1][2] <=ncovcol){
9907: Fixed[k]= 0; /* or 2 ?*/
9908: Dummy[k]= 1;
9909: modell[k].maintype= FTYPE;
9910: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
9911: ncovf++; /* Fixed variables without age */
9912: TvarF[ncovf]=Tvar[k];
9913: TvarFind[ncovf]=k;
9914: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9915: Fixed[k]= 1;
9916: Dummy[k]= 1;
9917: modell[k].maintype= VTYPE;
9918: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
9919: ncovv++; /* Varying variables without age */
9920: TvarV[ncovv]=Tvar[k];
9921: TvarVind[ncovv]=k;
9922: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9923: Fixed[k]= 1;
9924: Dummy[k]= 1;
9925: modell[k].maintype= VTYPE;
9926: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
9927: ncovv++; /* Varying variables without age */
9928: TvarV[ncovv]=Tvar[k];
9929: TvarVind[ncovv]=k;
9930: ncovv++; /* Varying variables without age */
9931: TvarV[ncovv]=Tvar[k];
9932: TvarVind[ncovv]=k;
9933: }
1.227 brouard 9934: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 9935: if(Tvard[k1][2] <=ncovcol){
9936: Fixed[k]= 1;
9937: Dummy[k]= 1;
9938: modell[k].maintype= VTYPE;
9939: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
9940: ncovv++; /* Varying variables without age */
9941: TvarV[ncovv]=Tvar[k];
9942: TvarVind[ncovv]=k;
9943: }else if(Tvard[k1][2] <=ncovcol+nqv){
9944: Fixed[k]= 1;
9945: Dummy[k]= 1;
9946: modell[k].maintype= VTYPE;
9947: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
9948: ncovv++; /* Varying variables without age */
9949: TvarV[ncovv]=Tvar[k];
9950: TvarVind[ncovv]=k;
9951: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9952: Fixed[k]= 1;
9953: Dummy[k]= 0;
9954: modell[k].maintype= VTYPE;
9955: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
9956: ncovv++; /* Varying variables without age */
9957: TvarV[ncovv]=Tvar[k];
9958: TvarVind[ncovv]=k;
9959: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9960: Fixed[k]= 1;
9961: Dummy[k]= 1;
9962: modell[k].maintype= VTYPE;
9963: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
9964: ncovv++; /* Varying variables without age */
9965: TvarV[ncovv]=Tvar[k];
9966: TvarVind[ncovv]=k;
9967: }
1.227 brouard 9968: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9969: if(Tvard[k1][2] <=ncovcol){
9970: Fixed[k]= 1;
9971: Dummy[k]= 1;
9972: modell[k].maintype= VTYPE;
9973: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
9974: ncovv++; /* Varying variables without age */
9975: TvarV[ncovv]=Tvar[k];
9976: TvarVind[ncovv]=k;
9977: }else if(Tvard[k1][2] <=ncovcol+nqv){
9978: Fixed[k]= 1;
9979: Dummy[k]= 1;
9980: modell[k].maintype= VTYPE;
9981: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
9982: ncovv++; /* Varying variables without age */
9983: TvarV[ncovv]=Tvar[k];
9984: TvarVind[ncovv]=k;
9985: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9986: Fixed[k]= 1;
9987: Dummy[k]= 1;
9988: modell[k].maintype= VTYPE;
9989: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
9990: ncovv++; /* Varying variables without age */
9991: TvarV[ncovv]=Tvar[k];
9992: TvarVind[ncovv]=k;
9993: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9994: Fixed[k]= 1;
9995: Dummy[k]= 1;
9996: modell[k].maintype= VTYPE;
9997: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
9998: ncovv++; /* Varying variables without age */
9999: TvarV[ncovv]=Tvar[k];
10000: TvarVind[ncovv]=k;
10001: }
1.227 brouard 10002: }else{
1.240 brouard 10003: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10004: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10005: } /*end k1*/
1.225 brouard 10006: }else{
1.226 brouard 10007: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10008: 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 10009: }
1.227 brouard 10010: 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 10011: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10012: 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]);
10013: }
10014: /* Searching for doublons in the model */
10015: for(k1=1; k1<= cptcovt;k1++){
10016: for(k2=1; k2 <k1;k2++){
1.285 brouard 10017: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10018: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10019: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10020: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10021: 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]);
10022: 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 10023: return(1);
10024: }
10025: }else if (Typevar[k1] ==2){
10026: k3=Tposprod[k1];
10027: k4=Tposprod[k2];
10028: 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])) ){
10029: 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]]);
10030: 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);
10031: return(1);
10032: }
10033: }
1.227 brouard 10034: }
10035: }
1.225 brouard 10036: }
10037: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10038: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10039: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10040: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10041: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10042: /*endread:*/
1.225 brouard 10043: printf("Exiting decodemodel: ");
10044: return (1);
1.136 brouard 10045: }
10046:
1.169 brouard 10047: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10048: {/* Check ages at death */
1.136 brouard 10049: int i, m;
1.218 brouard 10050: int firstone=0;
10051:
1.136 brouard 10052: for (i=1; i<=imx; i++) {
10053: for(m=2; (m<= maxwav); m++) {
10054: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10055: anint[m][i]=9999;
1.216 brouard 10056: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10057: s[m][i]=-1;
1.136 brouard 10058: }
10059: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10060: *nberr = *nberr + 1;
1.218 brouard 10061: if(firstone == 0){
10062: firstone=1;
1.260 brouard 10063: 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 10064: }
1.262 brouard 10065: 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 10066: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10067: }
10068: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10069: (*nberr)++;
1.259 brouard 10070: 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 10071: 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 10072: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10073: }
10074: }
10075: }
10076:
10077: for (i=1; i<=imx; i++) {
10078: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10079: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10080: 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 10081: if (s[m][i] >= nlstate+1) {
1.169 brouard 10082: if(agedc[i]>0){
10083: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10084: agev[m][i]=agedc[i];
1.214 brouard 10085: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10086: }else {
1.136 brouard 10087: if ((int)andc[i]!=9999){
10088: nbwarn++;
10089: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10090: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10091: agev[m][i]=-1;
10092: }
10093: }
1.169 brouard 10094: } /* agedc > 0 */
1.214 brouard 10095: } /* end if */
1.136 brouard 10096: else if(s[m][i] !=9){ /* Standard case, age in fractional
10097: years but with the precision of a month */
10098: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10099: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10100: agev[m][i]=1;
10101: else if(agev[m][i] < *agemin){
10102: *agemin=agev[m][i];
10103: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10104: }
10105: else if(agev[m][i] >*agemax){
10106: *agemax=agev[m][i];
1.156 brouard 10107: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10108: }
10109: /*agev[m][i]=anint[m][i]-annais[i];*/
10110: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10111: } /* en if 9*/
1.136 brouard 10112: else { /* =9 */
1.214 brouard 10113: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10114: agev[m][i]=1;
10115: s[m][i]=-1;
10116: }
10117: }
1.214 brouard 10118: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10119: agev[m][i]=1;
1.214 brouard 10120: else{
10121: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10122: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10123: agev[m][i]=0;
10124: }
10125: } /* End for lastpass */
10126: }
1.136 brouard 10127:
10128: for (i=1; i<=imx; i++) {
10129: for(m=firstpass; (m<=lastpass); m++){
10130: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10131: (*nberr)++;
1.136 brouard 10132: 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);
10133: 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);
10134: return 1;
10135: }
10136: }
10137: }
10138:
10139: /*for (i=1; i<=imx; i++){
10140: for (m=firstpass; (m<lastpass); m++){
10141: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10142: }
10143:
10144: }*/
10145:
10146:
1.139 brouard 10147: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10148: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10149:
10150: return (0);
1.164 brouard 10151: /* endread:*/
1.136 brouard 10152: printf("Exiting calandcheckages: ");
10153: return (1);
10154: }
10155:
1.172 brouard 10156: #if defined(_MSC_VER)
10157: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10158: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10159: //#include "stdafx.h"
10160: //#include <stdio.h>
10161: //#include <tchar.h>
10162: //#include <windows.h>
10163: //#include <iostream>
10164: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10165:
10166: LPFN_ISWOW64PROCESS fnIsWow64Process;
10167:
10168: BOOL IsWow64()
10169: {
10170: BOOL bIsWow64 = FALSE;
10171:
10172: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10173: // (HANDLE, PBOOL);
10174:
10175: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10176:
10177: HMODULE module = GetModuleHandle(_T("kernel32"));
10178: const char funcName[] = "IsWow64Process";
10179: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10180: GetProcAddress(module, funcName);
10181:
10182: if (NULL != fnIsWow64Process)
10183: {
10184: if (!fnIsWow64Process(GetCurrentProcess(),
10185: &bIsWow64))
10186: //throw std::exception("Unknown error");
10187: printf("Unknown error\n");
10188: }
10189: return bIsWow64 != FALSE;
10190: }
10191: #endif
1.177 brouard 10192:
1.191 brouard 10193: void syscompilerinfo(int logged)
1.167 brouard 10194: {
10195: /* #include "syscompilerinfo.h"*/
1.185 brouard 10196: /* command line Intel compiler 32bit windows, XP compatible:*/
10197: /* /GS /W3 /Gy
10198: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10199: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10200: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10201: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10202: */
10203: /* 64 bits */
1.185 brouard 10204: /*
10205: /GS /W3 /Gy
10206: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10207: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10208: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10209: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10210: /* Optimization are useless and O3 is slower than O2 */
10211: /*
10212: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10213: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10214: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10215: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10216: */
1.186 brouard 10217: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10218: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10219: /PDB:"visual studio
10220: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10221: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10222: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10223: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10224: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10225: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10226: uiAccess='false'"
10227: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10228: /NOLOGO /TLBID:1
10229: */
1.177 brouard 10230: #if defined __INTEL_COMPILER
1.178 brouard 10231: #if defined(__GNUC__)
10232: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10233: #endif
1.177 brouard 10234: #elif defined(__GNUC__)
1.179 brouard 10235: #ifndef __APPLE__
1.174 brouard 10236: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10237: #endif
1.177 brouard 10238: struct utsname sysInfo;
1.178 brouard 10239: int cross = CROSS;
10240: if (cross){
10241: printf("Cross-");
1.191 brouard 10242: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10243: }
1.174 brouard 10244: #endif
10245:
1.171 brouard 10246: #include <stdint.h>
1.178 brouard 10247:
1.191 brouard 10248: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10249: #if defined(__clang__)
1.191 brouard 10250: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10251: #endif
10252: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10253: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10254: #endif
10255: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10256: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10257: #endif
10258: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10259: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10260: #endif
10261: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10262: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10263: #endif
10264: #if defined(_MSC_VER)
1.191 brouard 10265: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10266: #endif
10267: #if defined(__PGI)
1.191 brouard 10268: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10269: #endif
10270: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10271: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10272: #endif
1.191 brouard 10273: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10274:
1.167 brouard 10275: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10276: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10277: // Windows (x64 and x86)
1.191 brouard 10278: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10279: #elif __unix__ // all unices, not all compilers
10280: // Unix
1.191 brouard 10281: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10282: #elif __linux__
10283: // linux
1.191 brouard 10284: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10285: #elif __APPLE__
1.174 brouard 10286: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10287: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10288: #endif
10289:
10290: /* __MINGW32__ */
10291: /* __CYGWIN__ */
10292: /* __MINGW64__ */
10293: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10294: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10295: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10296: /* _WIN64 // Defined for applications for Win64. */
10297: /* _M_X64 // Defined for compilations that target x64 processors. */
10298: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10299:
1.167 brouard 10300: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10301: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10302: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10303: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10304: #else
1.191 brouard 10305: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10306: #endif
10307:
1.169 brouard 10308: #if defined(__GNUC__)
10309: # if defined(__GNUC_PATCHLEVEL__)
10310: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10311: + __GNUC_MINOR__ * 100 \
10312: + __GNUC_PATCHLEVEL__)
10313: # else
10314: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10315: + __GNUC_MINOR__ * 100)
10316: # endif
1.174 brouard 10317: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10318: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10319:
10320: if (uname(&sysInfo) != -1) {
10321: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10322: 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 10323: }
10324: else
10325: perror("uname() error");
1.179 brouard 10326: //#ifndef __INTEL_COMPILER
10327: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10328: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10329: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10330: #endif
1.169 brouard 10331: #endif
1.172 brouard 10332:
1.286 brouard 10333: // void main ()
1.172 brouard 10334: // {
1.169 brouard 10335: #if defined(_MSC_VER)
1.174 brouard 10336: if (IsWow64()){
1.191 brouard 10337: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10338: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10339: }
10340: else{
1.191 brouard 10341: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10342: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10343: }
1.172 brouard 10344: // printf("\nPress Enter to continue...");
10345: // getchar();
10346: // }
10347:
1.169 brouard 10348: #endif
10349:
1.167 brouard 10350:
1.219 brouard 10351: }
1.136 brouard 10352:
1.219 brouard 10353: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 10354: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.235 brouard 10355: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10356: /* double ftolpl = 1.e-10; */
1.180 brouard 10357: double age, agebase, agelim;
1.203 brouard 10358: double tot;
1.180 brouard 10359:
1.202 brouard 10360: strcpy(filerespl,"PL_");
10361: strcat(filerespl,fileresu);
10362: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 10363: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10364: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 10365: }
1.288 brouard 10366: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
10367: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10368: pstamp(ficrespl);
1.288 brouard 10369: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10370: fprintf(ficrespl,"#Age ");
10371: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10372: fprintf(ficrespl,"\n");
1.180 brouard 10373:
1.219 brouard 10374: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10375:
1.219 brouard 10376: agebase=ageminpar;
10377: agelim=agemaxpar;
1.180 brouard 10378:
1.227 brouard 10379: /* i1=pow(2,ncoveff); */
1.234 brouard 10380: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10381: if (cptcovn < 1){i1=1;}
1.180 brouard 10382:
1.238 brouard 10383: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10384: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10385: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10386: continue;
1.235 brouard 10387:
1.238 brouard 10388: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10389: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10390: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10391: /* k=k+1; */
10392: /* to clean */
10393: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10394: fprintf(ficrespl,"#******");
10395: printf("#******");
10396: fprintf(ficlog,"#******");
10397: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10398: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10399: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10400: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10401: }
10402: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10403: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10404: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10405: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10406: }
10407: fprintf(ficrespl,"******\n");
10408: printf("******\n");
10409: fprintf(ficlog,"******\n");
10410: if(invalidvarcomb[k]){
10411: printf("\nCombination (%d) ignored because no case \n",k);
10412: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10413: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10414: continue;
10415: }
1.219 brouard 10416:
1.238 brouard 10417: fprintf(ficrespl,"#Age ");
10418: for(j=1;j<=cptcoveff;j++) {
10419: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10420: }
10421: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10422: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10423:
1.238 brouard 10424: for (age=agebase; age<=agelim; age++){
10425: /* for (age=agebase; age<=agebase; age++){ */
10426: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10427: fprintf(ficrespl,"%.0f ",age );
10428: for(j=1;j<=cptcoveff;j++)
10429: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10430: tot=0.;
10431: for(i=1; i<=nlstate;i++){
10432: tot += prlim[i][i];
10433: fprintf(ficrespl," %.5f", prlim[i][i]);
10434: }
10435: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10436: } /* Age */
10437: /* was end of cptcod */
10438: } /* cptcov */
10439: } /* nres */
1.219 brouard 10440: return 0;
1.180 brouard 10441: }
10442:
1.218 brouard 10443: 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 10444: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 10445:
10446: /* Computes the back prevalence limit for any combination of covariate values
10447: * at any age between ageminpar and agemaxpar
10448: */
1.235 brouard 10449: int i, j, k, i1, nres=0 ;
1.217 brouard 10450: /* double ftolpl = 1.e-10; */
10451: double age, agebase, agelim;
10452: double tot;
1.218 brouard 10453: /* double ***mobaverage; */
10454: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10455:
10456: strcpy(fileresplb,"PLB_");
10457: strcat(fileresplb,fileresu);
10458: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 10459: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
10460: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 10461: }
1.288 brouard 10462: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
10463: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 10464: pstamp(ficresplb);
1.288 brouard 10465: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 10466: fprintf(ficresplb,"#Age ");
10467: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10468: fprintf(ficresplb,"\n");
10469:
1.218 brouard 10470:
10471: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10472:
10473: agebase=ageminpar;
10474: agelim=agemaxpar;
10475:
10476:
1.227 brouard 10477: i1=pow(2,cptcoveff);
1.218 brouard 10478: if (cptcovn < 1){i1=1;}
1.227 brouard 10479:
1.238 brouard 10480: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10481: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10482: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10483: continue;
10484: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10485: fprintf(ficresplb,"#******");
10486: printf("#******");
10487: fprintf(ficlog,"#******");
10488: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10489: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10490: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10491: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10492: }
10493: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10494: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10495: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10496: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10497: }
10498: fprintf(ficresplb,"******\n");
10499: printf("******\n");
10500: fprintf(ficlog,"******\n");
10501: if(invalidvarcomb[k]){
10502: printf("\nCombination (%d) ignored because no cases \n",k);
10503: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10504: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10505: continue;
10506: }
1.218 brouard 10507:
1.238 brouard 10508: fprintf(ficresplb,"#Age ");
10509: for(j=1;j<=cptcoveff;j++) {
10510: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10511: }
10512: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10513: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10514:
10515:
1.238 brouard 10516: for (age=agebase; age<=agelim; age++){
10517: /* for (age=agebase; age<=agebase; age++){ */
10518: if(mobilavproj > 0){
10519: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10520: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10521: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10522: }else if (mobilavproj == 0){
10523: 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);
10524: 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);
10525: exit(1);
10526: }else{
10527: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10528: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10529: /* printf("TOTOT\n"); */
10530: /* exit(1); */
1.238 brouard 10531: }
10532: fprintf(ficresplb,"%.0f ",age );
10533: for(j=1;j<=cptcoveff;j++)
10534: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10535: tot=0.;
10536: for(i=1; i<=nlstate;i++){
10537: tot += bprlim[i][i];
10538: fprintf(ficresplb," %.5f", bprlim[i][i]);
10539: }
10540: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10541: } /* Age */
10542: /* was end of cptcod */
1.255 brouard 10543: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10544: } /* end of any combination */
10545: } /* end of nres */
1.218 brouard 10546: /* hBijx(p, bage, fage); */
10547: /* fclose(ficrespijb); */
10548:
10549: return 0;
1.217 brouard 10550: }
1.218 brouard 10551:
1.180 brouard 10552: int hPijx(double *p, int bage, int fage){
10553: /*------------- h Pij x at various ages ------------*/
10554:
10555: int stepsize;
10556: int agelim;
10557: int hstepm;
10558: int nhstepm;
1.235 brouard 10559: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10560:
10561: double agedeb;
10562: double ***p3mat;
10563:
1.201 brouard 10564: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10565: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10566: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10567: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10568: }
10569: printf("Computing pij: result on file '%s' \n", filerespij);
10570: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10571:
10572: stepsize=(int) (stepm+YEARM-1)/YEARM;
10573: /*if (stepm<=24) stepsize=2;*/
10574:
10575: agelim=AGESUP;
10576: hstepm=stepsize*YEARM; /* Every year of age */
10577: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10578:
1.180 brouard 10579: /* hstepm=1; aff par mois*/
10580: pstamp(ficrespij);
10581: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10582: i1= pow(2,cptcoveff);
1.218 brouard 10583: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10584: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10585: /* k=k+1; */
1.235 brouard 10586: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10587: for(k=1; k<=i1;k++){
1.253 brouard 10588: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10589: continue;
1.183 brouard 10590: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10591: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10592: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10593: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10594: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10595: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10596: }
1.183 brouard 10597: fprintf(ficrespij,"******\n");
10598:
10599: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10600: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10601: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10602:
10603: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10604:
1.183 brouard 10605: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10606: oldm=oldms;savm=savms;
1.235 brouard 10607: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10608: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10609: for(i=1; i<=nlstate;i++)
10610: for(j=1; j<=nlstate+ndeath;j++)
10611: fprintf(ficrespij," %1d-%1d",i,j);
10612: fprintf(ficrespij,"\n");
10613: for (h=0; h<=nhstepm; h++){
10614: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10615: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10616: for(i=1; i<=nlstate;i++)
10617: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10618: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10619: fprintf(ficrespij,"\n");
10620: }
1.183 brouard 10621: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10622: fprintf(ficrespij,"\n");
10623: }
1.180 brouard 10624: /*}*/
10625: }
1.218 brouard 10626: return 0;
1.180 brouard 10627: }
1.218 brouard 10628:
10629: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10630: /*------------- h Bij x at various ages ------------*/
10631:
10632: int stepsize;
1.218 brouard 10633: /* int agelim; */
10634: int ageminl;
1.217 brouard 10635: int hstepm;
10636: int nhstepm;
1.238 brouard 10637: int h, i, i1, j, k, nres;
1.218 brouard 10638:
1.217 brouard 10639: double agedeb;
10640: double ***p3mat;
1.218 brouard 10641:
10642: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10643: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10644: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10645: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10646: }
10647: printf("Computing pij back: result on file '%s' \n", filerespijb);
10648: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10649:
10650: stepsize=(int) (stepm+YEARM-1)/YEARM;
10651: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10652:
1.218 brouard 10653: /* agelim=AGESUP; */
1.289 brouard 10654: ageminl=AGEINF; /* was 30 */
1.218 brouard 10655: hstepm=stepsize*YEARM; /* Every year of age */
10656: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10657:
10658: /* hstepm=1; aff par mois*/
10659: pstamp(ficrespijb);
1.255 brouard 10660: 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 10661: i1= pow(2,cptcoveff);
1.218 brouard 10662: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10663: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10664: /* k=k+1; */
1.238 brouard 10665: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10666: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10667: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10668: continue;
10669: fprintf(ficrespijb,"\n#****** ");
10670: for(j=1;j<=cptcoveff;j++)
10671: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10672: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10673: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10674: }
10675: fprintf(ficrespijb,"******\n");
1.264 brouard 10676: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10677: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10678: continue;
10679: }
10680:
10681: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10682: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10683: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
10684: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10685: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
10686:
10687: /* nhstepm=nhstepm*YEARM; aff par mois*/
10688:
1.266 brouard 10689: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10690: /* and memory limitations if stepm is small */
10691:
1.238 brouard 10692: /* oldm=oldms;savm=savms; */
10693: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10694: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10695: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10696: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10697: for(i=1; i<=nlstate;i++)
10698: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10699: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10700: fprintf(ficrespijb,"\n");
1.238 brouard 10701: for (h=0; h<=nhstepm; h++){
10702: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10703: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10704: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10705: for(i=1; i<=nlstate;i++)
10706: for(j=1; j<=nlstate+ndeath;j++)
10707: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10708: fprintf(ficrespijb,"\n");
10709: }
10710: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10711: fprintf(ficrespijb,"\n");
10712: } /* end age deb */
10713: } /* end combination */
10714: } /* end nres */
1.218 brouard 10715: return 0;
10716: } /* hBijx */
1.217 brouard 10717:
1.180 brouard 10718:
1.136 brouard 10719: /***********************************************/
10720: /**************** Main Program *****************/
10721: /***********************************************/
10722:
10723: int main(int argc, char *argv[])
10724: {
10725: #ifdef GSL
10726: const gsl_multimin_fminimizer_type *T;
10727: size_t iteri = 0, it;
10728: int rval = GSL_CONTINUE;
10729: int status = GSL_SUCCESS;
10730: double ssval;
10731: #endif
10732: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 ! brouard 10733: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
! 10734: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 10735: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10736: int jj, ll, li, lj, lk;
1.136 brouard 10737: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10738: int num_filled;
1.136 brouard 10739: int itimes;
10740: int NDIM=2;
10741: int vpopbased=0;
1.235 brouard 10742: int nres=0;
1.258 brouard 10743: int endishere=0;
1.277 brouard 10744: int noffset=0;
1.274 brouard 10745: int ncurrv=0; /* Temporary variable */
10746:
1.164 brouard 10747: char ca[32], cb[32];
1.136 brouard 10748: /* FILE *fichtm; *//* Html File */
10749: /* FILE *ficgp;*/ /*Gnuplot File */
10750: struct stat info;
1.191 brouard 10751: double agedeb=0.;
1.194 brouard 10752:
10753: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10754: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10755:
1.165 brouard 10756: double fret;
1.191 brouard 10757: double dum=0.; /* Dummy variable */
1.136 brouard 10758: double ***p3mat;
1.218 brouard 10759: /* double ***mobaverage; */
1.164 brouard 10760:
10761: char line[MAXLINE];
1.197 brouard 10762: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10763:
1.234 brouard 10764: char modeltemp[MAXLINE];
1.230 brouard 10765: char resultline[MAXLINE];
10766:
1.136 brouard 10767: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10768: char *tok, *val; /* pathtot */
1.290 ! brouard 10769: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs declared globally ;*/
1.195 brouard 10770: int c, h , cpt, c2;
1.191 brouard 10771: int jl=0;
10772: int i1, j1, jk, stepsize=0;
1.194 brouard 10773: int count=0;
10774:
1.164 brouard 10775: int *tab;
1.136 brouard 10776: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.217 brouard 10777: int backcast=0;
1.136 brouard 10778: int mobilav=0,popforecast=0;
1.191 brouard 10779: int hstepm=0, nhstepm=0;
1.136 brouard 10780: int agemortsup;
10781: float sumlpop=0.;
10782: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
10783: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
10784:
1.191 brouard 10785: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 10786: double ftolpl=FTOL;
10787: double **prlim;
1.217 brouard 10788: double **bprlim;
1.136 brouard 10789: double ***param; /* Matrix of parameters */
1.251 brouard 10790: double ***paramstart; /* Matrix of starting parameter values */
10791: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 10792: double **matcov; /* Matrix of covariance */
1.203 brouard 10793: double **hess; /* Hessian matrix */
1.136 brouard 10794: double ***delti3; /* Scale */
10795: double *delti; /* Scale */
10796: double ***eij, ***vareij;
10797: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 10798:
1.136 brouard 10799: double *epj, vepp;
1.164 brouard 10800:
1.273 brouard 10801: double dateprev1, dateprev2;
10802: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0;
10803: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0;
1.217 brouard 10804:
1.136 brouard 10805: double **ximort;
1.145 brouard 10806: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 10807: int *dcwave;
10808:
1.164 brouard 10809: char z[1]="c";
1.136 brouard 10810:
10811: /*char *strt;*/
10812: char strtend[80];
1.126 brouard 10813:
1.164 brouard 10814:
1.126 brouard 10815: /* setlocale (LC_ALL, ""); */
10816: /* bindtextdomain (PACKAGE, LOCALEDIR); */
10817: /* textdomain (PACKAGE); */
10818: /* setlocale (LC_CTYPE, ""); */
10819: /* setlocale (LC_MESSAGES, ""); */
10820:
10821: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 10822: rstart_time = time(NULL);
10823: /* (void) gettimeofday(&start_time,&tzp);*/
10824: start_time = *localtime(&rstart_time);
1.126 brouard 10825: curr_time=start_time;
1.157 brouard 10826: /*tml = *localtime(&start_time.tm_sec);*/
10827: /* strcpy(strstart,asctime(&tml)); */
10828: strcpy(strstart,asctime(&start_time));
1.126 brouard 10829:
10830: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 10831: /* tp.tm_sec = tp.tm_sec +86400; */
10832: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 10833: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
10834: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
10835: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 10836: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 10837: /* strt=asctime(&tmg); */
10838: /* printf("Time(after) =%s",strstart); */
10839: /* (void) time (&time_value);
10840: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
10841: * tm = *localtime(&time_value);
10842: * strstart=asctime(&tm);
10843: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
10844: */
10845:
10846: nberr=0; /* Number of errors and warnings */
10847: nbwarn=0;
1.184 brouard 10848: #ifdef WIN32
10849: _getcwd(pathcd, size);
10850: #else
1.126 brouard 10851: getcwd(pathcd, size);
1.184 brouard 10852: #endif
1.191 brouard 10853: syscompilerinfo(0);
1.196 brouard 10854: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 10855: if(argc <=1){
10856: printf("\nEnter the parameter file name: ");
1.205 brouard 10857: if(!fgets(pathr,FILENAMELENGTH,stdin)){
10858: printf("ERROR Empty parameter file name\n");
10859: goto end;
10860: }
1.126 brouard 10861: i=strlen(pathr);
10862: if(pathr[i-1]=='\n')
10863: pathr[i-1]='\0';
1.156 brouard 10864: i=strlen(pathr);
1.205 brouard 10865: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 10866: pathr[i-1]='\0';
1.205 brouard 10867: }
10868: i=strlen(pathr);
10869: if( i==0 ){
10870: printf("ERROR Empty parameter file name\n");
10871: goto end;
10872: }
10873: for (tok = pathr; tok != NULL; ){
1.126 brouard 10874: printf("Pathr |%s|\n",pathr);
10875: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
10876: printf("val= |%s| pathr=%s\n",val,pathr);
10877: strcpy (pathtot, val);
10878: if(pathr[0] == '\0') break; /* Dirty */
10879: }
10880: }
1.281 brouard 10881: else if (argc<=2){
10882: strcpy(pathtot,argv[1]);
10883: }
1.126 brouard 10884: else{
10885: strcpy(pathtot,argv[1]);
1.281 brouard 10886: strcpy(z,argv[2]);
10887: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 10888: }
10889: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
10890: /*cygwin_split_path(pathtot,path,optionfile);
10891: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
10892: /* cutv(path,optionfile,pathtot,'\\');*/
10893:
10894: /* Split argv[0], imach program to get pathimach */
10895: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
10896: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10897: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10898: /* strcpy(pathimach,argv[0]); */
10899: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
10900: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
10901: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 10902: #ifdef WIN32
10903: _chdir(path); /* Can be a relative path */
10904: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
10905: #else
1.126 brouard 10906: chdir(path); /* Can be a relative path */
1.184 brouard 10907: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
10908: #endif
10909: printf("Current directory %s!\n",pathcd);
1.126 brouard 10910: strcpy(command,"mkdir ");
10911: strcat(command,optionfilefiname);
10912: if((outcmd=system(command)) != 0){
1.169 brouard 10913: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 10914: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
10915: /* fclose(ficlog); */
10916: /* exit(1); */
10917: }
10918: /* if((imk=mkdir(optionfilefiname))<0){ */
10919: /* perror("mkdir"); */
10920: /* } */
10921:
10922: /*-------- arguments in the command line --------*/
10923:
1.186 brouard 10924: /* Main Log file */
1.126 brouard 10925: strcat(filelog, optionfilefiname);
10926: strcat(filelog,".log"); /* */
10927: if((ficlog=fopen(filelog,"w"))==NULL) {
10928: printf("Problem with logfile %s\n",filelog);
10929: goto end;
10930: }
10931: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 10932: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 10933: fprintf(ficlog,"\nEnter the parameter file name: \n");
10934: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
10935: path=%s \n\
10936: optionfile=%s\n\
10937: optionfilext=%s\n\
1.156 brouard 10938: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 10939:
1.197 brouard 10940: syscompilerinfo(1);
1.167 brouard 10941:
1.126 brouard 10942: printf("Local time (at start):%s",strstart);
10943: fprintf(ficlog,"Local time (at start): %s",strstart);
10944: fflush(ficlog);
10945: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 10946: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 10947:
10948: /* */
10949: strcpy(fileres,"r");
10950: strcat(fileres, optionfilefiname);
1.201 brouard 10951: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 10952: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 10953: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 10954:
1.186 brouard 10955: /* Main ---------arguments file --------*/
1.126 brouard 10956:
10957: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 10958: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
10959: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 10960: fflush(ficlog);
1.149 brouard 10961: /* goto end; */
10962: exit(70);
1.126 brouard 10963: }
10964:
10965: strcpy(filereso,"o");
1.201 brouard 10966: strcat(filereso,fileresu);
1.126 brouard 10967: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
10968: printf("Problem with Output resultfile: %s\n", filereso);
10969: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
10970: fflush(ficlog);
10971: goto end;
10972: }
1.278 brouard 10973: /*-------- Rewriting parameter file ----------*/
10974: strcpy(rfileres,"r"); /* "Rparameterfile */
10975: strcat(rfileres,optionfilefiname); /* Parameter file first name */
10976: strcat(rfileres,"."); /* */
10977: strcat(rfileres,optionfilext); /* Other files have txt extension */
10978: if((ficres =fopen(rfileres,"w"))==NULL) {
10979: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
10980: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
10981: fflush(ficlog);
10982: goto end;
10983: }
10984: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 10985:
1.278 brouard 10986:
1.126 brouard 10987: /* Reads comments: lines beginning with '#' */
10988: numlinepar=0;
1.277 brouard 10989: /* Is it a BOM UTF-8 Windows file? */
10990: /* First parameter line */
1.197 brouard 10991: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 10992: noffset=0;
10993: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10994: {
10995: noffset=noffset+3;
10996: printf("# File is an UTF8 Bom.\n"); // 0xBF
10997: }
10998: else if( line[0] == (char)0xFE && line[1] == (char)0xFF)
10999: {
11000: noffset=noffset+2;
11001: printf("# File is an UTF16BE BOM file\n");
11002: }
11003: else if( line[0] == 0 && line[1] == 0)
11004: {
11005: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
11006: noffset=noffset+4;
11007: printf("# File is an UTF16BE BOM file\n");
11008: }
11009: } else{
11010: ;/*printf(" Not a BOM file\n");*/
11011: }
11012:
1.197 brouard 11013: /* If line starts with a # it is a comment */
1.277 brouard 11014: if (line[noffset] == '#') {
1.197 brouard 11015: numlinepar++;
11016: fputs(line,stdout);
11017: fputs(line,ficparo);
1.278 brouard 11018: fputs(line,ficres);
1.197 brouard 11019: fputs(line,ficlog);
11020: continue;
11021: }else
11022: break;
11023: }
11024: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11025: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11026: if (num_filled != 5) {
11027: printf("Should be 5 parameters\n");
1.283 brouard 11028: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11029: }
1.126 brouard 11030: numlinepar++;
1.197 brouard 11031: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11032: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11033: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11034: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11035: }
11036: /* Second parameter line */
11037: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11038: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11039: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11040: if (line[0] == '#') {
11041: numlinepar++;
1.283 brouard 11042: printf("%s",line);
11043: fprintf(ficres,"%s",line);
11044: fprintf(ficparo,"%s",line);
11045: fprintf(ficlog,"%s",line);
1.197 brouard 11046: continue;
11047: }else
11048: break;
11049: }
1.223 brouard 11050: 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", \
11051: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11052: if (num_filled != 11) {
11053: 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 11054: printf("but line=%s\n",line);
1.283 brouard 11055: 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");
11056: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11057: }
1.286 brouard 11058: if( lastpass > maxwav){
11059: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11060: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11061: fflush(ficlog);
11062: goto end;
11063: }
11064: 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 11065: 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 11066: 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 11067: 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 11068: }
1.203 brouard 11069: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11070: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11071: /* Third parameter line */
11072: while(fgets(line, MAXLINE, ficpar)) {
11073: /* If line starts with a # it is a comment */
11074: if (line[0] == '#') {
11075: numlinepar++;
1.283 brouard 11076: printf("%s",line);
11077: fprintf(ficres,"%s",line);
11078: fprintf(ficparo,"%s",line);
11079: fprintf(ficlog,"%s",line);
1.197 brouard 11080: continue;
11081: }else
11082: break;
11083: }
1.201 brouard 11084: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11085: if (num_filled != 1){
11086: printf("ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
11087: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
1.197 brouard 11088: model[0]='\0';
11089: goto end;
11090: }
11091: else{
11092: if (model[0]=='+'){
11093: for(i=1; i<=strlen(model);i++)
11094: modeltemp[i-1]=model[i];
1.201 brouard 11095: strcpy(model,modeltemp);
1.197 brouard 11096: }
11097: }
1.199 brouard 11098: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11099: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11100: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11101: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11102: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11103: }
11104: /* 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); */
11105: /* numlinepar=numlinepar+3; /\* In general *\/ */
11106: /* 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 11107: /* 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); */
11108: /* 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 11109: fflush(ficlog);
1.190 brouard 11110: /* if(model[0]=='#'|| model[0]== '\0'){ */
11111: if(model[0]=='#'){
1.279 brouard 11112: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11113: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11114: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11115: if(mle != -1){
1.279 brouard 11116: 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 11117: exit(1);
11118: }
11119: }
1.126 brouard 11120: while((c=getc(ficpar))=='#' && c!= EOF){
11121: ungetc(c,ficpar);
11122: fgets(line, MAXLINE, ficpar);
11123: numlinepar++;
1.195 brouard 11124: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11125: z[0]=line[1];
11126: }
11127: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11128: fputs(line, stdout);
11129: //puts(line);
1.126 brouard 11130: fputs(line,ficparo);
11131: fputs(line,ficlog);
11132: }
11133: ungetc(c,ficpar);
11134:
11135:
1.290 ! brouard 11136: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
! 11137: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
! 11138: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
! 11139: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11140: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11141: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11142: v1+v2*age+v2*v3 makes cptcovn = 3
11143: */
11144: if (strlen(model)>1)
1.187 brouard 11145: 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 11146: else
1.187 brouard 11147: ncovmodel=2; /* Constant and age */
1.133 brouard 11148: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11149: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11150: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11151: 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);
11152: 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);
11153: fflush(stdout);
11154: fclose (ficlog);
11155: goto end;
11156: }
1.126 brouard 11157: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11158: delti=delti3[1][1];
11159: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11160: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11161: /* We could also provide initial parameters values giving by simple logistic regression
11162: * only one way, that is without matrix product. We will have nlstate maximizations */
11163: /* for(i=1;i<nlstate;i++){ */
11164: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11165: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11166: /* } */
1.126 brouard 11167: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11168: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11169: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11170: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11171: fclose (ficparo);
11172: fclose (ficlog);
11173: goto end;
11174: exit(0);
1.220 brouard 11175: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11176: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11177: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11178: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11179: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11180: matcov=matrix(1,npar,1,npar);
1.203 brouard 11181: hess=matrix(1,npar,1,npar);
1.220 brouard 11182: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11183: /* Read guessed parameters */
1.126 brouard 11184: /* Reads comments: lines beginning with '#' */
11185: while((c=getc(ficpar))=='#' && c!= EOF){
11186: ungetc(c,ficpar);
11187: fgets(line, MAXLINE, ficpar);
11188: numlinepar++;
1.141 brouard 11189: fputs(line,stdout);
1.126 brouard 11190: fputs(line,ficparo);
11191: fputs(line,ficlog);
11192: }
11193: ungetc(c,ficpar);
11194:
11195: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11196: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11197: for(i=1; i <=nlstate; i++){
1.234 brouard 11198: j=0;
1.126 brouard 11199: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11200: if(jj==i) continue;
11201: j++;
11202: fscanf(ficpar,"%1d%1d",&i1,&j1);
11203: if ((i1 != i) || (j1 != jj)){
11204: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11205: It might be a problem of design; if ncovcol and the model are correct\n \
11206: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11207: exit(1);
11208: }
11209: fprintf(ficparo,"%1d%1d",i1,j1);
11210: if(mle==1)
11211: printf("%1d%1d",i,jj);
11212: fprintf(ficlog,"%1d%1d",i,jj);
11213: for(k=1; k<=ncovmodel;k++){
11214: fscanf(ficpar," %lf",¶m[i][j][k]);
11215: if(mle==1){
11216: printf(" %lf",param[i][j][k]);
11217: fprintf(ficlog," %lf",param[i][j][k]);
11218: }
11219: else
11220: fprintf(ficlog," %lf",param[i][j][k]);
11221: fprintf(ficparo," %lf",param[i][j][k]);
11222: }
11223: fscanf(ficpar,"\n");
11224: numlinepar++;
11225: if(mle==1)
11226: printf("\n");
11227: fprintf(ficlog,"\n");
11228: fprintf(ficparo,"\n");
1.126 brouard 11229: }
11230: }
11231: fflush(ficlog);
1.234 brouard 11232:
1.251 brouard 11233: /* Reads parameters values */
1.126 brouard 11234: p=param[1][1];
1.251 brouard 11235: pstart=paramstart[1][1];
1.126 brouard 11236:
11237: /* Reads comments: lines beginning with '#' */
11238: while((c=getc(ficpar))=='#' && c!= EOF){
11239: ungetc(c,ficpar);
11240: fgets(line, MAXLINE, ficpar);
11241: numlinepar++;
1.141 brouard 11242: fputs(line,stdout);
1.126 brouard 11243: fputs(line,ficparo);
11244: fputs(line,ficlog);
11245: }
11246: ungetc(c,ficpar);
11247:
11248: for(i=1; i <=nlstate; i++){
11249: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11250: fscanf(ficpar,"%1d%1d",&i1,&j1);
11251: if ( (i1-i) * (j1-j) != 0){
11252: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11253: exit(1);
11254: }
11255: printf("%1d%1d",i,j);
11256: fprintf(ficparo,"%1d%1d",i1,j1);
11257: fprintf(ficlog,"%1d%1d",i1,j1);
11258: for(k=1; k<=ncovmodel;k++){
11259: fscanf(ficpar,"%le",&delti3[i][j][k]);
11260: printf(" %le",delti3[i][j][k]);
11261: fprintf(ficparo," %le",delti3[i][j][k]);
11262: fprintf(ficlog," %le",delti3[i][j][k]);
11263: }
11264: fscanf(ficpar,"\n");
11265: numlinepar++;
11266: printf("\n");
11267: fprintf(ficparo,"\n");
11268: fprintf(ficlog,"\n");
1.126 brouard 11269: }
11270: }
11271: fflush(ficlog);
1.234 brouard 11272:
1.145 brouard 11273: /* Reads covariance matrix */
1.126 brouard 11274: delti=delti3[1][1];
1.220 brouard 11275:
11276:
1.126 brouard 11277: /* 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 11278:
1.126 brouard 11279: /* Reads comments: lines beginning with '#' */
11280: while((c=getc(ficpar))=='#' && c!= EOF){
11281: ungetc(c,ficpar);
11282: fgets(line, MAXLINE, ficpar);
11283: numlinepar++;
1.141 brouard 11284: fputs(line,stdout);
1.126 brouard 11285: fputs(line,ficparo);
11286: fputs(line,ficlog);
11287: }
11288: ungetc(c,ficpar);
1.220 brouard 11289:
1.126 brouard 11290: matcov=matrix(1,npar,1,npar);
1.203 brouard 11291: hess=matrix(1,npar,1,npar);
1.131 brouard 11292: for(i=1; i <=npar; i++)
11293: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11294:
1.194 brouard 11295: /* Scans npar lines */
1.126 brouard 11296: for(i=1; i <=npar; i++){
1.226 brouard 11297: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11298: if(count != 3){
1.226 brouard 11299: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11300: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11301: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11302: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11303: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11304: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11305: exit(1);
1.220 brouard 11306: }else{
1.226 brouard 11307: if(mle==1)
11308: printf("%1d%1d%d",i1,j1,jk);
11309: }
11310: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11311: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11312: for(j=1; j <=i; j++){
1.226 brouard 11313: fscanf(ficpar," %le",&matcov[i][j]);
11314: if(mle==1){
11315: printf(" %.5le",matcov[i][j]);
11316: }
11317: fprintf(ficlog," %.5le",matcov[i][j]);
11318: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11319: }
11320: fscanf(ficpar,"\n");
11321: numlinepar++;
11322: if(mle==1)
1.220 brouard 11323: printf("\n");
1.126 brouard 11324: fprintf(ficlog,"\n");
11325: fprintf(ficparo,"\n");
11326: }
1.194 brouard 11327: /* End of read covariance matrix npar lines */
1.126 brouard 11328: for(i=1; i <=npar; i++)
11329: for(j=i+1;j<=npar;j++)
1.226 brouard 11330: matcov[i][j]=matcov[j][i];
1.126 brouard 11331:
11332: if(mle==1)
11333: printf("\n");
11334: fprintf(ficlog,"\n");
11335:
11336: fflush(ficlog);
11337:
11338: } /* End of mle != -3 */
1.218 brouard 11339:
1.186 brouard 11340: /* Main data
11341: */
1.290 ! brouard 11342: nobs=lastobs-firstobs+1; /* was = lastobs;*/
! 11343: /* num=lvector(1,n); */
! 11344: /* moisnais=vector(1,n); */
! 11345: /* annais=vector(1,n); */
! 11346: /* moisdc=vector(1,n); */
! 11347: /* andc=vector(1,n); */
! 11348: /* weight=vector(1,n); */
! 11349: /* agedc=vector(1,n); */
! 11350: /* cod=ivector(1,n); */
! 11351: /* for(i=1;i<=n;i++){ */
! 11352: num=lvector(firstobs,lastobs);
! 11353: moisnais=vector(firstobs,lastobs);
! 11354: annais=vector(firstobs,lastobs);
! 11355: moisdc=vector(firstobs,lastobs);
! 11356: andc=vector(firstobs,lastobs);
! 11357: weight=vector(firstobs,lastobs);
! 11358: agedc=vector(firstobs,lastobs);
! 11359: cod=ivector(firstobs,lastobs);
! 11360: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 11361: num[i]=0;
11362: moisnais[i]=0;
11363: annais[i]=0;
11364: moisdc[i]=0;
11365: andc[i]=0;
11366: agedc[i]=0;
11367: cod[i]=0;
11368: weight[i]=1.0; /* Equal weights, 1 by default */
11369: }
1.290 ! brouard 11370: mint=matrix(1,maxwav,firstobs,lastobs);
! 11371: anint=matrix(1,maxwav,firstobs,lastobs);
! 11372: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11373: tab=ivector(1,NCOVMAX);
1.144 brouard 11374: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11375: 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 11376:
1.136 brouard 11377: /* Reads data from file datafile */
11378: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11379: goto end;
11380:
11381: /* Calculation of the number of parameters from char model */
1.234 brouard 11382: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11383: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11384: k=3 V4 Tvar[k=3]= 4 (from V4)
11385: k=2 V1 Tvar[k=2]= 1 (from V1)
11386: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11387: */
11388:
11389: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11390: TvarsDind=ivector(1,NCOVMAX); /* */
11391: TvarsD=ivector(1,NCOVMAX); /* */
11392: TvarsQind=ivector(1,NCOVMAX); /* */
11393: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11394: TvarF=ivector(1,NCOVMAX); /* */
11395: TvarFind=ivector(1,NCOVMAX); /* */
11396: TvarV=ivector(1,NCOVMAX); /* */
11397: TvarVind=ivector(1,NCOVMAX); /* */
11398: TvarA=ivector(1,NCOVMAX); /* */
11399: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11400: TvarFD=ivector(1,NCOVMAX); /* */
11401: TvarFDind=ivector(1,NCOVMAX); /* */
11402: TvarFQ=ivector(1,NCOVMAX); /* */
11403: TvarFQind=ivector(1,NCOVMAX); /* */
11404: TvarVD=ivector(1,NCOVMAX); /* */
11405: TvarVDind=ivector(1,NCOVMAX); /* */
11406: TvarVQ=ivector(1,NCOVMAX); /* */
11407: TvarVQind=ivector(1,NCOVMAX); /* */
11408:
1.230 brouard 11409: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11410: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11411: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11412: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11413: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11414: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11415: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11416: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11417: */
11418: /* For model-covariate k tells which data-covariate to use but
11419: because this model-covariate is a construction we invent a new column
11420: ncovcol + k1
11421: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11422: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11423: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11424: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11425: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11426: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11427: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11428: */
1.145 brouard 11429: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11430: 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 11431: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11432: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11433: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11434: 4 covariates (3 plus signs)
11435: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11436: */
1.230 brouard 11437: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11438: * individual dummy, fixed or varying:
11439: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11440: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11441: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11442: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11443: * Tmodelind[1]@9={9,0,3,2,}*/
11444: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11445: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11446: * individual quantitative, fixed or varying:
11447: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11448: * 3, 1, 0, 0, 0, 0, 0, 0},
11449: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11450: /* Main decodemodel */
11451:
1.187 brouard 11452:
1.223 brouard 11453: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11454: goto end;
11455:
1.137 brouard 11456: if((double)(lastobs-imx)/(double)imx > 1.10){
11457: nbwarn++;
11458: 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);
11459: 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);
11460: }
1.136 brouard 11461: /* if(mle==1){*/
1.137 brouard 11462: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11463: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11464: }
11465:
11466: /*-calculation of age at interview from date of interview and age at death -*/
11467: agev=matrix(1,maxwav,1,imx);
11468:
11469: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11470: goto end;
11471:
1.126 brouard 11472:
1.136 brouard 11473: agegomp=(int)agemin;
1.290 ! brouard 11474: free_vector(moisnais,firstobs,lastobs);
! 11475: free_vector(annais,firstobs,lastobs);
1.126 brouard 11476: /* free_matrix(mint,1,maxwav,1,n);
11477: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11478: /* free_vector(moisdc,1,n); */
11479: /* free_vector(andc,1,n); */
1.145 brouard 11480: /* */
11481:
1.126 brouard 11482: wav=ivector(1,imx);
1.214 brouard 11483: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11484: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11485: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11486: 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.*/
11487: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11488: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11489:
11490: /* Concatenates waves */
1.214 brouard 11491: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11492: Death is a valid wave (if date is known).
11493: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11494: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11495: and mw[mi+1][i]. dh depends on stepm.
11496: */
11497:
1.126 brouard 11498: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11499: /* Concatenates waves */
1.145 brouard 11500:
1.290 ! brouard 11501: free_vector(moisdc,firstobs,lastobs);
! 11502: free_vector(andc,firstobs,lastobs);
1.215 brouard 11503:
1.126 brouard 11504: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11505: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11506: ncodemax[1]=1;
1.145 brouard 11507: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11508: cptcoveff=0;
1.220 brouard 11509: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11510: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11511: }
11512:
11513: ncovcombmax=pow(2,cptcoveff);
11514: invalidvarcomb=ivector(1, ncovcombmax);
11515: for(i=1;i<ncovcombmax;i++)
11516: invalidvarcomb[i]=0;
11517:
1.211 brouard 11518: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11519: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11520: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11521:
1.200 brouard 11522: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11523: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11524: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11525: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11526: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11527: * (currently 0 or 1) in the data.
11528: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11529: * corresponding modality (h,j).
11530: */
11531:
1.145 brouard 11532: h=0;
11533: /*if (cptcovn > 0) */
1.126 brouard 11534: m=pow(2,cptcoveff);
11535:
1.144 brouard 11536: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11537: * For k=4 covariates, h goes from 1 to m=2**k
11538: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11539: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11540: * h\k 1 2 3 4
1.143 brouard 11541: *______________________________
11542: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11543: * 2 2 1 1 1
11544: * 3 i=2 1 2 1 1
11545: * 4 2 2 1 1
11546: * 5 i=3 1 i=2 1 2 1
11547: * 6 2 1 2 1
11548: * 7 i=4 1 2 2 1
11549: * 8 2 2 2 1
1.197 brouard 11550: * 9 i=5 1 i=3 1 i=2 1 2
11551: * 10 2 1 1 2
11552: * 11 i=6 1 2 1 2
11553: * 12 2 2 1 2
11554: * 13 i=7 1 i=4 1 2 2
11555: * 14 2 1 2 2
11556: * 15 i=8 1 2 2 2
11557: * 16 2 2 2 2
1.143 brouard 11558: */
1.212 brouard 11559: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11560: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11561: * and the value of each covariate?
11562: * V1=1, V2=1, V3=2, V4=1 ?
11563: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11564: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11565: * In order to get the real value in the data, we use nbcode
11566: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11567: * We are keeping this crazy system in order to be able (in the future?)
11568: * to have more than 2 values (0 or 1) for a covariate.
11569: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11570: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11571: * bbbbbbbb
11572: * 76543210
11573: * h-1 00000101 (6-1=5)
1.219 brouard 11574: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11575: * &
11576: * 1 00000001 (1)
1.219 brouard 11577: * 00000000 = 1 & ((h-1) >> (k-1))
11578: * +1= 00000001 =1
1.211 brouard 11579: *
11580: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11581: * h' 1101 =2^3+2^2+0x2^1+2^0
11582: * >>k' 11
11583: * & 00000001
11584: * = 00000001
11585: * +1 = 00000010=2 = codtabm(14,3)
11586: * Reverse h=6 and m=16?
11587: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11588: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11589: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11590: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11591: * V3=decodtabm(14,3,2**4)=2
11592: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11593: *(h-1) >> (j-1) 0011 =13 >> 2
11594: * &1 000000001
11595: * = 000000001
11596: * +1= 000000010 =2
11597: * 2211
11598: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11599: * V3=2
1.220 brouard 11600: * codtabm and decodtabm are identical
1.211 brouard 11601: */
11602:
1.145 brouard 11603:
11604: free_ivector(Ndum,-1,NCOVMAX);
11605:
11606:
1.126 brouard 11607:
1.186 brouard 11608: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11609: strcpy(optionfilegnuplot,optionfilefiname);
11610: if(mle==-3)
1.201 brouard 11611: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11612: strcat(optionfilegnuplot,".gp");
11613:
11614: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11615: printf("Problem with file %s",optionfilegnuplot);
11616: }
11617: else{
1.204 brouard 11618: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11619: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11620: //fprintf(ficgp,"set missing 'NaNq'\n");
11621: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11622: }
11623: /* fclose(ficgp);*/
1.186 brouard 11624:
11625:
11626: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11627:
11628: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11629: if(mle==-3)
1.201 brouard 11630: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11631: strcat(optionfilehtm,".htm");
11632: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11633: printf("Problem with %s \n",optionfilehtm);
11634: exit(0);
1.126 brouard 11635: }
11636:
11637: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11638: strcat(optionfilehtmcov,"-cov.htm");
11639: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11640: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11641: }
11642: else{
11643: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11644: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11645: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11646: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11647: }
11648:
1.213 brouard 11649: fprintf(fichtm,"<html><head>\n<head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<title>IMaCh %s</title></head>\n <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n<font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>-EUROREVES-Institut de longévité-2013-2016-Japan Society for the Promotion of Sciences 日本学術振興会 (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \
1.204 brouard 11650: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11651: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11652: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11653: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11654: \n\
11655: <hr size=\"2\" color=\"#EC5E5E\">\
11656: <ul><li><h4>Parameter files</h4>\n\
11657: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11658: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11659: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11660: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11661: - Date and time at start: %s</ul>\n",\
11662: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11663: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11664: fileres,fileres,\
11665: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11666: fflush(fichtm);
11667:
11668: strcpy(pathr,path);
11669: strcat(pathr,optionfilefiname);
1.184 brouard 11670: #ifdef WIN32
11671: _chdir(optionfilefiname); /* Move to directory named optionfile */
11672: #else
1.126 brouard 11673: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11674: #endif
11675:
1.126 brouard 11676:
1.220 brouard 11677: /* Calculates basic frequencies. Computes observed prevalence at single age
11678: and for any valid combination of covariates
1.126 brouard 11679: and prints on file fileres'p'. */
1.251 brouard 11680: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11681: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11682:
11683: fprintf(fichtm,"\n");
1.286 brouard 11684: 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 11685: ftol, stepm);
11686: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
11687: ncurrv=1;
11688: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
11689: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
11690: ncurrv=i;
11691: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 ! brouard 11692: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 11693: ncurrv=i;
11694: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 ! brouard 11695: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 11696: ncurrv=i;
11697: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
11698: 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", \
11699: nlstate, ndeath, maxwav, mle, weightopt);
11700:
11701: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
11702: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
11703:
11704:
11705: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Total number of observations=%d <br>\n\
1.126 brouard 11706: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11707: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 11708: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 11709: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 11710: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11711: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11712: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11713: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11714:
1.126 brouard 11715: /* For Powell, parameters are in a vector p[] starting at p[1]
11716: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11717: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11718:
11719: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11720: /* For mortality only */
1.126 brouard 11721: if (mle==-3){
1.136 brouard 11722: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11723: for(i=1;i<=NDIM;i++)
11724: for(j=1;j<=NDIM;j++)
11725: ximort[i][j]=0.;
1.186 brouard 11726: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 ! brouard 11727: cens=ivector(firstobs,lastobs);
! 11728: ageexmed=vector(firstobs,lastobs);
! 11729: agecens=vector(firstobs,lastobs);
! 11730: dcwave=ivector(firstobs,lastobs);
1.223 brouard 11731:
1.126 brouard 11732: for (i=1; i<=imx; i++){
11733: dcwave[i]=-1;
11734: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11735: if (s[m][i]>nlstate) {
11736: dcwave[i]=m;
11737: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11738: break;
11739: }
1.126 brouard 11740: }
1.226 brouard 11741:
1.126 brouard 11742: for (i=1; i<=imx; i++) {
11743: if (wav[i]>0){
1.226 brouard 11744: ageexmed[i]=agev[mw[1][i]][i];
11745: j=wav[i];
11746: agecens[i]=1.;
11747:
11748: if (ageexmed[i]> 1 && wav[i] > 0){
11749: agecens[i]=agev[mw[j][i]][i];
11750: cens[i]= 1;
11751: }else if (ageexmed[i]< 1)
11752: cens[i]= -1;
11753: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11754: cens[i]=0 ;
1.126 brouard 11755: }
11756: else cens[i]=-1;
11757: }
11758:
11759: for (i=1;i<=NDIM;i++) {
11760: for (j=1;j<=NDIM;j++)
1.226 brouard 11761: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 11762: }
11763:
1.145 brouard 11764: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 11765: /*printf("%lf %lf", p[1], p[2]);*/
11766:
11767:
1.136 brouard 11768: #ifdef GSL
11769: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 11770: #else
1.126 brouard 11771: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 11772: #endif
1.201 brouard 11773: strcpy(filerespow,"POW-MORT_");
11774: strcat(filerespow,fileresu);
1.126 brouard 11775: if((ficrespow=fopen(filerespow,"w"))==NULL) {
11776: printf("Problem with resultfile: %s\n", filerespow);
11777: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
11778: }
1.136 brouard 11779: #ifdef GSL
11780: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 11781: #else
1.126 brouard 11782: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 11783: #endif
1.126 brouard 11784: /* for (i=1;i<=nlstate;i++)
11785: for(j=1;j<=nlstate+ndeath;j++)
11786: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
11787: */
11788: fprintf(ficrespow,"\n");
1.136 brouard 11789: #ifdef GSL
11790: /* gsl starts here */
11791: T = gsl_multimin_fminimizer_nmsimplex;
11792: gsl_multimin_fminimizer *sfm = NULL;
11793: gsl_vector *ss, *x;
11794: gsl_multimin_function minex_func;
11795:
11796: /* Initial vertex size vector */
11797: ss = gsl_vector_alloc (NDIM);
11798:
11799: if (ss == NULL){
11800: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
11801: }
11802: /* Set all step sizes to 1 */
11803: gsl_vector_set_all (ss, 0.001);
11804:
11805: /* Starting point */
1.126 brouard 11806:
1.136 brouard 11807: x = gsl_vector_alloc (NDIM);
11808:
11809: if (x == NULL){
11810: gsl_vector_free(ss);
11811: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
11812: }
11813:
11814: /* Initialize method and iterate */
11815: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 11816: /* gsl_vector_set(x, 0, 0.0268); */
11817: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 11818: gsl_vector_set(x, 0, p[1]);
11819: gsl_vector_set(x, 1, p[2]);
11820:
11821: minex_func.f = &gompertz_f;
11822: minex_func.n = NDIM;
11823: minex_func.params = (void *)&p; /* ??? */
11824:
11825: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
11826: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
11827:
11828: printf("Iterations beginning .....\n\n");
11829: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
11830:
11831: iteri=0;
11832: while (rval == GSL_CONTINUE){
11833: iteri++;
11834: status = gsl_multimin_fminimizer_iterate(sfm);
11835:
11836: if (status) printf("error: %s\n", gsl_strerror (status));
11837: fflush(0);
11838:
11839: if (status)
11840: break;
11841:
11842: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
11843: ssval = gsl_multimin_fminimizer_size (sfm);
11844:
11845: if (rval == GSL_SUCCESS)
11846: printf ("converged to a local maximum at\n");
11847:
11848: printf("%5d ", iteri);
11849: for (it = 0; it < NDIM; it++){
11850: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
11851: }
11852: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
11853: }
11854:
11855: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
11856:
11857: gsl_vector_free(x); /* initial values */
11858: gsl_vector_free(ss); /* inital step size */
11859: for (it=0; it<NDIM; it++){
11860: p[it+1]=gsl_vector_get(sfm->x,it);
11861: fprintf(ficrespow," %.12lf", p[it]);
11862: }
11863: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
11864: #endif
11865: #ifdef POWELL
11866: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
11867: #endif
1.126 brouard 11868: fclose(ficrespow);
11869:
1.203 brouard 11870: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 11871:
11872: for(i=1; i <=NDIM; i++)
11873: for(j=i+1;j<=NDIM;j++)
1.220 brouard 11874: matcov[i][j]=matcov[j][i];
1.126 brouard 11875:
11876: printf("\nCovariance matrix\n ");
1.203 brouard 11877: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 11878: for(i=1; i <=NDIM; i++) {
11879: for(j=1;j<=NDIM;j++){
1.220 brouard 11880: printf("%f ",matcov[i][j]);
11881: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 11882: }
1.203 brouard 11883: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 11884: }
11885:
11886: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 11887: for (i=1;i<=NDIM;i++) {
1.126 brouard 11888: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 11889: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
11890: }
1.126 brouard 11891: lsurv=vector(1,AGESUP);
11892: lpop=vector(1,AGESUP);
11893: tpop=vector(1,AGESUP);
11894: lsurv[agegomp]=100000;
11895:
11896: for (k=agegomp;k<=AGESUP;k++) {
11897: agemortsup=k;
11898: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
11899: }
11900:
11901: for (k=agegomp;k<agemortsup;k++)
11902: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
11903:
11904: for (k=agegomp;k<agemortsup;k++){
11905: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
11906: sumlpop=sumlpop+lpop[k];
11907: }
11908:
11909: tpop[agegomp]=sumlpop;
11910: for (k=agegomp;k<(agemortsup-3);k++){
11911: /* tpop[k+1]=2;*/
11912: tpop[k+1]=tpop[k]-lpop[k];
11913: }
11914:
11915:
11916: printf("\nAge lx qx dx Lx Tx e(x)\n");
11917: for (k=agegomp;k<(agemortsup-2);k++)
11918: 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]);
11919:
11920:
11921: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 11922: ageminpar=50;
11923: agemaxpar=100;
1.194 brouard 11924: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
11925: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11926: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11927: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
11928: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11929: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11930: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 11931: }else{
11932: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
11933: 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 11934: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 11935: }
1.201 brouard 11936: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 11937: stepm, weightopt,\
11938: model,imx,p,matcov,agemortsup);
11939:
11940: free_vector(lsurv,1,AGESUP);
11941: free_vector(lpop,1,AGESUP);
11942: free_vector(tpop,1,AGESUP);
1.220 brouard 11943: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 ! brouard 11944: free_ivector(dcwave,firstobs,lastobs);
! 11945: free_vector(agecens,firstobs,lastobs);
! 11946: free_vector(ageexmed,firstobs,lastobs);
! 11947: free_ivector(cens,firstobs,lastobs);
1.220 brouard 11948: #ifdef GSL
1.136 brouard 11949: #endif
1.186 brouard 11950: } /* Endof if mle==-3 mortality only */
1.205 brouard 11951: /* Standard */
11952: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
11953: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11954: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 11955: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 11956: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11957: for (k=1; k<=npar;k++)
11958: printf(" %d %8.5f",k,p[k]);
11959: printf("\n");
1.205 brouard 11960: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
11961: /* mlikeli uses func not funcone */
1.247 brouard 11962: /* for(i=1;i<nlstate;i++){ */
11963: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11964: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11965: /* } */
1.205 brouard 11966: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
11967: }
11968: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
11969: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11970: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
11971: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11972: }
11973: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 11974: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11975: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11976: for (k=1; k<=npar;k++)
11977: printf(" %d %8.5f",k,p[k]);
11978: printf("\n");
11979:
11980: /*--------- results files --------------*/
1.283 brouard 11981: /* 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 11982:
11983:
11984: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11985: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11986: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11987: for(i=1,jk=1; i <=nlstate; i++){
11988: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 11989: if (k != i) {
11990: printf("%d%d ",i,k);
11991: fprintf(ficlog,"%d%d ",i,k);
11992: fprintf(ficres,"%1d%1d ",i,k);
11993: for(j=1; j <=ncovmodel; j++){
11994: printf("%12.7f ",p[jk]);
11995: fprintf(ficlog,"%12.7f ",p[jk]);
11996: fprintf(ficres,"%12.7f ",p[jk]);
11997: jk++;
11998: }
11999: printf("\n");
12000: fprintf(ficlog,"\n");
12001: fprintf(ficres,"\n");
12002: }
1.126 brouard 12003: }
12004: }
1.203 brouard 12005: if(mle != 0){
12006: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 12007: ftolhess=ftol; /* Usually correct */
1.203 brouard 12008: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
12009: 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");
12010: 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");
12011: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 12012: for(k=1; k <=(nlstate+ndeath); k++){
12013: if (k != i) {
12014: printf("%d%d ",i,k);
12015: fprintf(ficlog,"%d%d ",i,k);
12016: for(j=1; j <=ncovmodel; j++){
12017: 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]));
12018: 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]));
12019: jk++;
12020: }
12021: printf("\n");
12022: fprintf(ficlog,"\n");
12023: }
12024: }
1.193 brouard 12025: }
1.203 brouard 12026: } /* end of hesscov and Wald tests */
1.225 brouard 12027:
1.203 brouard 12028: /* */
1.126 brouard 12029: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
12030: printf("# Scales (for hessian or gradient estimation)\n");
12031: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
12032: for(i=1,jk=1; i <=nlstate; i++){
12033: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 12034: if (j!=i) {
12035: fprintf(ficres,"%1d%1d",i,j);
12036: printf("%1d%1d",i,j);
12037: fprintf(ficlog,"%1d%1d",i,j);
12038: for(k=1; k<=ncovmodel;k++){
12039: printf(" %.5e",delti[jk]);
12040: fprintf(ficlog," %.5e",delti[jk]);
12041: fprintf(ficres," %.5e",delti[jk]);
12042: jk++;
12043: }
12044: printf("\n");
12045: fprintf(ficlog,"\n");
12046: fprintf(ficres,"\n");
12047: }
1.126 brouard 12048: }
12049: }
12050:
12051: 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 12052: if(mle >= 1) /* To big for the screen */
1.126 brouard 12053: 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");
12054: 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");
12055: /* # 121 Var(a12)\n\ */
12056: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12057: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12058: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12059: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12060: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12061: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12062: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12063:
12064:
12065: /* Just to have a covariance matrix which will be more understandable
12066: even is we still don't want to manage dictionary of variables
12067: */
12068: for(itimes=1;itimes<=2;itimes++){
12069: jj=0;
12070: for(i=1; i <=nlstate; i++){
1.225 brouard 12071: for(j=1; j <=nlstate+ndeath; j++){
12072: if(j==i) continue;
12073: for(k=1; k<=ncovmodel;k++){
12074: jj++;
12075: ca[0]= k+'a'-1;ca[1]='\0';
12076: if(itimes==1){
12077: if(mle>=1)
12078: printf("#%1d%1d%d",i,j,k);
12079: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12080: fprintf(ficres,"#%1d%1d%d",i,j,k);
12081: }else{
12082: if(mle>=1)
12083: printf("%1d%1d%d",i,j,k);
12084: fprintf(ficlog,"%1d%1d%d",i,j,k);
12085: fprintf(ficres,"%1d%1d%d",i,j,k);
12086: }
12087: ll=0;
12088: for(li=1;li <=nlstate; li++){
12089: for(lj=1;lj <=nlstate+ndeath; lj++){
12090: if(lj==li) continue;
12091: for(lk=1;lk<=ncovmodel;lk++){
12092: ll++;
12093: if(ll<=jj){
12094: cb[0]= lk +'a'-1;cb[1]='\0';
12095: if(ll<jj){
12096: if(itimes==1){
12097: if(mle>=1)
12098: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12099: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12100: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12101: }else{
12102: if(mle>=1)
12103: printf(" %.5e",matcov[jj][ll]);
12104: fprintf(ficlog," %.5e",matcov[jj][ll]);
12105: fprintf(ficres," %.5e",matcov[jj][ll]);
12106: }
12107: }else{
12108: if(itimes==1){
12109: if(mle>=1)
12110: printf(" Var(%s%1d%1d)",ca,i,j);
12111: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12112: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12113: }else{
12114: if(mle>=1)
12115: printf(" %.7e",matcov[jj][ll]);
12116: fprintf(ficlog," %.7e",matcov[jj][ll]);
12117: fprintf(ficres," %.7e",matcov[jj][ll]);
12118: }
12119: }
12120: }
12121: } /* end lk */
12122: } /* end lj */
12123: } /* end li */
12124: if(mle>=1)
12125: printf("\n");
12126: fprintf(ficlog,"\n");
12127: fprintf(ficres,"\n");
12128: numlinepar++;
12129: } /* end k*/
12130: } /*end j */
1.126 brouard 12131: } /* end i */
12132: } /* end itimes */
12133:
12134: fflush(ficlog);
12135: fflush(ficres);
1.225 brouard 12136: while(fgets(line, MAXLINE, ficpar)) {
12137: /* If line starts with a # it is a comment */
12138: if (line[0] == '#') {
12139: numlinepar++;
12140: fputs(line,stdout);
12141: fputs(line,ficparo);
12142: fputs(line,ficlog);
12143: continue;
12144: }else
12145: break;
12146: }
12147:
1.209 brouard 12148: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12149: /* ungetc(c,ficpar); */
12150: /* fgets(line, MAXLINE, ficpar); */
12151: /* fputs(line,stdout); */
12152: /* fputs(line,ficparo); */
12153: /* } */
12154: /* ungetc(c,ficpar); */
1.126 brouard 12155:
12156: estepm=0;
1.209 brouard 12157: 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 12158:
12159: if (num_filled != 6) {
12160: 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);
12161: 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);
12162: goto end;
12163: }
12164: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12165: }
12166: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12167: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12168:
1.209 brouard 12169: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12170: if (estepm==0 || estepm < stepm) estepm=stepm;
12171: if (fage <= 2) {
12172: bage = ageminpar;
12173: fage = agemaxpar;
12174: }
12175:
12176: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12177: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12178: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12179:
1.186 brouard 12180: /* Other stuffs, more or less useful */
1.254 brouard 12181: while(fgets(line, MAXLINE, ficpar)) {
12182: /* If line starts with a # it is a comment */
12183: if (line[0] == '#') {
12184: numlinepar++;
12185: fputs(line,stdout);
12186: fputs(line,ficparo);
12187: fputs(line,ficlog);
12188: continue;
12189: }else
12190: break;
12191: }
12192:
12193: 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){
12194:
12195: if (num_filled != 7) {
12196: 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);
12197: 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);
12198: goto end;
12199: }
12200: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12201: 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);
12202: 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);
12203: 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 12204: }
1.254 brouard 12205:
12206: while(fgets(line, MAXLINE, ficpar)) {
12207: /* If line starts with a # it is a comment */
12208: if (line[0] == '#') {
12209: numlinepar++;
12210: fputs(line,stdout);
12211: fputs(line,ficparo);
12212: fputs(line,ficlog);
12213: continue;
12214: }else
12215: break;
1.126 brouard 12216: }
12217:
12218:
12219: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12220: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12221:
1.254 brouard 12222: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12223: if (num_filled != 1) {
12224: 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);
12225: 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);
12226: goto end;
12227: }
12228: printf("pop_based=%d\n",popbased);
12229: fprintf(ficlog,"pop_based=%d\n",popbased);
12230: fprintf(ficparo,"pop_based=%d\n",popbased);
12231: fprintf(ficres,"pop_based=%d\n",popbased);
12232: }
12233:
1.258 brouard 12234: /* Results */
12235: nresult=0;
12236: do{
12237: if(!fgets(line, MAXLINE, ficpar)){
12238: endishere=1;
12239: parameterline=14;
12240: }else if (line[0] == '#') {
12241: /* If line starts with a # it is a comment */
1.254 brouard 12242: numlinepar++;
12243: fputs(line,stdout);
12244: fputs(line,ficparo);
12245: fputs(line,ficlog);
12246: continue;
1.258 brouard 12247: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12248: parameterline=11;
12249: else if(sscanf(line,"backcast=%[^\n]\n",modeltemp))
12250: parameterline=12;
12251: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
12252: parameterline=13;
12253: else{
12254: parameterline=14;
1.254 brouard 12255: }
1.258 brouard 12256: switch (parameterline){
12257: case 11:
12258: 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){
12259: if (num_filled != 8) {
12260: 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\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
12261: 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 mov_average=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
12262: goto end;
12263: }
12264: 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);
12265: 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);
12266: 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);
12267: 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);
12268: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12269: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12270: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
12271:
1.258 brouard 12272: }
1.254 brouard 12273: break;
1.258 brouard 12274: case 12:
12275: /*fscanf(ficpar,"backcast=%d starting-back-date=%lf/%lf/%lf final-back-date=%lf/%lf/%lf mobil_average=%d\n",&backcast,&jback1,&mback1,&anback1,&jback2,&mback2,&anback2,&mobilavproj);*/
12276: if((num_filled=sscanf(line,"backcast=%d starting-back-date=%lf/%lf/%lf final-back-date=%lf/%lf/%lf mobil_average=%d\n",&backcast,&jback1,&mback1,&anback1,&jback2,&mback2,&anback2,&mobilavproj)) !=EOF){
12277: if (num_filled != 8) {
1.262 brouard 12278: printf("Error: Not 8 (data)parameters in line but %d, for example:backcast=1 starting-back-date=1/1/1990 final-back-date=1/1/1970 mobil_average=1\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
12279: fprintf(ficlog,"Error: Not 8 (data)parameters in line but %d, for example:backcast=1 starting-back-date=1/1/1990 final-back-date=1/1/1970 mobil_average=1\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
1.258 brouard 12280: goto end;
12281: }
12282: printf("backcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",backcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
12283: fprintf(ficparo,"backcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",backcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
12284: fprintf(ficlog,"backcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",backcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
12285: fprintf(ficres,"backcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",backcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
12286: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12287: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12288: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.258 brouard 12289: }
1.230 brouard 12290: break;
1.258 brouard 12291: case 13:
12292: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
12293: if (num_filled == 0){
12294: resultline[0]='\0';
12295: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12296: fprintf(ficlog,"Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12297: break;
12298: } else if (num_filled != 1){
12299: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12300: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12301: }
12302: nresult++; /* Sum of resultlines */
12303: printf("Result %d: result=%s\n",nresult, resultline);
12304: if(nresult > MAXRESULTLINES){
12305: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12306: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12307: goto end;
12308: }
12309: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
12310: fprintf(ficparo,"result: %s\n",resultline);
12311: fprintf(ficres,"result: %s\n",resultline);
12312: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 12313: break;
1.258 brouard 12314: case 14:
1.259 brouard 12315: if(ncovmodel >2 && nresult==0 ){
12316: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12317: goto end;
12318: }
1.259 brouard 12319: break;
1.258 brouard 12320: default:
12321: nresult=1;
12322: decoderesult(".",nresult ); /* No covariate */
12323: }
12324: } /* End switch parameterline */
12325: }while(endishere==0); /* End do */
1.126 brouard 12326:
1.230 brouard 12327: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12328: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12329:
12330: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12331: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12332: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12333: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12334: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12335: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12336: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12337: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12338: }else{
1.270 brouard 12339: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
12340: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, backcast, pathc,p, (int)anproj1-bage, (int)anback1-fage);
1.220 brouard 12341: }
12342: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.258 brouard 12343: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,backcast, estepm, \
1.273 brouard 12344: jprev1,mprev1,anprev1,dateprev1, dateproj1, dateback1,jprev2,mprev2,anprev2,dateprev2,dateproj2, dateback2);
1.220 brouard 12345:
1.225 brouard 12346: /*------------ free_vector -------------*/
12347: /* chdir(path); */
1.220 brouard 12348:
1.215 brouard 12349: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12350: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12351: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12352: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 ! brouard 12353: free_lvector(num,firstobs,lastobs);
! 12354: free_vector(agedc,firstobs,lastobs);
1.126 brouard 12355: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12356: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12357: fclose(ficparo);
12358: fclose(ficres);
1.220 brouard 12359:
12360:
1.186 brouard 12361: /* Other results (useful)*/
1.220 brouard 12362:
12363:
1.126 brouard 12364: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12365: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12366: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12367: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12368: fclose(ficrespl);
12369:
12370: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12371: /*#include "hpijx.h"*/
12372: hPijx(p, bage, fage);
1.145 brouard 12373: fclose(ficrespij);
1.227 brouard 12374:
1.220 brouard 12375: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12376: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12377: k=1;
1.126 brouard 12378: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12379:
1.269 brouard 12380: /* Prevalence for each covariate combination in probs[age][status][cov] */
12381: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12382: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12383: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12384: for(k=1;k<=ncovcombmax;k++)
12385: probs[i][j][k]=0.;
1.269 brouard 12386: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
12387: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12388: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 12389: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12390: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12391: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12392: for(k=1;k<=ncovcombmax;k++)
12393: mobaverages[i][j][k]=0.;
1.219 brouard 12394: mobaverage=mobaverages;
12395: if (mobilav!=0) {
1.235 brouard 12396: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12397: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12398: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12399: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12400: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12401: }
1.269 brouard 12402: } else if (mobilavproj !=0) {
1.235 brouard 12403: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12404: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12405: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12406: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12407: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12408: }
1.269 brouard 12409: }else{
12410: printf("Internal error moving average\n");
12411: fflush(stdout);
12412: exit(1);
1.219 brouard 12413: }
12414: }/* end if moving average */
1.227 brouard 12415:
1.126 brouard 12416: /*---------- Forecasting ------------------*/
12417: if(prevfcast==1){
12418: /* if(stepm ==1){*/
1.269 brouard 12419: prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
1.126 brouard 12420: }
1.269 brouard 12421:
12422: /* Backcasting */
1.217 brouard 12423: if(backcast==1){
1.219 brouard 12424: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12425: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12426: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12427:
12428: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12429:
12430: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 12431:
1.219 brouard 12432: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12433: fclose(ficresplb);
12434:
1.222 brouard 12435: hBijx(p, bage, fage, mobaverage);
12436: fclose(ficrespijb);
1.219 brouard 12437:
1.269 brouard 12438: prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2,
12439: mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff);
12440: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12441:
12442:
1.269 brouard 12443: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12444: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12445: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12446: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.269 brouard 12447: } /* end Backcasting */
1.268 brouard 12448:
1.186 brouard 12449:
12450: /* ------ Other prevalence ratios------------ */
1.126 brouard 12451:
1.215 brouard 12452: free_ivector(wav,1,imx);
12453: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12454: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12455: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12456:
12457:
1.127 brouard 12458: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12459:
1.201 brouard 12460: strcpy(filerese,"E_");
12461: strcat(filerese,fileresu);
1.126 brouard 12462: if((ficreseij=fopen(filerese,"w"))==NULL) {
12463: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12464: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12465: }
1.208 brouard 12466: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12467: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12468:
12469: pstamp(ficreseij);
1.219 brouard 12470:
1.235 brouard 12471: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12472: if (cptcovn < 1){i1=1;}
12473:
12474: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12475: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12476: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12477: continue;
1.219 brouard 12478: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12479: printf("\n#****** ");
1.225 brouard 12480: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12481: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12482: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12483: }
12484: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12485: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12486: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12487: }
12488: fprintf(ficreseij,"******\n");
1.235 brouard 12489: printf("******\n");
1.219 brouard 12490:
12491: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12492: oldm=oldms;savm=savms;
1.235 brouard 12493: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12494:
1.219 brouard 12495: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12496: }
12497: fclose(ficreseij);
1.208 brouard 12498: printf("done evsij\n");fflush(stdout);
12499: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 12500:
1.218 brouard 12501:
1.227 brouard 12502: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12503:
1.201 brouard 12504: strcpy(filerest,"T_");
12505: strcat(filerest,fileresu);
1.127 brouard 12506: if((ficrest=fopen(filerest,"w"))==NULL) {
12507: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12508: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12509: }
1.208 brouard 12510: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12511: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12512: strcpy(fileresstde,"STDE_");
12513: strcat(fileresstde,fileresu);
1.126 brouard 12514: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12515: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12516: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12517: }
1.227 brouard 12518: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12519: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12520:
1.201 brouard 12521: strcpy(filerescve,"CVE_");
12522: strcat(filerescve,fileresu);
1.126 brouard 12523: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12524: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12525: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12526: }
1.227 brouard 12527: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12528: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12529:
1.201 brouard 12530: strcpy(fileresv,"V_");
12531: strcat(fileresv,fileresu);
1.126 brouard 12532: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12533: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12534: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12535: }
1.227 brouard 12536: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12537: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12538:
1.235 brouard 12539: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12540: if (cptcovn < 1){i1=1;}
12541:
12542: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12543: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12544: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12545: continue;
1.242 brouard 12546: printf("\n#****** Result for:");
12547: fprintf(ficrest,"\n#****** Result for:");
12548: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12549: for(j=1;j<=cptcoveff;j++){
12550: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12551: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12552: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12553: }
1.235 brouard 12554: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12555: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12556: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12557: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12558: }
1.208 brouard 12559: fprintf(ficrest,"******\n");
1.227 brouard 12560: fprintf(ficlog,"******\n");
12561: printf("******\n");
1.208 brouard 12562:
12563: fprintf(ficresstdeij,"\n#****** ");
12564: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12565: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12566: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12567: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12568: }
1.235 brouard 12569: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12570: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12571: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12572: }
1.208 brouard 12573: fprintf(ficresstdeij,"******\n");
12574: fprintf(ficrescveij,"******\n");
12575:
12576: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12577: /* pstamp(ficresvij); */
1.225 brouard 12578: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12579: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12580: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12581: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12582: }
1.208 brouard 12583: fprintf(ficresvij,"******\n");
12584:
12585: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12586: oldm=oldms;savm=savms;
1.235 brouard 12587: printf(" cvevsij ");
12588: fprintf(ficlog, " cvevsij ");
12589: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12590: printf(" end cvevsij \n ");
12591: fprintf(ficlog, " end cvevsij \n ");
12592:
12593: /*
12594: */
12595: /* goto endfree; */
12596:
12597: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12598: pstamp(ficrest);
12599:
1.269 brouard 12600: epj=vector(1,nlstate+1);
1.208 brouard 12601: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12602: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12603: cptcod= 0; /* To be deleted */
12604: printf("varevsij vpopbased=%d \n",vpopbased);
12605: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12606: 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 12607: 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 ");
12608: if(vpopbased==1)
12609: 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);
12610: else
1.288 brouard 12611: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12612: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12613: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12614: fprintf(ficrest,"\n");
12615: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 12616: printf("Computing age specific forward period (stable) prevalences in each health state \n");
12617: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12618: for(age=bage; age <=fage ;age++){
1.235 brouard 12619: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12620: if (vpopbased==1) {
12621: if(mobilav ==0){
12622: for(i=1; i<=nlstate;i++)
12623: prlim[i][i]=probs[(int)age][i][k];
12624: }else{ /* mobilav */
12625: for(i=1; i<=nlstate;i++)
12626: prlim[i][i]=mobaverage[(int)age][i][k];
12627: }
12628: }
1.219 brouard 12629:
1.227 brouard 12630: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12631: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12632: /* printf(" age %4.0f ",age); */
12633: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12634: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12635: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12636: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12637: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12638: }
12639: epj[nlstate+1] +=epj[j];
12640: }
12641: /* printf(" age %4.0f \n",age); */
1.219 brouard 12642:
1.227 brouard 12643: for(i=1, vepp=0.;i <=nlstate;i++)
12644: for(j=1;j <=nlstate;j++)
12645: vepp += vareij[i][j][(int)age];
12646: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12647: for(j=1;j <=nlstate;j++){
12648: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12649: }
12650: fprintf(ficrest,"\n");
12651: }
1.208 brouard 12652: } /* End vpopbased */
1.269 brouard 12653: free_vector(epj,1,nlstate+1);
1.208 brouard 12654: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12655: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 12656: printf("done selection\n");fflush(stdout);
12657: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12658:
1.235 brouard 12659: } /* End k selection */
1.227 brouard 12660:
12661: printf("done State-specific expectancies\n");fflush(stdout);
12662: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12663:
1.288 brouard 12664: /* variance-covariance of forward period prevalence*/
1.269 brouard 12665: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12666:
1.227 brouard 12667:
1.290 ! brouard 12668: free_vector(weight,firstobs,lastobs);
1.227 brouard 12669: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 ! brouard 12670: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
! 12671: free_matrix(anint,1,maxwav,firstobs,lastobs);
! 12672: free_matrix(mint,1,maxwav,firstobs,lastobs);
! 12673: free_ivector(cod,firstobs,lastobs);
1.227 brouard 12674: free_ivector(tab,1,NCOVMAX);
12675: fclose(ficresstdeij);
12676: fclose(ficrescveij);
12677: fclose(ficresvij);
12678: fclose(ficrest);
12679: fclose(ficpar);
12680:
12681:
1.126 brouard 12682: /*---------- End : free ----------------*/
1.219 brouard 12683: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 12684: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
12685: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12686: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12687: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12688: } /* mle==-3 arrives here for freeing */
1.227 brouard 12689: /* endfree:*/
12690: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12691: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12692: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.290 ! brouard 12693: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
! 12694: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
! 12695: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
! 12696: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 12697: free_matrix(matcov,1,npar,1,npar);
12698: free_matrix(hess,1,npar,1,npar);
12699: /*free_vector(delti,1,npar);*/
12700: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12701: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 12702: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 12703: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12704:
12705: free_ivector(ncodemax,1,NCOVMAX);
12706: free_ivector(ncodemaxwundef,1,NCOVMAX);
12707: free_ivector(Dummy,-1,NCOVMAX);
12708: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 12709: free_ivector(DummyV,1,NCOVMAX);
12710: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 12711: free_ivector(Typevar,-1,NCOVMAX);
12712: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 12713: free_ivector(TvarsQ,1,NCOVMAX);
12714: free_ivector(TvarsQind,1,NCOVMAX);
12715: free_ivector(TvarsD,1,NCOVMAX);
12716: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 12717: free_ivector(TvarFD,1,NCOVMAX);
12718: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 12719: free_ivector(TvarF,1,NCOVMAX);
12720: free_ivector(TvarFind,1,NCOVMAX);
12721: free_ivector(TvarV,1,NCOVMAX);
12722: free_ivector(TvarVind,1,NCOVMAX);
12723: free_ivector(TvarA,1,NCOVMAX);
12724: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 12725: free_ivector(TvarFQ,1,NCOVMAX);
12726: free_ivector(TvarFQind,1,NCOVMAX);
12727: free_ivector(TvarVD,1,NCOVMAX);
12728: free_ivector(TvarVDind,1,NCOVMAX);
12729: free_ivector(TvarVQ,1,NCOVMAX);
12730: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 12731: free_ivector(Tvarsel,1,NCOVMAX);
12732: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 12733: free_ivector(Tposprod,1,NCOVMAX);
12734: free_ivector(Tprod,1,NCOVMAX);
12735: free_ivector(Tvaraff,1,NCOVMAX);
12736: free_ivector(invalidvarcomb,1,ncovcombmax);
12737: free_ivector(Tage,1,NCOVMAX);
12738: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 12739: free_ivector(TmodelInvind,1,NCOVMAX);
12740: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 12741:
12742: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
12743: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 12744: fflush(fichtm);
12745: fflush(ficgp);
12746:
1.227 brouard 12747:
1.126 brouard 12748: if((nberr >0) || (nbwarn>0)){
1.216 brouard 12749: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
12750: 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 12751: }else{
12752: printf("End of Imach\n");
12753: fprintf(ficlog,"End of Imach\n");
12754: }
12755: printf("See log file on %s\n",filelog);
12756: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 12757: /*(void) gettimeofday(&end_time,&tzp);*/
12758: rend_time = time(NULL);
12759: end_time = *localtime(&rend_time);
12760: /* tml = *localtime(&end_time.tm_sec); */
12761: strcpy(strtend,asctime(&end_time));
1.126 brouard 12762: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
12763: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 12764: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 12765:
1.157 brouard 12766: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
12767: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
12768: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 12769: /* printf("Total time was %d uSec.\n", total_usecs);*/
12770: /* if(fileappend(fichtm,optionfilehtm)){ */
12771: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12772: fclose(fichtm);
12773: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12774: fclose(fichtmcov);
12775: fclose(ficgp);
12776: fclose(ficlog);
12777: /*------ End -----------*/
1.227 brouard 12778:
1.281 brouard 12779:
12780: /* Executes gnuplot */
1.227 brouard 12781:
12782: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 12783: #ifdef WIN32
1.227 brouard 12784: if (_chdir(pathcd) != 0)
12785: printf("Can't move to directory %s!\n",path);
12786: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 12787: #else
1.227 brouard 12788: if(chdir(pathcd) != 0)
12789: printf("Can't move to directory %s!\n", path);
12790: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 12791: #endif
1.126 brouard 12792: printf("Current directory %s!\n",pathcd);
12793: /*strcat(plotcmd,CHARSEPARATOR);*/
12794: sprintf(plotcmd,"gnuplot");
1.157 brouard 12795: #ifdef _WIN32
1.126 brouard 12796: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
12797: #endif
12798: if(!stat(plotcmd,&info)){
1.158 brouard 12799: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12800: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 12801: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 12802: }else
12803: strcpy(pplotcmd,plotcmd);
1.157 brouard 12804: #ifdef __unix
1.126 brouard 12805: strcpy(plotcmd,GNUPLOTPROGRAM);
12806: if(!stat(plotcmd,&info)){
1.158 brouard 12807: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12808: }else
12809: strcpy(pplotcmd,plotcmd);
12810: #endif
12811: }else
12812: strcpy(pplotcmd,plotcmd);
12813:
12814: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 12815: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.227 brouard 12816:
1.126 brouard 12817: if((outcmd=system(plotcmd)) != 0){
1.158 brouard 12818: printf("gnuplot command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 12819: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 12820: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.150 brouard 12821: if((outcmd=system(plotcmd)) != 0)
1.153 brouard 12822: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.126 brouard 12823: }
1.158 brouard 12824: printf(" Successful, please wait...");
1.126 brouard 12825: while (z[0] != 'q') {
12826: /* chdir(path); */
1.154 brouard 12827: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 12828: scanf("%s",z);
12829: /* if (z[0] == 'c') system("./imach"); */
12830: if (z[0] == 'e') {
1.158 brouard 12831: #ifdef __APPLE__
1.152 brouard 12832: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 12833: #elif __linux
12834: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 12835: #else
1.152 brouard 12836: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 12837: #endif
12838: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
12839: system(pplotcmd);
1.126 brouard 12840: }
12841: else if (z[0] == 'g') system(plotcmd);
12842: else if (z[0] == 'q') exit(0);
12843: }
1.227 brouard 12844: end:
1.126 brouard 12845: while (z[0] != 'q') {
1.195 brouard 12846: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 12847: scanf("%s",z);
12848: }
1.283 brouard 12849: printf("End\n");
1.282 brouard 12850: exit(0);
1.126 brouard 12851: }
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