Annotation of imach/src/imach.c, revision 1.289
1.289 ! brouard 1: /* $Id: imach.c,v 1.288 2018/05/02 20:58:27 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.289 ! brouard 4: Revision 1.288 2018/05/02 20:58:27 brouard
! 5: Summary: Some bugs fixed
! 6:
1.288 brouard 7: Revision 1.287 2018/05/01 17:57:25 brouard
8: Summary: Bug fixed by providing frequencies only for non missing covariates
9:
1.287 brouard 10: Revision 1.286 2018/04/27 14:27:04 brouard
11: Summary: some minor bugs
12:
1.286 brouard 13: Revision 1.285 2018/04/21 21:02:16 brouard
14: Summary: Some bugs fixed, valgrind tested
15:
1.285 brouard 16: Revision 1.284 2018/04/20 05:22:13 brouard
17: Summary: Computing mean and stdeviation of fixed quantitative variables
18:
1.284 brouard 19: Revision 1.283 2018/04/19 14:49:16 brouard
20: Summary: Some minor bugs fixed
21:
1.283 brouard 22: Revision 1.282 2018/02/27 22:50:02 brouard
23: *** empty log message ***
24:
1.282 brouard 25: Revision 1.281 2018/02/27 19:25:23 brouard
26: Summary: Adding second argument for quitting
27:
1.281 brouard 28: Revision 1.280 2018/02/21 07:58:13 brouard
29: Summary: 0.99r15
30:
31: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
32:
1.280 brouard 33: Revision 1.279 2017/07/20 13:35:01 brouard
34: Summary: temporary working
35:
1.279 brouard 36: Revision 1.278 2017/07/19 14:09:02 brouard
37: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
38:
1.278 brouard 39: Revision 1.277 2017/07/17 08:53:49 brouard
40: Summary: BOM files can be read now
41:
1.277 brouard 42: Revision 1.276 2017/06/30 15:48:31 brouard
43: Summary: Graphs improvements
44:
1.276 brouard 45: Revision 1.275 2017/06/30 13:39:33 brouard
46: Summary: Saito's color
47:
1.275 brouard 48: Revision 1.274 2017/06/29 09:47:08 brouard
49: Summary: Version 0.99r14
50:
1.274 brouard 51: Revision 1.273 2017/06/27 11:06:02 brouard
52: Summary: More documentation on projections
53:
1.273 brouard 54: Revision 1.272 2017/06/27 10:22:40 brouard
55: Summary: Color of backprojection changed from 6 to 5(yellow)
56:
1.272 brouard 57: Revision 1.271 2017/06/27 10:17:50 brouard
58: Summary: Some bug with rint
59:
1.271 brouard 60: Revision 1.270 2017/05/24 05:45:29 brouard
61: *** empty log message ***
62:
1.270 brouard 63: Revision 1.269 2017/05/23 08:39:25 brouard
64: Summary: Code into subroutine, cleanings
65:
1.269 brouard 66: Revision 1.268 2017/05/18 20:09:32 brouard
67: Summary: backprojection and confidence intervals of backprevalence
68:
1.268 brouard 69: Revision 1.267 2017/05/13 10:25:05 brouard
70: Summary: temporary save for backprojection
71:
1.267 brouard 72: Revision 1.266 2017/05/13 07:26:12 brouard
73: Summary: Version 0.99r13 (improvements and bugs fixed)
74:
1.266 brouard 75: Revision 1.265 2017/04/26 16:22:11 brouard
76: Summary: imach 0.99r13 Some bugs fixed
77:
1.265 brouard 78: Revision 1.264 2017/04/26 06:01:29 brouard
79: Summary: Labels in graphs
80:
1.264 brouard 81: Revision 1.263 2017/04/24 15:23:15 brouard
82: Summary: to save
83:
1.263 brouard 84: Revision 1.262 2017/04/18 16:48:12 brouard
85: *** empty log message ***
86:
1.262 brouard 87: Revision 1.261 2017/04/05 10:14:09 brouard
88: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
89:
1.261 brouard 90: Revision 1.260 2017/04/04 17:46:59 brouard
91: Summary: Gnuplot indexations fixed (humm)
92:
1.260 brouard 93: Revision 1.259 2017/04/04 13:01:16 brouard
94: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
95:
1.259 brouard 96: Revision 1.258 2017/04/03 10:17:47 brouard
97: Summary: Version 0.99r12
98:
99: Some cleanings, conformed with updated documentation.
100:
1.258 brouard 101: Revision 1.257 2017/03/29 16:53:30 brouard
102: Summary: Temp
103:
1.257 brouard 104: Revision 1.256 2017/03/27 05:50:23 brouard
105: Summary: Temporary
106:
1.256 brouard 107: Revision 1.255 2017/03/08 16:02:28 brouard
108: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
109:
1.255 brouard 110: Revision 1.254 2017/03/08 07:13:00 brouard
111: Summary: Fixing data parameter line
112:
1.254 brouard 113: Revision 1.253 2016/12/15 11:59:41 brouard
114: Summary: 0.99 in progress
115:
1.253 brouard 116: Revision 1.252 2016/09/15 21:15:37 brouard
117: *** empty log message ***
118:
1.252 brouard 119: Revision 1.251 2016/09/15 15:01:13 brouard
120: Summary: not working
121:
1.251 brouard 122: Revision 1.250 2016/09/08 16:07:27 brouard
123: Summary: continue
124:
1.250 brouard 125: Revision 1.249 2016/09/07 17:14:18 brouard
126: Summary: Starting values from frequencies
127:
1.249 brouard 128: Revision 1.248 2016/09/07 14:10:18 brouard
129: *** empty log message ***
130:
1.248 brouard 131: Revision 1.247 2016/09/02 11:11:21 brouard
132: *** empty log message ***
133:
1.247 brouard 134: Revision 1.246 2016/09/02 08:49:22 brouard
135: *** empty log message ***
136:
1.246 brouard 137: Revision 1.245 2016/09/02 07:25:01 brouard
138: *** empty log message ***
139:
1.245 brouard 140: Revision 1.244 2016/09/02 07:17:34 brouard
141: *** empty log message ***
142:
1.244 brouard 143: Revision 1.243 2016/09/02 06:45:35 brouard
144: *** empty log message ***
145:
1.243 brouard 146: Revision 1.242 2016/08/30 15:01:20 brouard
147: Summary: Fixing a lots
148:
1.242 brouard 149: Revision 1.241 2016/08/29 17:17:25 brouard
150: Summary: gnuplot problem in Back projection to fix
151:
1.241 brouard 152: Revision 1.240 2016/08/29 07:53:18 brouard
153: Summary: Better
154:
1.240 brouard 155: Revision 1.239 2016/08/26 15:51:03 brouard
156: Summary: Improvement in Powell output in order to copy and paste
157:
158: Author:
159:
1.239 brouard 160: Revision 1.238 2016/08/26 14:23:35 brouard
161: Summary: Starting tests of 0.99
162:
1.238 brouard 163: Revision 1.237 2016/08/26 09:20:19 brouard
164: Summary: to valgrind
165:
1.237 brouard 166: Revision 1.236 2016/08/25 10:50:18 brouard
167: *** empty log message ***
168:
1.236 brouard 169: Revision 1.235 2016/08/25 06:59:23 brouard
170: *** empty log message ***
171:
1.235 brouard 172: Revision 1.234 2016/08/23 16:51:20 brouard
173: *** empty log message ***
174:
1.234 brouard 175: Revision 1.233 2016/08/23 07:40:50 brouard
176: Summary: not working
177:
1.233 brouard 178: Revision 1.232 2016/08/22 14:20:21 brouard
179: Summary: not working
180:
1.232 brouard 181: Revision 1.231 2016/08/22 07:17:15 brouard
182: Summary: not working
183:
1.231 brouard 184: Revision 1.230 2016/08/22 06:55:53 brouard
185: Summary: Not working
186:
1.230 brouard 187: Revision 1.229 2016/07/23 09:45:53 brouard
188: Summary: Completing for func too
189:
1.229 brouard 190: Revision 1.228 2016/07/22 17:45:30 brouard
191: Summary: Fixing some arrays, still debugging
192:
1.227 brouard 193: Revision 1.226 2016/07/12 18:42:34 brouard
194: Summary: temp
195:
1.226 brouard 196: Revision 1.225 2016/07/12 08:40:03 brouard
197: Summary: saving but not running
198:
1.225 brouard 199: Revision 1.224 2016/07/01 13:16:01 brouard
200: Summary: Fixes
201:
1.224 brouard 202: Revision 1.223 2016/02/19 09:23:35 brouard
203: Summary: temporary
204:
1.223 brouard 205: Revision 1.222 2016/02/17 08:14:50 brouard
206: Summary: Probably last 0.98 stable version 0.98r6
207:
1.222 brouard 208: Revision 1.221 2016/02/15 23:35:36 brouard
209: Summary: minor bug
210:
1.220 brouard 211: Revision 1.219 2016/02/15 00:48:12 brouard
212: *** empty log message ***
213:
1.219 brouard 214: Revision 1.218 2016/02/12 11:29:23 brouard
215: Summary: 0.99 Back projections
216:
1.218 brouard 217: Revision 1.217 2015/12/23 17:18:31 brouard
218: Summary: Experimental backcast
219:
1.217 brouard 220: Revision 1.216 2015/12/18 17:32:11 brouard
221: Summary: 0.98r4 Warning and status=-2
222:
223: Version 0.98r4 is now:
224: - displaying an error when status is -1, date of interview unknown and date of death known;
225: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
226: Older changes concerning s=-2, dating from 2005 have been supersed.
227:
1.216 brouard 228: Revision 1.215 2015/12/16 08:52:24 brouard
229: Summary: 0.98r4 working
230:
1.215 brouard 231: Revision 1.214 2015/12/16 06:57:54 brouard
232: Summary: temporary not working
233:
1.214 brouard 234: Revision 1.213 2015/12/11 18:22:17 brouard
235: Summary: 0.98r4
236:
1.213 brouard 237: Revision 1.212 2015/11/21 12:47:24 brouard
238: Summary: minor typo
239:
1.212 brouard 240: Revision 1.211 2015/11/21 12:41:11 brouard
241: Summary: 0.98r3 with some graph of projected cross-sectional
242:
243: Author: Nicolas Brouard
244:
1.211 brouard 245: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 246: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 247: Summary: Adding ftolpl parameter
248: Author: N Brouard
249:
250: We had difficulties to get smoothed confidence intervals. It was due
251: to the period prevalence which wasn't computed accurately. The inner
252: parameter ftolpl is now an outer parameter of the .imach parameter
253: file after estepm. If ftolpl is small 1.e-4 and estepm too,
254: computation are long.
255:
1.209 brouard 256: Revision 1.208 2015/11/17 14:31:57 brouard
257: Summary: temporary
258:
1.208 brouard 259: Revision 1.207 2015/10/27 17:36:57 brouard
260: *** empty log message ***
261:
1.207 brouard 262: Revision 1.206 2015/10/24 07:14:11 brouard
263: *** empty log message ***
264:
1.206 brouard 265: Revision 1.205 2015/10/23 15:50:53 brouard
266: Summary: 0.98r3 some clarification for graphs on likelihood contributions
267:
1.205 brouard 268: Revision 1.204 2015/10/01 16:20:26 brouard
269: Summary: Some new graphs of contribution to likelihood
270:
1.204 brouard 271: Revision 1.203 2015/09/30 17:45:14 brouard
272: Summary: looking at better estimation of the hessian
273:
274: Also a better criteria for convergence to the period prevalence And
275: therefore adding the number of years needed to converge. (The
276: prevalence in any alive state shold sum to one
277:
1.203 brouard 278: Revision 1.202 2015/09/22 19:45:16 brouard
279: Summary: Adding some overall graph on contribution to likelihood. Might change
280:
1.202 brouard 281: Revision 1.201 2015/09/15 17:34:58 brouard
282: Summary: 0.98r0
283:
284: - Some new graphs like suvival functions
285: - Some bugs fixed like model=1+age+V2.
286:
1.201 brouard 287: Revision 1.200 2015/09/09 16:53:55 brouard
288: Summary: Big bug thanks to Flavia
289:
290: Even model=1+age+V2. did not work anymore
291:
1.200 brouard 292: Revision 1.199 2015/09/07 14:09:23 brouard
293: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
294:
1.199 brouard 295: Revision 1.198 2015/09/03 07:14:39 brouard
296: Summary: 0.98q5 Flavia
297:
1.198 brouard 298: Revision 1.197 2015/09/01 18:24:39 brouard
299: *** empty log message ***
300:
1.197 brouard 301: Revision 1.196 2015/08/18 23:17:52 brouard
302: Summary: 0.98q5
303:
1.196 brouard 304: Revision 1.195 2015/08/18 16:28:39 brouard
305: Summary: Adding a hack for testing purpose
306:
307: After reading the title, ftol and model lines, if the comment line has
308: a q, starting with #q, the answer at the end of the run is quit. It
309: permits to run test files in batch with ctest. The former workaround was
310: $ echo q | imach foo.imach
311:
1.195 brouard 312: Revision 1.194 2015/08/18 13:32:00 brouard
313: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
314:
1.194 brouard 315: Revision 1.193 2015/08/04 07:17:42 brouard
316: Summary: 0.98q4
317:
1.193 brouard 318: Revision 1.192 2015/07/16 16:49:02 brouard
319: Summary: Fixing some outputs
320:
1.192 brouard 321: Revision 1.191 2015/07/14 10:00:33 brouard
322: Summary: Some fixes
323:
1.191 brouard 324: Revision 1.190 2015/05/05 08:51:13 brouard
325: Summary: Adding digits in output parameters (7 digits instead of 6)
326:
327: Fix 1+age+.
328:
1.190 brouard 329: Revision 1.189 2015/04/30 14:45:16 brouard
330: Summary: 0.98q2
331:
1.189 brouard 332: Revision 1.188 2015/04/30 08:27:53 brouard
333: *** empty log message ***
334:
1.188 brouard 335: Revision 1.187 2015/04/29 09:11:15 brouard
336: *** empty log message ***
337:
1.187 brouard 338: Revision 1.186 2015/04/23 12:01:52 brouard
339: Summary: V1*age is working now, version 0.98q1
340:
341: Some codes had been disabled in order to simplify and Vn*age was
342: working in the optimization phase, ie, giving correct MLE parameters,
343: but, as usual, outputs were not correct and program core dumped.
344:
1.186 brouard 345: Revision 1.185 2015/03/11 13:26:42 brouard
346: Summary: Inclusion of compile and links command line for Intel Compiler
347:
1.185 brouard 348: Revision 1.184 2015/03/11 11:52:39 brouard
349: Summary: Back from Windows 8. Intel Compiler
350:
1.184 brouard 351: Revision 1.183 2015/03/10 20:34:32 brouard
352: Summary: 0.98q0, trying with directest, mnbrak fixed
353:
354: We use directest instead of original Powell test; probably no
355: incidence on the results, but better justifications;
356: We fixed Numerical Recipes mnbrak routine which was wrong and gave
357: wrong results.
358:
1.183 brouard 359: Revision 1.182 2015/02/12 08:19:57 brouard
360: Summary: Trying to keep directest which seems simpler and more general
361: Author: Nicolas Brouard
362:
1.182 brouard 363: Revision 1.181 2015/02/11 23:22:24 brouard
364: Summary: Comments on Powell added
365:
366: Author:
367:
1.181 brouard 368: Revision 1.180 2015/02/11 17:33:45 brouard
369: Summary: Finishing move from main to function (hpijx and prevalence_limit)
370:
1.180 brouard 371: Revision 1.179 2015/01/04 09:57:06 brouard
372: Summary: back to OS/X
373:
1.179 brouard 374: Revision 1.178 2015/01/04 09:35:48 brouard
375: *** empty log message ***
376:
1.178 brouard 377: Revision 1.177 2015/01/03 18:40:56 brouard
378: Summary: Still testing ilc32 on OSX
379:
1.177 brouard 380: Revision 1.176 2015/01/03 16:45:04 brouard
381: *** empty log message ***
382:
1.176 brouard 383: Revision 1.175 2015/01/03 16:33:42 brouard
384: *** empty log message ***
385:
1.175 brouard 386: Revision 1.174 2015/01/03 16:15:49 brouard
387: Summary: Still in cross-compilation
388:
1.174 brouard 389: Revision 1.173 2015/01/03 12:06:26 brouard
390: Summary: trying to detect cross-compilation
391:
1.173 brouard 392: Revision 1.172 2014/12/27 12:07:47 brouard
393: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
394:
1.172 brouard 395: Revision 1.171 2014/12/23 13:26:59 brouard
396: Summary: Back from Visual C
397:
398: Still problem with utsname.h on Windows
399:
1.171 brouard 400: Revision 1.170 2014/12/23 11:17:12 brouard
401: Summary: Cleaning some \%% back to %%
402:
403: The escape was mandatory for a specific compiler (which one?), but too many warnings.
404:
1.170 brouard 405: Revision 1.169 2014/12/22 23:08:31 brouard
406: Summary: 0.98p
407:
408: Outputs some informations on compiler used, OS etc. Testing on different platforms.
409:
1.169 brouard 410: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 411: Summary: update
1.169 brouard 412:
1.168 brouard 413: Revision 1.167 2014/12/22 13:50:56 brouard
414: Summary: Testing uname and compiler version and if compiled 32 or 64
415:
416: Testing on Linux 64
417:
1.167 brouard 418: Revision 1.166 2014/12/22 11:40:47 brouard
419: *** empty log message ***
420:
1.166 brouard 421: Revision 1.165 2014/12/16 11:20:36 brouard
422: Summary: After compiling on Visual C
423:
424: * imach.c (Module): Merging 1.61 to 1.162
425:
1.165 brouard 426: Revision 1.164 2014/12/16 10:52:11 brouard
427: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
428:
429: * imach.c (Module): Merging 1.61 to 1.162
430:
1.164 brouard 431: Revision 1.163 2014/12/16 10:30:11 brouard
432: * imach.c (Module): Merging 1.61 to 1.162
433:
1.163 brouard 434: Revision 1.162 2014/09/25 11:43:39 brouard
435: Summary: temporary backup 0.99!
436:
1.162 brouard 437: Revision 1.1 2014/09/16 11:06:58 brouard
438: Summary: With some code (wrong) for nlopt
439:
440: Author:
441:
442: Revision 1.161 2014/09/15 20:41:41 brouard
443: Summary: Problem with macro SQR on Intel compiler
444:
1.161 brouard 445: Revision 1.160 2014/09/02 09:24:05 brouard
446: *** empty log message ***
447:
1.160 brouard 448: Revision 1.159 2014/09/01 10:34:10 brouard
449: Summary: WIN32
450: Author: Brouard
451:
1.159 brouard 452: Revision 1.158 2014/08/27 17:11:51 brouard
453: *** empty log message ***
454:
1.158 brouard 455: Revision 1.157 2014/08/27 16:26:55 brouard
456: Summary: Preparing windows Visual studio version
457: Author: Brouard
458:
459: In order to compile on Visual studio, time.h is now correct and time_t
460: and tm struct should be used. difftime should be used but sometimes I
461: just make the differences in raw time format (time(&now).
462: Trying to suppress #ifdef LINUX
463: Add xdg-open for __linux in order to open default browser.
464:
1.157 brouard 465: Revision 1.156 2014/08/25 20:10:10 brouard
466: *** empty log message ***
467:
1.156 brouard 468: Revision 1.155 2014/08/25 18:32:34 brouard
469: Summary: New compile, minor changes
470: Author: Brouard
471:
1.155 brouard 472: Revision 1.154 2014/06/20 17:32:08 brouard
473: Summary: Outputs now all graphs of convergence to period prevalence
474:
1.154 brouard 475: Revision 1.153 2014/06/20 16:45:46 brouard
476: Summary: If 3 live state, convergence to period prevalence on same graph
477: Author: Brouard
478:
1.153 brouard 479: Revision 1.152 2014/06/18 17:54:09 brouard
480: Summary: open browser, use gnuplot on same dir than imach if not found in the path
481:
1.152 brouard 482: Revision 1.151 2014/06/18 16:43:30 brouard
483: *** empty log message ***
484:
1.151 brouard 485: Revision 1.150 2014/06/18 16:42:35 brouard
486: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
487: Author: brouard
488:
1.150 brouard 489: Revision 1.149 2014/06/18 15:51:14 brouard
490: Summary: Some fixes in parameter files errors
491: Author: Nicolas Brouard
492:
1.149 brouard 493: Revision 1.148 2014/06/17 17:38:48 brouard
494: Summary: Nothing new
495: Author: Brouard
496:
497: Just a new packaging for OS/X version 0.98nS
498:
1.148 brouard 499: Revision 1.147 2014/06/16 10:33:11 brouard
500: *** empty log message ***
501:
1.147 brouard 502: Revision 1.146 2014/06/16 10:20:28 brouard
503: Summary: Merge
504: Author: Brouard
505:
506: Merge, before building revised version.
507:
1.146 brouard 508: Revision 1.145 2014/06/10 21:23:15 brouard
509: Summary: Debugging with valgrind
510: Author: Nicolas Brouard
511:
512: Lot of changes in order to output the results with some covariates
513: After the Edimburgh REVES conference 2014, it seems mandatory to
514: improve the code.
515: No more memory valgrind error but a lot has to be done in order to
516: continue the work of splitting the code into subroutines.
517: Also, decodemodel has been improved. Tricode is still not
518: optimal. nbcode should be improved. Documentation has been added in
519: the source code.
520:
1.144 brouard 521: Revision 1.143 2014/01/26 09:45:38 brouard
522: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
523:
524: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
525: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
526:
1.143 brouard 527: Revision 1.142 2014/01/26 03:57:36 brouard
528: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
529:
530: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
531:
1.142 brouard 532: Revision 1.141 2014/01/26 02:42:01 brouard
533: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
534:
1.141 brouard 535: Revision 1.140 2011/09/02 10:37:54 brouard
536: Summary: times.h is ok with mingw32 now.
537:
1.140 brouard 538: Revision 1.139 2010/06/14 07:50:17 brouard
539: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
540: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
541:
1.139 brouard 542: Revision 1.138 2010/04/30 18:19:40 brouard
543: *** empty log message ***
544:
1.138 brouard 545: Revision 1.137 2010/04/29 18:11:38 brouard
546: (Module): Checking covariates for more complex models
547: than V1+V2. A lot of change to be done. Unstable.
548:
1.137 brouard 549: Revision 1.136 2010/04/26 20:30:53 brouard
550: (Module): merging some libgsl code. Fixing computation
551: of likelione (using inter/intrapolation if mle = 0) in order to
552: get same likelihood as if mle=1.
553: Some cleaning of code and comments added.
554:
1.136 brouard 555: Revision 1.135 2009/10/29 15:33:14 brouard
556: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
557:
1.135 brouard 558: Revision 1.134 2009/10/29 13:18:53 brouard
559: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
560:
1.134 brouard 561: Revision 1.133 2009/07/06 10:21:25 brouard
562: just nforces
563:
1.133 brouard 564: Revision 1.132 2009/07/06 08:22:05 brouard
565: Many tings
566:
1.132 brouard 567: Revision 1.131 2009/06/20 16:22:47 brouard
568: Some dimensions resccaled
569:
1.131 brouard 570: Revision 1.130 2009/05/26 06:44:34 brouard
571: (Module): Max Covariate is now set to 20 instead of 8. A
572: lot of cleaning with variables initialized to 0. Trying to make
573: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
574:
1.130 brouard 575: Revision 1.129 2007/08/31 13:49:27 lievre
576: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
577:
1.129 lievre 578: Revision 1.128 2006/06/30 13:02:05 brouard
579: (Module): Clarifications on computing e.j
580:
1.128 brouard 581: Revision 1.127 2006/04/28 18:11:50 brouard
582: (Module): Yes the sum of survivors was wrong since
583: imach-114 because nhstepm was no more computed in the age
584: loop. Now we define nhstepma in the age loop.
585: (Module): In order to speed up (in case of numerous covariates) we
586: compute health expectancies (without variances) in a first step
587: and then all the health expectancies with variances or standard
588: deviation (needs data from the Hessian matrices) which slows the
589: computation.
590: In the future we should be able to stop the program is only health
591: expectancies and graph are needed without standard deviations.
592:
1.127 brouard 593: Revision 1.126 2006/04/28 17:23:28 brouard
594: (Module): Yes the sum of survivors was wrong since
595: imach-114 because nhstepm was no more computed in the age
596: loop. Now we define nhstepma in the age loop.
597: Version 0.98h
598:
1.126 brouard 599: Revision 1.125 2006/04/04 15:20:31 lievre
600: Errors in calculation of health expectancies. Age was not initialized.
601: Forecasting file added.
602:
603: Revision 1.124 2006/03/22 17:13:53 lievre
604: Parameters are printed with %lf instead of %f (more numbers after the comma).
605: The log-likelihood is printed in the log file
606:
607: Revision 1.123 2006/03/20 10:52:43 brouard
608: * imach.c (Module): <title> changed, corresponds to .htm file
609: name. <head> headers where missing.
610:
611: * imach.c (Module): Weights can have a decimal point as for
612: English (a comma might work with a correct LC_NUMERIC environment,
613: otherwise the weight is truncated).
614: Modification of warning when the covariates values are not 0 or
615: 1.
616: Version 0.98g
617:
618: Revision 1.122 2006/03/20 09:45:41 brouard
619: (Module): Weights can have a decimal point as for
620: English (a comma might work with a correct LC_NUMERIC environment,
621: otherwise the weight is truncated).
622: Modification of warning when the covariates values are not 0 or
623: 1.
624: Version 0.98g
625:
626: Revision 1.121 2006/03/16 17:45:01 lievre
627: * imach.c (Module): Comments concerning covariates added
628:
629: * imach.c (Module): refinements in the computation of lli if
630: status=-2 in order to have more reliable computation if stepm is
631: not 1 month. Version 0.98f
632:
633: Revision 1.120 2006/03/16 15:10:38 lievre
634: (Module): refinements in the computation of lli if
635: status=-2 in order to have more reliable computation if stepm is
636: not 1 month. Version 0.98f
637:
638: Revision 1.119 2006/03/15 17:42:26 brouard
639: (Module): Bug if status = -2, the loglikelihood was
640: computed as likelihood omitting the logarithm. Version O.98e
641:
642: Revision 1.118 2006/03/14 18:20:07 brouard
643: (Module): varevsij Comments added explaining the second
644: table of variances if popbased=1 .
645: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
646: (Module): Function pstamp added
647: (Module): Version 0.98d
648:
649: Revision 1.117 2006/03/14 17:16:22 brouard
650: (Module): varevsij Comments added explaining the second
651: table of variances if popbased=1 .
652: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
653: (Module): Function pstamp added
654: (Module): Version 0.98d
655:
656: Revision 1.116 2006/03/06 10:29:27 brouard
657: (Module): Variance-covariance wrong links and
658: varian-covariance of ej. is needed (Saito).
659:
660: Revision 1.115 2006/02/27 12:17:45 brouard
661: (Module): One freematrix added in mlikeli! 0.98c
662:
663: Revision 1.114 2006/02/26 12:57:58 brouard
664: (Module): Some improvements in processing parameter
665: filename with strsep.
666:
667: Revision 1.113 2006/02/24 14:20:24 brouard
668: (Module): Memory leaks checks with valgrind and:
669: datafile was not closed, some imatrix were not freed and on matrix
670: allocation too.
671:
672: Revision 1.112 2006/01/30 09:55:26 brouard
673: (Module): Back to gnuplot.exe instead of wgnuplot.exe
674:
675: Revision 1.111 2006/01/25 20:38:18 brouard
676: (Module): Lots of cleaning and bugs added (Gompertz)
677: (Module): Comments can be added in data file. Missing date values
678: can be a simple dot '.'.
679:
680: Revision 1.110 2006/01/25 00:51:50 brouard
681: (Module): Lots of cleaning and bugs added (Gompertz)
682:
683: Revision 1.109 2006/01/24 19:37:15 brouard
684: (Module): Comments (lines starting with a #) are allowed in data.
685:
686: Revision 1.108 2006/01/19 18:05:42 lievre
687: Gnuplot problem appeared...
688: To be fixed
689:
690: Revision 1.107 2006/01/19 16:20:37 brouard
691: Test existence of gnuplot in imach path
692:
693: Revision 1.106 2006/01/19 13:24:36 brouard
694: Some cleaning and links added in html output
695:
696: Revision 1.105 2006/01/05 20:23:19 lievre
697: *** empty log message ***
698:
699: Revision 1.104 2005/09/30 16:11:43 lievre
700: (Module): sump fixed, loop imx fixed, and simplifications.
701: (Module): If the status is missing at the last wave but we know
702: that the person is alive, then we can code his/her status as -2
703: (instead of missing=-1 in earlier versions) and his/her
704: contributions to the likelihood is 1 - Prob of dying from last
705: health status (= 1-p13= p11+p12 in the easiest case of somebody in
706: the healthy state at last known wave). Version is 0.98
707:
708: Revision 1.103 2005/09/30 15:54:49 lievre
709: (Module): sump fixed, loop imx fixed, and simplifications.
710:
711: Revision 1.102 2004/09/15 17:31:30 brouard
712: Add the possibility to read data file including tab characters.
713:
714: Revision 1.101 2004/09/15 10:38:38 brouard
715: Fix on curr_time
716:
717: Revision 1.100 2004/07/12 18:29:06 brouard
718: Add version for Mac OS X. Just define UNIX in Makefile
719:
720: Revision 1.99 2004/06/05 08:57:40 brouard
721: *** empty log message ***
722:
723: Revision 1.98 2004/05/16 15:05:56 brouard
724: New version 0.97 . First attempt to estimate force of mortality
725: directly from the data i.e. without the need of knowing the health
726: state at each age, but using a Gompertz model: log u =a + b*age .
727: This is the basic analysis of mortality and should be done before any
728: other analysis, in order to test if the mortality estimated from the
729: cross-longitudinal survey is different from the mortality estimated
730: from other sources like vital statistic data.
731:
732: The same imach parameter file can be used but the option for mle should be -3.
733:
1.133 brouard 734: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 735: former routines in order to include the new code within the former code.
736:
737: The output is very simple: only an estimate of the intercept and of
738: the slope with 95% confident intervals.
739:
740: Current limitations:
741: A) Even if you enter covariates, i.e. with the
742: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
743: B) There is no computation of Life Expectancy nor Life Table.
744:
745: Revision 1.97 2004/02/20 13:25:42 lievre
746: Version 0.96d. Population forecasting command line is (temporarily)
747: suppressed.
748:
749: Revision 1.96 2003/07/15 15:38:55 brouard
750: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
751: rewritten within the same printf. Workaround: many printfs.
752:
753: Revision 1.95 2003/07/08 07:54:34 brouard
754: * imach.c (Repository):
755: (Repository): Using imachwizard code to output a more meaningful covariance
756: matrix (cov(a12,c31) instead of numbers.
757:
758: Revision 1.94 2003/06/27 13:00:02 brouard
759: Just cleaning
760:
761: Revision 1.93 2003/06/25 16:33:55 brouard
762: (Module): On windows (cygwin) function asctime_r doesn't
763: exist so I changed back to asctime which exists.
764: (Module): Version 0.96b
765:
766: Revision 1.92 2003/06/25 16:30:45 brouard
767: (Module): On windows (cygwin) function asctime_r doesn't
768: exist so I changed back to asctime which exists.
769:
770: Revision 1.91 2003/06/25 15:30:29 brouard
771: * imach.c (Repository): Duplicated warning errors corrected.
772: (Repository): Elapsed time after each iteration is now output. It
773: helps to forecast when convergence will be reached. Elapsed time
774: is stamped in powell. We created a new html file for the graphs
775: concerning matrix of covariance. It has extension -cov.htm.
776:
777: Revision 1.90 2003/06/24 12:34:15 brouard
778: (Module): Some bugs corrected for windows. Also, when
779: mle=-1 a template is output in file "or"mypar.txt with the design
780: of the covariance matrix to be input.
781:
782: Revision 1.89 2003/06/24 12:30:52 brouard
783: (Module): Some bugs corrected for windows. Also, when
784: mle=-1 a template is output in file "or"mypar.txt with the design
785: of the covariance matrix to be input.
786:
787: Revision 1.88 2003/06/23 17:54:56 brouard
788: * 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.
789:
790: Revision 1.87 2003/06/18 12:26:01 brouard
791: Version 0.96
792:
793: Revision 1.86 2003/06/17 20:04:08 brouard
794: (Module): Change position of html and gnuplot routines and added
795: routine fileappend.
796:
797: Revision 1.85 2003/06/17 13:12:43 brouard
798: * imach.c (Repository): Check when date of death was earlier that
799: current date of interview. It may happen when the death was just
800: prior to the death. In this case, dh was negative and likelihood
801: was wrong (infinity). We still send an "Error" but patch by
802: assuming that the date of death was just one stepm after the
803: interview.
804: (Repository): Because some people have very long ID (first column)
805: we changed int to long in num[] and we added a new lvector for
806: memory allocation. But we also truncated to 8 characters (left
807: truncation)
808: (Repository): No more line truncation errors.
809:
810: Revision 1.84 2003/06/13 21:44:43 brouard
811: * imach.c (Repository): Replace "freqsummary" at a correct
812: place. It differs from routine "prevalence" which may be called
813: many times. Probs is memory consuming and must be used with
814: parcimony.
815: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
816:
817: Revision 1.83 2003/06/10 13:39:11 lievre
818: *** empty log message ***
819:
820: Revision 1.82 2003/06/05 15:57:20 brouard
821: Add log in imach.c and fullversion number is now printed.
822:
823: */
824: /*
825: Interpolated Markov Chain
826:
827: Short summary of the programme:
828:
1.227 brouard 829: This program computes Healthy Life Expectancies or State-specific
830: (if states aren't health statuses) Expectancies from
831: cross-longitudinal data. Cross-longitudinal data consist in:
832:
833: -1- a first survey ("cross") where individuals from different ages
834: are interviewed on their health status or degree of disability (in
835: the case of a health survey which is our main interest)
836:
837: -2- at least a second wave of interviews ("longitudinal") which
838: measure each change (if any) in individual health status. Health
839: expectancies are computed from the time spent in each health state
840: according to a model. More health states you consider, more time is
841: necessary to reach the Maximum Likelihood of the parameters involved
842: in the model. The simplest model is the multinomial logistic model
843: where pij is the probability to be observed in state j at the second
844: wave conditional to be observed in state i at the first
845: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
846: etc , where 'age' is age and 'sex' is a covariate. If you want to
847: have a more complex model than "constant and age", you should modify
848: the program where the markup *Covariates have to be included here
849: again* invites you to do it. More covariates you add, slower the
1.126 brouard 850: convergence.
851:
852: The advantage of this computer programme, compared to a simple
853: multinomial logistic model, is clear when the delay between waves is not
854: identical for each individual. Also, if a individual missed an
855: intermediate interview, the information is lost, but taken into
856: account using an interpolation or extrapolation.
857:
858: hPijx is the probability to be observed in state i at age x+h
859: conditional to the observed state i at age x. The delay 'h' can be
860: split into an exact number (nh*stepm) of unobserved intermediate
861: states. This elementary transition (by month, quarter,
862: semester or year) is modelled as a multinomial logistic. The hPx
863: matrix is simply the matrix product of nh*stepm elementary matrices
864: and the contribution of each individual to the likelihood is simply
865: hPijx.
866:
867: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 868: of the life expectancies. It also computes the period (stable) prevalence.
869:
870: Back prevalence and projections:
1.227 brouard 871:
872: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
873: double agemaxpar, double ftolpl, int *ncvyearp, double
874: dateprev1,double dateprev2, int firstpass, int lastpass, int
875: mobilavproj)
876:
877: Computes the back prevalence limit for any combination of
878: covariate values k at any age between ageminpar and agemaxpar and
879: returns it in **bprlim. In the loops,
880:
881: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
882: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
883:
884: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 885: Computes for any combination of covariates k and any age between bage and fage
886: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
887: oldm=oldms;savm=savms;
1.227 brouard 888:
1.267 brouard 889: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 890: Computes the transition matrix starting at age 'age' over
891: 'nhstepm*hstepm*stepm' months (i.e. until
892: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 893: nhstepm*hstepm matrices.
894:
895: Returns p3mat[i][j][h] after calling
896: p3mat[i][j][h]=matprod2(newm,
897: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
898: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
899: oldm);
1.226 brouard 900:
901: Important routines
902:
903: - func (or funcone), computes logit (pij) distinguishing
904: o fixed variables (single or product dummies or quantitative);
905: o varying variables by:
906: (1) wave (single, product dummies, quantitative),
907: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
908: % fixed dummy (treated) or quantitative (not done because time-consuming);
909: % varying dummy (not done) or quantitative (not done);
910: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
911: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
912: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
913: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
914: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 915:
1.226 brouard 916:
917:
1.133 brouard 918: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
919: Institut national d'études démographiques, Paris.
1.126 brouard 920: This software have been partly granted by Euro-REVES, a concerted action
921: from the European Union.
922: It is copyrighted identically to a GNU software product, ie programme and
923: software can be distributed freely for non commercial use. Latest version
924: can be accessed at http://euroreves.ined.fr/imach .
925:
926: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
927: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
928:
929: **********************************************************************/
930: /*
931: main
932: read parameterfile
933: read datafile
934: concatwav
935: freqsummary
936: if (mle >= 1)
937: mlikeli
938: print results files
939: if mle==1
940: computes hessian
941: read end of parameter file: agemin, agemax, bage, fage, estepm
942: begin-prev-date,...
943: open gnuplot file
944: open html file
1.145 brouard 945: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
946: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
947: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
948: freexexit2 possible for memory heap.
949:
950: h Pij x | pij_nom ficrestpij
951: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
952: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
953: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
954:
955: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
956: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
957: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
958: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
959: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
960:
1.126 brouard 961: forecasting if prevfcast==1 prevforecast call prevalence()
962: health expectancies
963: Variance-covariance of DFLE
964: prevalence()
965: movingaverage()
966: varevsij()
967: if popbased==1 varevsij(,popbased)
968: total life expectancies
969: Variance of period (stable) prevalence
970: end
971: */
972:
1.187 brouard 973: /* #define DEBUG */
974: /* #define DEBUGBRENT */
1.203 brouard 975: /* #define DEBUGLINMIN */
976: /* #define DEBUGHESS */
977: #define DEBUGHESSIJ
1.224 brouard 978: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 979: #define POWELL /* Instead of NLOPT */
1.224 brouard 980: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 981: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
982: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 983:
984: #include <math.h>
985: #include <stdio.h>
986: #include <stdlib.h>
987: #include <string.h>
1.226 brouard 988: #include <ctype.h>
1.159 brouard 989:
990: #ifdef _WIN32
991: #include <io.h>
1.172 brouard 992: #include <windows.h>
993: #include <tchar.h>
1.159 brouard 994: #else
1.126 brouard 995: #include <unistd.h>
1.159 brouard 996: #endif
1.126 brouard 997:
998: #include <limits.h>
999: #include <sys/types.h>
1.171 brouard 1000:
1001: #if defined(__GNUC__)
1002: #include <sys/utsname.h> /* Doesn't work on Windows */
1003: #endif
1004:
1.126 brouard 1005: #include <sys/stat.h>
1006: #include <errno.h>
1.159 brouard 1007: /* extern int errno; */
1.126 brouard 1008:
1.157 brouard 1009: /* #ifdef LINUX */
1010: /* #include <time.h> */
1011: /* #include "timeval.h" */
1012: /* #else */
1013: /* #include <sys/time.h> */
1014: /* #endif */
1015:
1.126 brouard 1016: #include <time.h>
1017:
1.136 brouard 1018: #ifdef GSL
1019: #include <gsl/gsl_errno.h>
1020: #include <gsl/gsl_multimin.h>
1021: #endif
1022:
1.167 brouard 1023:
1.162 brouard 1024: #ifdef NLOPT
1025: #include <nlopt.h>
1026: typedef struct {
1027: double (* function)(double [] );
1028: } myfunc_data ;
1029: #endif
1030:
1.126 brouard 1031: /* #include <libintl.h> */
1032: /* #define _(String) gettext (String) */
1033:
1.251 brouard 1034: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1035:
1036: #define GNUPLOTPROGRAM "gnuplot"
1037: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1038: #define FILENAMELENGTH 132
1039:
1040: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1041: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1042:
1.144 brouard 1043: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1044: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1045:
1046: #define NINTERVMAX 8
1.144 brouard 1047: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1048: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1049: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 1050: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1051: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1052: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.126 brouard 1053: #define MAXN 20000
1.144 brouard 1054: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1055: /* #define AGESUP 130 */
1.288 brouard 1056: /* #define AGESUP 150 */
1057: #define AGESUP 200
1.268 brouard 1058: #define AGEINF 0
1.218 brouard 1059: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1060: #define AGEBASE 40
1.194 brouard 1061: #define AGEOVERFLOW 1.e20
1.164 brouard 1062: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1063: #ifdef _WIN32
1064: #define DIRSEPARATOR '\\'
1065: #define CHARSEPARATOR "\\"
1066: #define ODIRSEPARATOR '/'
1067: #else
1.126 brouard 1068: #define DIRSEPARATOR '/'
1069: #define CHARSEPARATOR "/"
1070: #define ODIRSEPARATOR '\\'
1071: #endif
1072:
1.289 ! brouard 1073: /* $Id: imach.c,v 1.288 2018/05/02 20:58:27 brouard Exp $ */
1.126 brouard 1074: /* $State: Exp $ */
1.196 brouard 1075: #include "version.h"
1076: char version[]=__IMACH_VERSION__;
1.283 brouard 1077: 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";
1.289 ! brouard 1078: char fullversion[]="$Revision: 1.288 $ $Date: 2018/05/02 20:58:27 $";
1.126 brouard 1079: char strstart[80];
1080: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1081: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1082: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1083: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1084: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1085: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1086: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1087: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1088: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1089: int cptcovprodnoage=0; /**< Number of covariate products without age */
1090: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1091: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1092: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1093: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1094: int nsd=0; /**< Total number of single dummy variables (output) */
1095: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1096: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1097: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1098: int ntveff=0; /**< ntveff number of effective time varying variables */
1099: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1100: int cptcov=0; /* Working variable */
1.218 brouard 1101: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 1102: int npar=NPARMAX;
1103: int nlstate=2; /* Number of live states */
1104: int ndeath=1; /* Number of dead states */
1.130 brouard 1105: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1106: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1107: int popbased=0;
1108:
1109: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1110: int maxwav=0; /* Maxim number of waves */
1111: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1112: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1113: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1114: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1115: int mle=1, weightopt=0;
1.126 brouard 1116: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1117: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1118: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1119: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1120: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1121: int selected(int kvar); /* Is covariate kvar selected for printing results */
1122:
1.130 brouard 1123: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1124: double **matprod2(); /* test */
1.126 brouard 1125: double **oldm, **newm, **savm; /* Working pointers to matrices */
1126: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1127: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1128:
1.136 brouard 1129: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1130: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1131: FILE *ficlog, *ficrespow;
1.130 brouard 1132: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1133: double fretone; /* Only one call to likelihood */
1.130 brouard 1134: long ipmx=0; /* Number of contributions */
1.126 brouard 1135: double sw; /* Sum of weights */
1136: char filerespow[FILENAMELENGTH];
1137: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1138: FILE *ficresilk;
1139: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1140: FILE *ficresprobmorprev;
1141: FILE *fichtm, *fichtmcov; /* Html File */
1142: FILE *ficreseij;
1143: char filerese[FILENAMELENGTH];
1144: FILE *ficresstdeij;
1145: char fileresstde[FILENAMELENGTH];
1146: FILE *ficrescveij;
1147: char filerescve[FILENAMELENGTH];
1148: FILE *ficresvij;
1149: char fileresv[FILENAMELENGTH];
1.269 brouard 1150:
1.126 brouard 1151: char title[MAXLINE];
1.234 brouard 1152: char model[MAXLINE]; /**< The model line */
1.217 brouard 1153: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1154: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1155: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1156: char command[FILENAMELENGTH];
1157: int outcmd=0;
1158:
1.217 brouard 1159: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1160: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1161: char filelog[FILENAMELENGTH]; /* Log file */
1162: char filerest[FILENAMELENGTH];
1163: char fileregp[FILENAMELENGTH];
1164: char popfile[FILENAMELENGTH];
1165:
1166: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1167:
1.157 brouard 1168: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1169: /* struct timezone tzp; */
1170: /* extern int gettimeofday(); */
1171: struct tm tml, *gmtime(), *localtime();
1172:
1173: extern time_t time();
1174:
1175: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1176: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1177: struct tm tm;
1178:
1.126 brouard 1179: char strcurr[80], strfor[80];
1180:
1181: char *endptr;
1182: long lval;
1183: double dval;
1184:
1185: #define NR_END 1
1186: #define FREE_ARG char*
1187: #define FTOL 1.0e-10
1188:
1189: #define NRANSI
1.240 brouard 1190: #define ITMAX 200
1191: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1192:
1193: #define TOL 2.0e-4
1194:
1195: #define CGOLD 0.3819660
1196: #define ZEPS 1.0e-10
1197: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1198:
1199: #define GOLD 1.618034
1200: #define GLIMIT 100.0
1201: #define TINY 1.0e-20
1202:
1203: static double maxarg1,maxarg2;
1204: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1205: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1206:
1207: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1208: #define rint(a) floor(a+0.5)
1.166 brouard 1209: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1210: #define mytinydouble 1.0e-16
1.166 brouard 1211: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1212: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1213: /* static double dsqrarg; */
1214: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1215: static double sqrarg;
1216: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1217: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1218: int agegomp= AGEGOMP;
1219:
1220: int imx;
1221: int stepm=1;
1222: /* Stepm, step in month: minimum step interpolation*/
1223:
1224: int estepm;
1225: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1226:
1227: int m,nb;
1228: long *num;
1.197 brouard 1229: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1230: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1231: covariate for which somebody answered excluding
1232: undefined. Usually 2: 0 and 1. */
1233: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1234: covariate for which somebody answered including
1235: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1236: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1237: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1238: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1239: double *ageexmed,*agecens;
1240: double dateintmean=0;
1241:
1242: double *weight;
1243: int **s; /* Status */
1.141 brouard 1244: double *agedc;
1.145 brouard 1245: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1246: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1247: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1248: double **coqvar; /* Fixed quantitative covariate nqv */
1249: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1250: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1251: double idx;
1252: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1253: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1254: /*k 1 2 3 4 5 6 7 8 9 */
1255: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1256: /* Tndvar[k] 1 2 3 4 5 */
1257: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1258: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1259: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1260: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1261: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1262: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1263: /* Tprod[i]=k 4 7 */
1264: /* Tage[i]=k 5 8 */
1265: /* */
1266: /* Type */
1267: /* V 1 2 3 4 5 */
1268: /* F F V V V */
1269: /* D Q D D Q */
1270: /* */
1271: int *TvarsD;
1272: int *TvarsDind;
1273: int *TvarsQ;
1274: int *TvarsQind;
1275:
1.235 brouard 1276: #define MAXRESULTLINES 10
1277: int nresult=0;
1.258 brouard 1278: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1279: int TKresult[MAXRESULTLINES];
1.237 brouard 1280: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1281: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1282: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1283: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1284: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1285: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1286:
1.234 brouard 1287: /* 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 1288: 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 */
1289: 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 */
1290: 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 */
1291: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1292: 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 */
1293: 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 1294: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1295: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1296: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1297: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1298: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1299: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1300: 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 */
1301: 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 */
1302:
1.230 brouard 1303: int *Tvarsel; /**< Selected covariates for output */
1304: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1305: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1306: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1307: 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 1308: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1309: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1310: int *Tage;
1.227 brouard 1311: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1312: 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 1313: 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*/
1314: 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 1315: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1316: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1317: int **Tvard;
1318: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1319: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1320: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1321: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1322: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1323: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1324: double *lsurv, *lpop, *tpop;
1325:
1.231 brouard 1326: #define FD 1; /* Fixed dummy covariate */
1327: #define FQ 2; /* Fixed quantitative covariate */
1328: #define FP 3; /* Fixed product covariate */
1329: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1330: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1331: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1332: #define VD 10; /* Varying dummy covariate */
1333: #define VQ 11; /* Varying quantitative covariate */
1334: #define VP 12; /* Varying product covariate */
1335: #define VPDD 13; /* Varying product dummy*dummy covariate */
1336: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1337: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1338: #define APFD 16; /* Age product * fixed dummy covariate */
1339: #define APFQ 17; /* Age product * fixed quantitative covariate */
1340: #define APVD 18; /* Age product * varying dummy covariate */
1341: #define APVQ 19; /* Age product * varying quantitative covariate */
1342:
1343: #define FTYPE 1; /* Fixed covariate */
1344: #define VTYPE 2; /* Varying covariate (loop in wave) */
1345: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1346:
1347: struct kmodel{
1348: int maintype; /* main type */
1349: int subtype; /* subtype */
1350: };
1351: struct kmodel modell[NCOVMAX];
1352:
1.143 brouard 1353: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1354: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1355:
1356: /**************** split *************************/
1357: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1358: {
1359: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1360: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1361: */
1362: char *ss; /* pointer */
1.186 brouard 1363: int l1=0, l2=0; /* length counters */
1.126 brouard 1364:
1365: l1 = strlen(path ); /* length of path */
1366: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1367: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1368: if ( ss == NULL ) { /* no directory, so determine current directory */
1369: strcpy( name, path ); /* we got the fullname name because no directory */
1370: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1371: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1372: /* get current working directory */
1373: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1374: #ifdef WIN32
1375: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1376: #else
1377: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1378: #endif
1.126 brouard 1379: return( GLOCK_ERROR_GETCWD );
1380: }
1381: /* got dirc from getcwd*/
1382: printf(" DIRC = %s \n",dirc);
1.205 brouard 1383: } else { /* strip directory from path */
1.126 brouard 1384: ss++; /* after this, the filename */
1385: l2 = strlen( ss ); /* length of filename */
1386: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1387: strcpy( name, ss ); /* save file name */
1388: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1389: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1390: printf(" DIRC2 = %s \n",dirc);
1391: }
1392: /* We add a separator at the end of dirc if not exists */
1393: l1 = strlen( dirc ); /* length of directory */
1394: if( dirc[l1-1] != DIRSEPARATOR ){
1395: dirc[l1] = DIRSEPARATOR;
1396: dirc[l1+1] = 0;
1397: printf(" DIRC3 = %s \n",dirc);
1398: }
1399: ss = strrchr( name, '.' ); /* find last / */
1400: if (ss >0){
1401: ss++;
1402: strcpy(ext,ss); /* save extension */
1403: l1= strlen( name);
1404: l2= strlen(ss)+1;
1405: strncpy( finame, name, l1-l2);
1406: finame[l1-l2]= 0;
1407: }
1408:
1409: return( 0 ); /* we're done */
1410: }
1411:
1412:
1413: /******************************************/
1414:
1415: void replace_back_to_slash(char *s, char*t)
1416: {
1417: int i;
1418: int lg=0;
1419: i=0;
1420: lg=strlen(t);
1421: for(i=0; i<= lg; i++) {
1422: (s[i] = t[i]);
1423: if (t[i]== '\\') s[i]='/';
1424: }
1425: }
1426:
1.132 brouard 1427: char *trimbb(char *out, char *in)
1.137 brouard 1428: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1429: char *s;
1430: s=out;
1431: while (*in != '\0'){
1.137 brouard 1432: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1433: in++;
1434: }
1435: *out++ = *in++;
1436: }
1437: *out='\0';
1438: return s;
1439: }
1440:
1.187 brouard 1441: /* char *substrchaine(char *out, char *in, char *chain) */
1442: /* { */
1443: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1444: /* char *s, *t; */
1445: /* t=in;s=out; */
1446: /* while ((*in != *chain) && (*in != '\0')){ */
1447: /* *out++ = *in++; */
1448: /* } */
1449:
1450: /* /\* *in matches *chain *\/ */
1451: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1452: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1453: /* } */
1454: /* in--; chain--; */
1455: /* while ( (*in != '\0')){ */
1456: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1457: /* *out++ = *in++; */
1458: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1459: /* } */
1460: /* *out='\0'; */
1461: /* out=s; */
1462: /* return out; */
1463: /* } */
1464: char *substrchaine(char *out, char *in, char *chain)
1465: {
1466: /* Substract chain 'chain' from 'in', return and output 'out' */
1467: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1468:
1469: char *strloc;
1470:
1471: strcpy (out, in);
1472: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1473: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1474: if(strloc != NULL){
1475: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1476: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1477: /* strcpy (strloc, strloc +strlen(chain));*/
1478: }
1479: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1480: return out;
1481: }
1482:
1483:
1.145 brouard 1484: char *cutl(char *blocc, char *alocc, char *in, char occ)
1485: {
1.187 brouard 1486: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1487: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1488: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1489: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1490: */
1.160 brouard 1491: char *s, *t;
1.145 brouard 1492: t=in;s=in;
1493: while ((*in != occ) && (*in != '\0')){
1494: *alocc++ = *in++;
1495: }
1496: if( *in == occ){
1497: *(alocc)='\0';
1498: s=++in;
1499: }
1500:
1501: if (s == t) {/* occ not found */
1502: *(alocc-(in-s))='\0';
1503: in=s;
1504: }
1505: while ( *in != '\0'){
1506: *blocc++ = *in++;
1507: }
1508:
1509: *blocc='\0';
1510: return t;
1511: }
1.137 brouard 1512: char *cutv(char *blocc, char *alocc, char *in, char occ)
1513: {
1.187 brouard 1514: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1515: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1516: gives blocc="abcdef2ghi" and alocc="j".
1517: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1518: */
1519: char *s, *t;
1520: t=in;s=in;
1521: while (*in != '\0'){
1522: while( *in == occ){
1523: *blocc++ = *in++;
1524: s=in;
1525: }
1526: *blocc++ = *in++;
1527: }
1528: if (s == t) /* occ not found */
1529: *(blocc-(in-s))='\0';
1530: else
1531: *(blocc-(in-s)-1)='\0';
1532: in=s;
1533: while ( *in != '\0'){
1534: *alocc++ = *in++;
1535: }
1536:
1537: *alocc='\0';
1538: return s;
1539: }
1540:
1.126 brouard 1541: int nbocc(char *s, char occ)
1542: {
1543: int i,j=0;
1544: int lg=20;
1545: i=0;
1546: lg=strlen(s);
1547: for(i=0; i<= lg; i++) {
1.234 brouard 1548: if (s[i] == occ ) j++;
1.126 brouard 1549: }
1550: return j;
1551: }
1552:
1.137 brouard 1553: /* void cutv(char *u,char *v, char*t, char occ) */
1554: /* { */
1555: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1556: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1557: /* gives u="abcdef2ghi" and v="j" *\/ */
1558: /* int i,lg,j,p=0; */
1559: /* i=0; */
1560: /* lg=strlen(t); */
1561: /* for(j=0; j<=lg-1; j++) { */
1562: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1563: /* } */
1.126 brouard 1564:
1.137 brouard 1565: /* for(j=0; j<p; j++) { */
1566: /* (u[j] = t[j]); */
1567: /* } */
1568: /* u[p]='\0'; */
1.126 brouard 1569:
1.137 brouard 1570: /* for(j=0; j<= lg; j++) { */
1571: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1572: /* } */
1573: /* } */
1.126 brouard 1574:
1.160 brouard 1575: #ifdef _WIN32
1576: char * strsep(char **pp, const char *delim)
1577: {
1578: char *p, *q;
1579:
1580: if ((p = *pp) == NULL)
1581: return 0;
1582: if ((q = strpbrk (p, delim)) != NULL)
1583: {
1584: *pp = q + 1;
1585: *q = '\0';
1586: }
1587: else
1588: *pp = 0;
1589: return p;
1590: }
1591: #endif
1592:
1.126 brouard 1593: /********************** nrerror ********************/
1594:
1595: void nrerror(char error_text[])
1596: {
1597: fprintf(stderr,"ERREUR ...\n");
1598: fprintf(stderr,"%s\n",error_text);
1599: exit(EXIT_FAILURE);
1600: }
1601: /*********************** vector *******************/
1602: double *vector(int nl, int nh)
1603: {
1604: double *v;
1605: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1606: if (!v) nrerror("allocation failure in vector");
1607: return v-nl+NR_END;
1608: }
1609:
1610: /************************ free vector ******************/
1611: void free_vector(double*v, int nl, int nh)
1612: {
1613: free((FREE_ARG)(v+nl-NR_END));
1614: }
1615:
1616: /************************ivector *******************************/
1617: int *ivector(long nl,long nh)
1618: {
1619: int *v;
1620: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1621: if (!v) nrerror("allocation failure in ivector");
1622: return v-nl+NR_END;
1623: }
1624:
1625: /******************free ivector **************************/
1626: void free_ivector(int *v, long nl, long nh)
1627: {
1628: free((FREE_ARG)(v+nl-NR_END));
1629: }
1630:
1631: /************************lvector *******************************/
1632: long *lvector(long nl,long nh)
1633: {
1634: long *v;
1635: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1636: if (!v) nrerror("allocation failure in ivector");
1637: return v-nl+NR_END;
1638: }
1639:
1640: /******************free lvector **************************/
1641: void free_lvector(long *v, long nl, long nh)
1642: {
1643: free((FREE_ARG)(v+nl-NR_END));
1644: }
1645:
1646: /******************* imatrix *******************************/
1647: int **imatrix(long nrl, long nrh, long ncl, long nch)
1648: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1649: {
1650: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1651: int **m;
1652:
1653: /* allocate pointers to rows */
1654: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1655: if (!m) nrerror("allocation failure 1 in matrix()");
1656: m += NR_END;
1657: m -= nrl;
1658:
1659:
1660: /* allocate rows and set pointers to them */
1661: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1662: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1663: m[nrl] += NR_END;
1664: m[nrl] -= ncl;
1665:
1666: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1667:
1668: /* return pointer to array of pointers to rows */
1669: return m;
1670: }
1671:
1672: /****************** free_imatrix *************************/
1673: void free_imatrix(m,nrl,nrh,ncl,nch)
1674: int **m;
1675: long nch,ncl,nrh,nrl;
1676: /* free an int matrix allocated by imatrix() */
1677: {
1678: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1679: free((FREE_ARG) (m+nrl-NR_END));
1680: }
1681:
1682: /******************* matrix *******************************/
1683: double **matrix(long nrl, long nrh, long ncl, long nch)
1684: {
1685: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1686: double **m;
1687:
1688: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1689: if (!m) nrerror("allocation failure 1 in matrix()");
1690: m += NR_END;
1691: m -= nrl;
1692:
1693: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1694: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1695: m[nrl] += NR_END;
1696: m[nrl] -= ncl;
1697:
1698: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1699: return m;
1.145 brouard 1700: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1701: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1702: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1703: */
1704: }
1705:
1706: /*************************free matrix ************************/
1707: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1708: {
1709: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1710: free((FREE_ARG)(m+nrl-NR_END));
1711: }
1712:
1713: /******************* ma3x *******************************/
1714: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1715: {
1716: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1717: double ***m;
1718:
1719: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1720: if (!m) nrerror("allocation failure 1 in matrix()");
1721: m += NR_END;
1722: m -= nrl;
1723:
1724: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1725: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1726: m[nrl] += NR_END;
1727: m[nrl] -= ncl;
1728:
1729: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1730:
1731: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1732: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1733: m[nrl][ncl] += NR_END;
1734: m[nrl][ncl] -= nll;
1735: for (j=ncl+1; j<=nch; j++)
1736: m[nrl][j]=m[nrl][j-1]+nlay;
1737:
1738: for (i=nrl+1; i<=nrh; i++) {
1739: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1740: for (j=ncl+1; j<=nch; j++)
1741: m[i][j]=m[i][j-1]+nlay;
1742: }
1743: return m;
1744: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1745: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1746: */
1747: }
1748:
1749: /*************************free ma3x ************************/
1750: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1751: {
1752: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1753: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1754: free((FREE_ARG)(m+nrl-NR_END));
1755: }
1756:
1757: /*************** function subdirf ***********/
1758: char *subdirf(char fileres[])
1759: {
1760: /* Caution optionfilefiname is hidden */
1761: strcpy(tmpout,optionfilefiname);
1762: strcat(tmpout,"/"); /* Add to the right */
1763: strcat(tmpout,fileres);
1764: return tmpout;
1765: }
1766:
1767: /*************** function subdirf2 ***********/
1768: char *subdirf2(char fileres[], char *preop)
1769: {
1770:
1771: /* Caution optionfilefiname is hidden */
1772: strcpy(tmpout,optionfilefiname);
1773: strcat(tmpout,"/");
1774: strcat(tmpout,preop);
1775: strcat(tmpout,fileres);
1776: return tmpout;
1777: }
1778:
1779: /*************** function subdirf3 ***********/
1780: char *subdirf3(char fileres[], char *preop, char *preop2)
1781: {
1782:
1783: /* Caution optionfilefiname is hidden */
1784: strcpy(tmpout,optionfilefiname);
1785: strcat(tmpout,"/");
1786: strcat(tmpout,preop);
1787: strcat(tmpout,preop2);
1788: strcat(tmpout,fileres);
1789: return tmpout;
1790: }
1.213 brouard 1791:
1792: /*************** function subdirfext ***********/
1793: char *subdirfext(char fileres[], char *preop, char *postop)
1794: {
1795:
1796: strcpy(tmpout,preop);
1797: strcat(tmpout,fileres);
1798: strcat(tmpout,postop);
1799: return tmpout;
1800: }
1.126 brouard 1801:
1.213 brouard 1802: /*************** function subdirfext3 ***********/
1803: char *subdirfext3(char fileres[], char *preop, char *postop)
1804: {
1805:
1806: /* Caution optionfilefiname is hidden */
1807: strcpy(tmpout,optionfilefiname);
1808: strcat(tmpout,"/");
1809: strcat(tmpout,preop);
1810: strcat(tmpout,fileres);
1811: strcat(tmpout,postop);
1812: return tmpout;
1813: }
1814:
1.162 brouard 1815: char *asc_diff_time(long time_sec, char ascdiff[])
1816: {
1817: long sec_left, days, hours, minutes;
1818: days = (time_sec) / (60*60*24);
1819: sec_left = (time_sec) % (60*60*24);
1820: hours = (sec_left) / (60*60) ;
1821: sec_left = (sec_left) %(60*60);
1822: minutes = (sec_left) /60;
1823: sec_left = (sec_left) % (60);
1824: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1825: return ascdiff;
1826: }
1827:
1.126 brouard 1828: /***************** f1dim *************************/
1829: extern int ncom;
1830: extern double *pcom,*xicom;
1831: extern double (*nrfunc)(double []);
1832:
1833: double f1dim(double x)
1834: {
1835: int j;
1836: double f;
1837: double *xt;
1838:
1839: xt=vector(1,ncom);
1840: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1841: f=(*nrfunc)(xt);
1842: free_vector(xt,1,ncom);
1843: return f;
1844: }
1845:
1846: /*****************brent *************************/
1847: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1848: {
1849: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1850: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1851: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1852: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1853: * returned function value.
1854: */
1.126 brouard 1855: int iter;
1856: double a,b,d,etemp;
1.159 brouard 1857: double fu=0,fv,fw,fx;
1.164 brouard 1858: double ftemp=0.;
1.126 brouard 1859: double p,q,r,tol1,tol2,u,v,w,x,xm;
1860: double e=0.0;
1861:
1862: a=(ax < cx ? ax : cx);
1863: b=(ax > cx ? ax : cx);
1864: x=w=v=bx;
1865: fw=fv=fx=(*f)(x);
1866: for (iter=1;iter<=ITMAX;iter++) {
1867: xm=0.5*(a+b);
1868: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1869: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1870: printf(".");fflush(stdout);
1871: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1872: #ifdef DEBUGBRENT
1.126 brouard 1873: 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);
1874: 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);
1875: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1876: #endif
1877: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1878: *xmin=x;
1879: return fx;
1880: }
1881: ftemp=fu;
1882: if (fabs(e) > tol1) {
1883: r=(x-w)*(fx-fv);
1884: q=(x-v)*(fx-fw);
1885: p=(x-v)*q-(x-w)*r;
1886: q=2.0*(q-r);
1887: if (q > 0.0) p = -p;
1888: q=fabs(q);
1889: etemp=e;
1890: e=d;
1891: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1892: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1893: else {
1.224 brouard 1894: d=p/q;
1895: u=x+d;
1896: if (u-a < tol2 || b-u < tol2)
1897: d=SIGN(tol1,xm-x);
1.126 brouard 1898: }
1899: } else {
1900: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1901: }
1902: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1903: fu=(*f)(u);
1904: if (fu <= fx) {
1905: if (u >= x) a=x; else b=x;
1906: SHFT(v,w,x,u)
1.183 brouard 1907: SHFT(fv,fw,fx,fu)
1908: } else {
1909: if (u < x) a=u; else b=u;
1910: if (fu <= fw || w == x) {
1.224 brouard 1911: v=w;
1912: w=u;
1913: fv=fw;
1914: fw=fu;
1.183 brouard 1915: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1916: v=u;
1917: fv=fu;
1.183 brouard 1918: }
1919: }
1.126 brouard 1920: }
1921: nrerror("Too many iterations in brent");
1922: *xmin=x;
1923: return fx;
1924: }
1925:
1926: /****************** mnbrak ***********************/
1927:
1928: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1929: double (*func)(double))
1.183 brouard 1930: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1931: the downhill direction (defined by the function as evaluated at the initial points) and returns
1932: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1933: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1934: */
1.126 brouard 1935: double ulim,u,r,q, dum;
1936: double fu;
1.187 brouard 1937:
1938: double scale=10.;
1939: int iterscale=0;
1940:
1941: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1942: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1943:
1944:
1945: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1946: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1947: /* *bx = *ax - (*ax - *bx)/scale; */
1948: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1949: /* } */
1950:
1.126 brouard 1951: if (*fb > *fa) {
1952: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1953: SHFT(dum,*fb,*fa,dum)
1954: }
1.126 brouard 1955: *cx=(*bx)+GOLD*(*bx-*ax);
1956: *fc=(*func)(*cx);
1.183 brouard 1957: #ifdef DEBUG
1.224 brouard 1958: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1959: 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 1960: #endif
1.224 brouard 1961: 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 1962: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1963: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1964: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1965: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1966: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1967: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1968: fu=(*func)(u);
1.163 brouard 1969: #ifdef DEBUG
1970: /* f(x)=A(x-u)**2+f(u) */
1971: double A, fparabu;
1972: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1973: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 1974: 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);
1975: 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 1976: /* And thus,it can be that fu > *fc even if fparabu < *fc */
1977: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
1978: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
1979: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 1980: #endif
1.184 brouard 1981: #ifdef MNBRAKORIGINAL
1.183 brouard 1982: #else
1.191 brouard 1983: /* if (fu > *fc) { */
1984: /* #ifdef DEBUG */
1985: /* printf("mnbrak4 fu > fc \n"); */
1986: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
1987: /* #endif */
1988: /* /\* 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 *\\/ *\/ */
1989: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
1990: /* dum=u; /\* Shifting c and u *\/ */
1991: /* u = *cx; */
1992: /* *cx = dum; */
1993: /* dum = fu; */
1994: /* fu = *fc; */
1995: /* *fc =dum; */
1996: /* } else { /\* end *\/ */
1997: /* #ifdef DEBUG */
1998: /* printf("mnbrak3 fu < fc \n"); */
1999: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2000: /* #endif */
2001: /* dum=u; /\* Shifting c and u *\/ */
2002: /* u = *cx; */
2003: /* *cx = dum; */
2004: /* dum = fu; */
2005: /* fu = *fc; */
2006: /* *fc =dum; */
2007: /* } */
1.224 brouard 2008: #ifdef DEBUGMNBRAK
2009: double A, fparabu;
2010: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2011: fparabu= *fa - A*(*ax-u)*(*ax-u);
2012: 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);
2013: 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 2014: #endif
1.191 brouard 2015: dum=u; /* Shifting c and u */
2016: u = *cx;
2017: *cx = dum;
2018: dum = fu;
2019: fu = *fc;
2020: *fc =dum;
1.183 brouard 2021: #endif
1.162 brouard 2022: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2023: #ifdef DEBUG
1.224 brouard 2024: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2025: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2026: #endif
1.126 brouard 2027: fu=(*func)(u);
2028: if (fu < *fc) {
1.183 brouard 2029: #ifdef DEBUG
1.224 brouard 2030: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2031: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2032: #endif
2033: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2034: SHFT(*fb,*fc,fu,(*func)(u))
2035: #ifdef DEBUG
2036: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2037: #endif
2038: }
1.162 brouard 2039: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2040: #ifdef DEBUG
1.224 brouard 2041: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2042: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2043: #endif
1.126 brouard 2044: u=ulim;
2045: fu=(*func)(u);
1.183 brouard 2046: } else { /* u could be left to b (if r > q parabola has a maximum) */
2047: #ifdef DEBUG
1.224 brouard 2048: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2049: 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 2050: #endif
1.126 brouard 2051: u=(*cx)+GOLD*(*cx-*bx);
2052: fu=(*func)(u);
1.224 brouard 2053: #ifdef DEBUG
2054: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2055: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2056: #endif
1.183 brouard 2057: } /* end tests */
1.126 brouard 2058: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2059: SHFT(*fa,*fb,*fc,fu)
2060: #ifdef DEBUG
1.224 brouard 2061: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2062: 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 2063: #endif
2064: } /* 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 2065: }
2066:
2067: /*************** linmin ************************/
1.162 brouard 2068: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2069: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2070: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2071: the value of func at the returned location p . This is actually all accomplished by calling the
2072: routines mnbrak and brent .*/
1.126 brouard 2073: int ncom;
2074: double *pcom,*xicom;
2075: double (*nrfunc)(double []);
2076:
1.224 brouard 2077: #ifdef LINMINORIGINAL
1.126 brouard 2078: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2079: #else
2080: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2081: #endif
1.126 brouard 2082: {
2083: double brent(double ax, double bx, double cx,
2084: double (*f)(double), double tol, double *xmin);
2085: double f1dim(double x);
2086: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2087: double *fc, double (*func)(double));
2088: int j;
2089: double xx,xmin,bx,ax;
2090: double fx,fb,fa;
1.187 brouard 2091:
1.203 brouard 2092: #ifdef LINMINORIGINAL
2093: #else
2094: double scale=10., axs, xxs; /* Scale added for infinity */
2095: #endif
2096:
1.126 brouard 2097: ncom=n;
2098: pcom=vector(1,n);
2099: xicom=vector(1,n);
2100: nrfunc=func;
2101: for (j=1;j<=n;j++) {
2102: pcom[j]=p[j];
1.202 brouard 2103: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2104: }
1.187 brouard 2105:
1.203 brouard 2106: #ifdef LINMINORIGINAL
2107: xx=1.;
2108: #else
2109: axs=0.0;
2110: xxs=1.;
2111: do{
2112: xx= xxs;
2113: #endif
1.187 brouard 2114: ax=0.;
2115: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2116: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2117: /* 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)) */
2118: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2119: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2120: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2121: /* 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 2122: #ifdef LINMINORIGINAL
2123: #else
2124: if (fx != fx){
1.224 brouard 2125: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2126: printf("|");
2127: fprintf(ficlog,"|");
1.203 brouard 2128: #ifdef DEBUGLINMIN
1.224 brouard 2129: 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 2130: #endif
2131: }
1.224 brouard 2132: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2133: #endif
2134:
1.191 brouard 2135: #ifdef DEBUGLINMIN
2136: 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 2137: 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 2138: #endif
1.224 brouard 2139: #ifdef LINMINORIGINAL
2140: #else
2141: if(fb == fx){ /* Flat function in the direction */
2142: xmin=xx;
2143: *flat=1;
2144: }else{
2145: *flat=0;
2146: #endif
2147: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2148: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2149: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2150: /* fmin = f(p[j] + xmin * xi[j]) */
2151: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2152: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2153: #ifdef DEBUG
1.224 brouard 2154: 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);
2155: 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);
2156: #endif
2157: #ifdef LINMINORIGINAL
2158: #else
2159: }
1.126 brouard 2160: #endif
1.191 brouard 2161: #ifdef DEBUGLINMIN
2162: printf("linmin end ");
1.202 brouard 2163: fprintf(ficlog,"linmin end ");
1.191 brouard 2164: #endif
1.126 brouard 2165: for (j=1;j<=n;j++) {
1.203 brouard 2166: #ifdef LINMINORIGINAL
2167: xi[j] *= xmin;
2168: #else
2169: #ifdef DEBUGLINMIN
2170: if(xxs <1.0)
2171: printf(" before xi[%d]=%12.8f", j,xi[j]);
2172: #endif
2173: 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) */
2174: #ifdef DEBUGLINMIN
2175: if(xxs <1.0)
2176: 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 );
2177: #endif
2178: #endif
1.187 brouard 2179: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2180: }
1.191 brouard 2181: #ifdef DEBUGLINMIN
1.203 brouard 2182: printf("\n");
1.191 brouard 2183: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2184: 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 2185: for (j=1;j<=n;j++) {
1.202 brouard 2186: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2187: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2188: if(j % ncovmodel == 0){
1.191 brouard 2189: printf("\n");
1.202 brouard 2190: fprintf(ficlog,"\n");
2191: }
1.191 brouard 2192: }
1.203 brouard 2193: #else
1.191 brouard 2194: #endif
1.126 brouard 2195: free_vector(xicom,1,n);
2196: free_vector(pcom,1,n);
2197: }
2198:
2199:
2200: /*************** powell ************************/
1.162 brouard 2201: /*
2202: Minimization of a function func of n variables. Input consists of an initial starting point
2203: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2204: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2205: such that failure to decrease by more than this amount on one iteration signals doneness. On
2206: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2207: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2208: */
1.224 brouard 2209: #ifdef LINMINORIGINAL
2210: #else
2211: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2212: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2213: #endif
1.126 brouard 2214: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2215: double (*func)(double []))
2216: {
1.224 brouard 2217: #ifdef LINMINORIGINAL
2218: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2219: double (*func)(double []));
1.224 brouard 2220: #else
1.241 brouard 2221: void linmin(double p[], double xi[], int n, double *fret,
2222: double (*func)(double []),int *flat);
1.224 brouard 2223: #endif
1.239 brouard 2224: int i,ibig,j,jk,k;
1.126 brouard 2225: double del,t,*pt,*ptt,*xit;
1.181 brouard 2226: double directest;
1.126 brouard 2227: double fp,fptt;
2228: double *xits;
2229: int niterf, itmp;
1.224 brouard 2230: #ifdef LINMINORIGINAL
2231: #else
2232:
2233: flatdir=ivector(1,n);
2234: for (j=1;j<=n;j++) flatdir[j]=0;
2235: #endif
1.126 brouard 2236:
2237: pt=vector(1,n);
2238: ptt=vector(1,n);
2239: xit=vector(1,n);
2240: xits=vector(1,n);
2241: *fret=(*func)(p);
2242: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2243: rcurr_time = time(NULL);
1.126 brouard 2244: for (*iter=1;;++(*iter)) {
1.187 brouard 2245: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2246: ibig=0;
2247: del=0.0;
1.157 brouard 2248: rlast_time=rcurr_time;
2249: /* (void) gettimeofday(&curr_time,&tzp); */
2250: rcurr_time = time(NULL);
2251: curr_time = *localtime(&rcurr_time);
2252: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2253: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2254: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2255: for (i=1;i<=n;i++) {
1.126 brouard 2256: fprintf(ficrespow," %.12lf", p[i]);
2257: }
1.239 brouard 2258: fprintf(ficrespow,"\n");fflush(ficrespow);
2259: printf("\n#model= 1 + age ");
2260: fprintf(ficlog,"\n#model= 1 + age ");
2261: if(nagesqr==1){
1.241 brouard 2262: printf(" + age*age ");
2263: fprintf(ficlog," + age*age ");
1.239 brouard 2264: }
2265: for(j=1;j <=ncovmodel-2;j++){
2266: if(Typevar[j]==0) {
2267: printf(" + V%d ",Tvar[j]);
2268: fprintf(ficlog," + V%d ",Tvar[j]);
2269: }else if(Typevar[j]==1) {
2270: printf(" + V%d*age ",Tvar[j]);
2271: fprintf(ficlog," + V%d*age ",Tvar[j]);
2272: }else if(Typevar[j]==2) {
2273: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2274: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2275: }
2276: }
1.126 brouard 2277: printf("\n");
1.239 brouard 2278: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2279: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2280: fprintf(ficlog,"\n");
1.239 brouard 2281: for(i=1,jk=1; i <=nlstate; i++){
2282: for(k=1; k <=(nlstate+ndeath); k++){
2283: if (k != i) {
2284: printf("%d%d ",i,k);
2285: fprintf(ficlog,"%d%d ",i,k);
2286: for(j=1; j <=ncovmodel; j++){
2287: printf("%12.7f ",p[jk]);
2288: fprintf(ficlog,"%12.7f ",p[jk]);
2289: jk++;
2290: }
2291: printf("\n");
2292: fprintf(ficlog,"\n");
2293: }
2294: }
2295: }
1.241 brouard 2296: if(*iter <=3 && *iter >1){
1.157 brouard 2297: tml = *localtime(&rcurr_time);
2298: strcpy(strcurr,asctime(&tml));
2299: rforecast_time=rcurr_time;
1.126 brouard 2300: itmp = strlen(strcurr);
2301: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2302: strcurr[itmp-1]='\0';
1.162 brouard 2303: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2304: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2305: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2306: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2307: forecast_time = *localtime(&rforecast_time);
2308: strcpy(strfor,asctime(&forecast_time));
2309: itmp = strlen(strfor);
2310: if(strfor[itmp-1]=='\n')
2311: strfor[itmp-1]='\0';
2312: 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);
2313: 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 2314: }
2315: }
1.187 brouard 2316: for (i=1;i<=n;i++) { /* For each direction i */
2317: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2318: fptt=(*fret);
2319: #ifdef DEBUG
1.203 brouard 2320: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2321: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2322: #endif
1.203 brouard 2323: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2324: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2325: #ifdef LINMINORIGINAL
1.188 brouard 2326: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2327: #else
2328: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2329: flatdir[i]=flat; /* Function is vanishing in that direction i */
2330: #endif
2331: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2332: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2333: /* because that direction will be replaced unless the gain del is small */
2334: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2335: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2336: /* with the new direction. */
2337: del=fabs(fptt-(*fret));
2338: ibig=i;
1.126 brouard 2339: }
2340: #ifdef DEBUG
2341: printf("%d %.12e",i,(*fret));
2342: fprintf(ficlog,"%d %.12e",i,(*fret));
2343: for (j=1;j<=n;j++) {
1.224 brouard 2344: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2345: printf(" x(%d)=%.12e",j,xit[j]);
2346: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2347: }
2348: for(j=1;j<=n;j++) {
1.225 brouard 2349: printf(" p(%d)=%.12e",j,p[j]);
2350: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2351: }
2352: printf("\n");
2353: fprintf(ficlog,"\n");
2354: #endif
1.187 brouard 2355: } /* end loop on each direction i */
2356: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2357: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2358: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2359: for(j=1;j<=n;j++) {
1.225 brouard 2360: if(flatdir[j] >0){
2361: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2362: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2363: }
2364: /* printf("\n"); */
2365: /* fprintf(ficlog,"\n"); */
2366: }
1.243 brouard 2367: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2368: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2369: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2370: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2371: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2372: /* decreased of more than 3.84 */
2373: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2374: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2375: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2376:
1.188 brouard 2377: /* Starting the program with initial values given by a former maximization will simply change */
2378: /* the scales of the directions and the directions, because the are reset to canonical directions */
2379: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2380: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2381: #ifdef DEBUG
2382: int k[2],l;
2383: k[0]=1;
2384: k[1]=-1;
2385: printf("Max: %.12e",(*func)(p));
2386: fprintf(ficlog,"Max: %.12e",(*func)(p));
2387: for (j=1;j<=n;j++) {
2388: printf(" %.12e",p[j]);
2389: fprintf(ficlog," %.12e",p[j]);
2390: }
2391: printf("\n");
2392: fprintf(ficlog,"\n");
2393: for(l=0;l<=1;l++) {
2394: for (j=1;j<=n;j++) {
2395: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2396: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2397: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2398: }
2399: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2400: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2401: }
2402: #endif
2403:
1.224 brouard 2404: #ifdef LINMINORIGINAL
2405: #else
2406: free_ivector(flatdir,1,n);
2407: #endif
1.126 brouard 2408: free_vector(xit,1,n);
2409: free_vector(xits,1,n);
2410: free_vector(ptt,1,n);
2411: free_vector(pt,1,n);
2412: return;
1.192 brouard 2413: } /* enough precision */
1.240 brouard 2414: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2415: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2416: ptt[j]=2.0*p[j]-pt[j];
2417: xit[j]=p[j]-pt[j];
2418: pt[j]=p[j];
2419: }
1.181 brouard 2420: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2421: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2422: if (*iter <=4) {
1.225 brouard 2423: #else
2424: #endif
1.224 brouard 2425: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2426: #else
1.161 brouard 2427: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2428: #endif
1.162 brouard 2429: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2430: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2431: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2432: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2433: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2434: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2435: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2436: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2437: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2438: /* Even if f3 <f1, directest can be negative and t >0 */
2439: /* mu² and del² are equal when f3=f1 */
2440: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2441: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2442: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2443: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2444: #ifdef NRCORIGINAL
2445: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2446: #else
2447: 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 2448: t= t- del*SQR(fp-fptt);
1.183 brouard 2449: #endif
1.202 brouard 2450: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2451: #ifdef DEBUG
1.181 brouard 2452: 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);
2453: 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 2454: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2455: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2456: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2457: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2458: 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);
2459: 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);
2460: #endif
1.183 brouard 2461: #ifdef POWELLORIGINAL
2462: if (t < 0.0) { /* Then we use it for new direction */
2463: #else
1.182 brouard 2464: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2465: 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 2466: 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 2467: 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 2468: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2469: }
1.181 brouard 2470: if (directest < 0.0) { /* Then we use it for new direction */
2471: #endif
1.191 brouard 2472: #ifdef DEBUGLINMIN
1.234 brouard 2473: printf("Before linmin in direction P%d-P0\n",n);
2474: for (j=1;j<=n;j++) {
2475: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2476: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2477: if(j % ncovmodel == 0){
2478: printf("\n");
2479: fprintf(ficlog,"\n");
2480: }
2481: }
1.224 brouard 2482: #endif
2483: #ifdef LINMINORIGINAL
1.234 brouard 2484: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2485: #else
1.234 brouard 2486: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2487: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2488: #endif
1.234 brouard 2489:
1.191 brouard 2490: #ifdef DEBUGLINMIN
1.234 brouard 2491: for (j=1;j<=n;j++) {
2492: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2493: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2494: if(j % ncovmodel == 0){
2495: printf("\n");
2496: fprintf(ficlog,"\n");
2497: }
2498: }
1.224 brouard 2499: #endif
1.234 brouard 2500: for (j=1;j<=n;j++) {
2501: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2502: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2503: }
1.224 brouard 2504: #ifdef LINMINORIGINAL
2505: #else
1.234 brouard 2506: for (j=1, flatd=0;j<=n;j++) {
2507: if(flatdir[j]>0)
2508: flatd++;
2509: }
2510: if(flatd >0){
1.255 brouard 2511: printf("%d flat directions: ",flatd);
2512: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2513: for (j=1;j<=n;j++) {
2514: if(flatdir[j]>0){
2515: printf("%d ",j);
2516: fprintf(ficlog,"%d ",j);
2517: }
2518: }
2519: printf("\n");
2520: fprintf(ficlog,"\n");
2521: }
1.191 brouard 2522: #endif
1.234 brouard 2523: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2524: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2525:
1.126 brouard 2526: #ifdef DEBUG
1.234 brouard 2527: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2528: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2529: for(j=1;j<=n;j++){
2530: printf(" %lf",xit[j]);
2531: fprintf(ficlog," %lf",xit[j]);
2532: }
2533: printf("\n");
2534: fprintf(ficlog,"\n");
1.126 brouard 2535: #endif
1.192 brouard 2536: } /* end of t or directest negative */
1.224 brouard 2537: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2538: #else
1.234 brouard 2539: } /* end if (fptt < fp) */
1.192 brouard 2540: #endif
1.225 brouard 2541: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2542: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2543: #else
1.224 brouard 2544: #endif
1.234 brouard 2545: } /* loop iteration */
1.126 brouard 2546: }
1.234 brouard 2547:
1.126 brouard 2548: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2549:
1.235 brouard 2550: 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 2551: {
1.279 brouard 2552: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2553: * (and selected quantitative values in nres)
2554: * by left multiplying the unit
2555: * matrix by transitions matrix until convergence is reached with precision ftolpl
2556: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2557: * Wx is row vector: population in state 1, population in state 2, population dead
2558: * or prevalence in state 1, prevalence in state 2, 0
2559: * newm is the matrix after multiplications, its rows are identical at a factor.
2560: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2561: * Output is prlim.
2562: * Initial matrix pimij
2563: */
1.206 brouard 2564: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2565: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2566: /* 0, 0 , 1} */
2567: /*
2568: * and after some iteration: */
2569: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2570: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2571: /* 0, 0 , 1} */
2572: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2573: /* {0.51571254859325999, 0.4842874514067399, */
2574: /* 0.51326036147820708, 0.48673963852179264} */
2575: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2576:
1.126 brouard 2577: int i, ii,j,k;
1.209 brouard 2578: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2579: /* double **matprod2(); */ /* test */
1.218 brouard 2580: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2581: double **newm;
1.209 brouard 2582: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2583: int ncvloop=0;
1.288 brouard 2584: int first=0;
1.169 brouard 2585:
1.209 brouard 2586: min=vector(1,nlstate);
2587: max=vector(1,nlstate);
2588: meandiff=vector(1,nlstate);
2589:
1.218 brouard 2590: /* Starting with matrix unity */
1.126 brouard 2591: for (ii=1;ii<=nlstate+ndeath;ii++)
2592: for (j=1;j<=nlstate+ndeath;j++){
2593: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2594: }
1.169 brouard 2595:
2596: cov[1]=1.;
2597:
2598: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2599: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2600: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2601: ncvloop++;
1.126 brouard 2602: newm=savm;
2603: /* Covariates have to be included here again */
1.138 brouard 2604: cov[2]=agefin;
1.187 brouard 2605: if(nagesqr==1)
2606: cov[3]= agefin*agefin;;
1.234 brouard 2607: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2608: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2609: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2610: /* 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 2611: }
2612: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2613: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2614: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2615: /* 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 2616: }
1.237 brouard 2617: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2618: if(Dummy[Tvar[Tage[k]]]){
2619: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2620: } else{
1.235 brouard 2621: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2622: }
1.235 brouard 2623: /* 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 2624: }
1.237 brouard 2625: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2626: /* 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 2627: if(Dummy[Tvard[k][1]==0]){
2628: if(Dummy[Tvard[k][2]==0]){
2629: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2630: }else{
2631: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2632: }
2633: }else{
2634: if(Dummy[Tvard[k][2]==0]){
2635: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2636: }else{
2637: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2638: }
2639: }
1.234 brouard 2640: }
1.138 brouard 2641: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2642: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2643: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2644: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2645: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2646: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2647: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2648:
1.126 brouard 2649: savm=oldm;
2650: oldm=newm;
1.209 brouard 2651:
2652: for(j=1; j<=nlstate; j++){
2653: max[j]=0.;
2654: min[j]=1.;
2655: }
2656: for(i=1;i<=nlstate;i++){
2657: sumnew=0;
2658: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2659: for(j=1; j<=nlstate; j++){
2660: prlim[i][j]= newm[i][j]/(1-sumnew);
2661: max[j]=FMAX(max[j],prlim[i][j]);
2662: min[j]=FMIN(min[j],prlim[i][j]);
2663: }
2664: }
2665:
1.126 brouard 2666: maxmax=0.;
1.209 brouard 2667: for(j=1; j<=nlstate; j++){
2668: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2669: maxmax=FMAX(maxmax,meandiff[j]);
2670: /* 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 2671: } /* j loop */
1.203 brouard 2672: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2673: /* 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 2674: if(maxmax < ftolpl){
1.209 brouard 2675: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2676: free_vector(min,1,nlstate);
2677: free_vector(max,1,nlstate);
2678: free_vector(meandiff,1,nlstate);
1.126 brouard 2679: return prlim;
2680: }
1.288 brouard 2681: } /* agefin loop */
1.208 brouard 2682: /* After some age loop it doesn't converge */
1.288 brouard 2683: if(!first){
2684: first=1;
2685: 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);
2686: }
2687: 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);
2688:
1.209 brouard 2689: /* 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); */
2690: free_vector(min,1,nlstate);
2691: free_vector(max,1,nlstate);
2692: free_vector(meandiff,1,nlstate);
1.208 brouard 2693:
1.169 brouard 2694: return prlim; /* should not reach here */
1.126 brouard 2695: }
2696:
1.217 brouard 2697:
2698: /**** Back Prevalence limit (stable or period prevalence) ****************/
2699:
1.218 brouard 2700: /* 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) */
2701: /* 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 2702: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2703: {
1.264 brouard 2704: /* 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 2705: matrix by transitions matrix until convergence is reached with precision ftolpl */
2706: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2707: /* Wx is row vector: population in state 1, population in state 2, population dead */
2708: /* or prevalence in state 1, prevalence in state 2, 0 */
2709: /* newm is the matrix after multiplications, its rows are identical at a factor */
2710: /* Initial matrix pimij */
2711: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2712: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2713: /* 0, 0 , 1} */
2714: /*
2715: * and after some iteration: */
2716: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2717: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2718: /* 0, 0 , 1} */
2719: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2720: /* {0.51571254859325999, 0.4842874514067399, */
2721: /* 0.51326036147820708, 0.48673963852179264} */
2722: /* If we start from prlim again, prlim tends to a constant matrix */
2723:
2724: int i, ii,j,k;
1.247 brouard 2725: int first=0;
1.217 brouard 2726: double *min, *max, *meandiff, maxmax,sumnew=0.;
2727: /* double **matprod2(); */ /* test */
2728: double **out, cov[NCOVMAX+1], **bmij();
2729: double **newm;
1.218 brouard 2730: double **dnewm, **doldm, **dsavm; /* for use */
2731: double **oldm, **savm; /* for use */
2732:
1.217 brouard 2733: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2734: int ncvloop=0;
2735:
2736: min=vector(1,nlstate);
2737: max=vector(1,nlstate);
2738: meandiff=vector(1,nlstate);
2739:
1.266 brouard 2740: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2741: oldm=oldms; savm=savms;
2742:
2743: /* Starting with matrix unity */
2744: for (ii=1;ii<=nlstate+ndeath;ii++)
2745: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2746: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2747: }
2748:
2749: cov[1]=1.;
2750:
2751: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2752: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2753: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 2754: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2755: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2756: ncvloop++;
1.218 brouard 2757: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2758: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2759: /* Covariates have to be included here again */
2760: cov[2]=agefin;
2761: if(nagesqr==1)
2762: cov[3]= agefin*agefin;;
1.242 brouard 2763: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2764: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2765: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2766: /* 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 2767: }
2768: /* for (k=1; k<=cptcovn;k++) { */
2769: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2770: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2771: /* /\* 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])]); *\/ */
2772: /* } */
2773: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2774: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2775: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2776: /* 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]); */
2777: }
2778: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2779: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2780: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2781: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2782: for (k=1; k<=cptcovage;k++){ /* For product with age */
2783: if(Dummy[Tvar[Tage[k]]]){
2784: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2785: } else{
2786: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2787: }
2788: /* 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]); */
2789: }
2790: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2791: /* 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]); */
2792: if(Dummy[Tvard[k][1]==0]){
2793: if(Dummy[Tvard[k][2]==0]){
2794: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2795: }else{
2796: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2797: }
2798: }else{
2799: if(Dummy[Tvard[k][2]==0]){
2800: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2801: }else{
2802: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2803: }
2804: }
1.217 brouard 2805: }
2806:
2807: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2808: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2809: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2810: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2811: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2812: /* ij should be linked to the correct index of cov */
2813: /* age and covariate values ij are in 'cov', but we need to pass
2814: * ij for the observed prevalence at age and status and covariate
2815: * number: prevacurrent[(int)agefin][ii][ij]
2816: */
2817: /* 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 *\/ */
2818: /* 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 *\/ */
2819: 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 2820: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2821: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2822: /* for(i=1; i<=nlstate+ndeath; i++) { */
2823: /* printf("%d newm= ",i); */
2824: /* for(j=1;j<=nlstate+ndeath;j++) { */
2825: /* printf("%f ",newm[i][j]); */
2826: /* } */
2827: /* printf("oldm * "); */
2828: /* for(j=1;j<=nlstate+ndeath;j++) { */
2829: /* printf("%f ",oldm[i][j]); */
2830: /* } */
1.268 brouard 2831: /* printf(" bmmij "); */
1.266 brouard 2832: /* for(j=1;j<=nlstate+ndeath;j++) { */
2833: /* printf("%f ",pmmij[i][j]); */
2834: /* } */
2835: /* printf("\n"); */
2836: /* } */
2837: /* } */
1.217 brouard 2838: savm=oldm;
2839: oldm=newm;
1.266 brouard 2840:
1.217 brouard 2841: for(j=1; j<=nlstate; j++){
2842: max[j]=0.;
2843: min[j]=1.;
2844: }
2845: for(j=1; j<=nlstate; j++){
2846: for(i=1;i<=nlstate;i++){
1.234 brouard 2847: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2848: bprlim[i][j]= newm[i][j];
2849: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2850: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2851: }
2852: }
1.218 brouard 2853:
1.217 brouard 2854: maxmax=0.;
2855: for(i=1; i<=nlstate; i++){
2856: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2857: maxmax=FMAX(maxmax,meandiff[i]);
2858: /* 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 2859: } /* i loop */
1.217 brouard 2860: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 2861: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2862: if(maxmax < ftolpl){
1.220 brouard 2863: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2864: free_vector(min,1,nlstate);
2865: free_vector(max,1,nlstate);
2866: free_vector(meandiff,1,nlstate);
2867: return bprlim;
2868: }
1.288 brouard 2869: } /* agefin loop */
1.217 brouard 2870: /* After some age loop it doesn't converge */
1.288 brouard 2871: if(!first){
1.247 brouard 2872: first=1;
2873: 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\
2874: 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);
2875: }
2876: 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 2877: 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);
2878: /* 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); */
2879: free_vector(min,1,nlstate);
2880: free_vector(max,1,nlstate);
2881: free_vector(meandiff,1,nlstate);
2882:
2883: return bprlim; /* should not reach here */
2884: }
2885:
1.126 brouard 2886: /*************** transition probabilities ***************/
2887:
2888: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2889: {
1.138 brouard 2890: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2891: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2892: model to the ncovmodel covariates (including constant and age).
2893: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2894: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2895: ncth covariate in the global vector x is given by the formula:
2896: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2897: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2898: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2899: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 2900: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 2901: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 2902: Sum on j ps[i][j] should equal to 1.
1.138 brouard 2903: */
2904: double s1, lnpijopii;
1.126 brouard 2905: /*double t34;*/
1.164 brouard 2906: int i,j, nc, ii, jj;
1.126 brouard 2907:
1.223 brouard 2908: for(i=1; i<= nlstate; i++){
2909: for(j=1; j<i;j++){
2910: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2911: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2912: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2913: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2914: }
2915: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2916: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2917: }
2918: for(j=i+1; j<=nlstate+ndeath;j++){
2919: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2920: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2921: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2922: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2923: }
2924: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2925: }
2926: }
1.218 brouard 2927:
1.223 brouard 2928: for(i=1; i<= nlstate; i++){
2929: s1=0;
2930: for(j=1; j<i; j++){
2931: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2932: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2933: }
2934: for(j=i+1; j<=nlstate+ndeath; j++){
2935: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2936: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2937: }
2938: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2939: ps[i][i]=1./(s1+1.);
2940: /* Computing other pijs */
2941: for(j=1; j<i; j++)
2942: ps[i][j]= exp(ps[i][j])*ps[i][i];
2943: for(j=i+1; j<=nlstate+ndeath; j++)
2944: ps[i][j]= exp(ps[i][j])*ps[i][i];
2945: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2946: } /* end i */
1.218 brouard 2947:
1.223 brouard 2948: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2949: for(jj=1; jj<= nlstate+ndeath; jj++){
2950: ps[ii][jj]=0;
2951: ps[ii][ii]=1;
2952: }
2953: }
1.218 brouard 2954:
2955:
1.223 brouard 2956: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2957: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2958: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2959: /* } */
2960: /* printf("\n "); */
2961: /* } */
2962: /* printf("\n ");printf("%lf ",cov[2]);*/
2963: /*
2964: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2965: goto end;*/
1.266 brouard 2966: return ps; /* Pointer is unchanged since its call */
1.126 brouard 2967: }
2968:
1.218 brouard 2969: /*************** backward transition probabilities ***************/
2970:
2971: /* 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 ) */
2972: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2973: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
2974: {
1.266 brouard 2975: /* Computes the backward probability at age agefin and covariate combination ij. In fact cov is already filled and x too.
2976: * 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 2977: */
1.218 brouard 2978: int i, ii, j,k;
1.222 brouard 2979:
2980: double **out, **pmij();
2981: double sumnew=0.;
1.218 brouard 2982: double agefin;
1.268 brouard 2983: 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 2984: double **dnewm, **dsavm, **doldm;
2985: double **bbmij;
2986:
1.218 brouard 2987: doldm=ddoldms; /* global pointers */
1.222 brouard 2988: dnewm=ddnewms;
2989: dsavm=ddsavms;
2990:
2991: agefin=cov[2];
1.268 brouard 2992: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 2993: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 2994: the observed prevalence (with this covariate ij) at beginning of transition */
2995: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 2996:
2997: /* P_x */
1.266 brouard 2998: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 2999: /* outputs pmmij which is a stochastic matrix in row */
3000:
3001: /* Diag(w_x) */
3002: /* Problem with prevacurrent which can be zero */
3003: sumnew=0.;
1.269 brouard 3004: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3005: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.269 brouard 3006: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3007: sumnew+=prevacurrent[(int)agefin][ii][ij];
3008: }
3009: if(sumnew >0.01){ /* At least some value in the prevalence */
3010: for (ii=1;ii<=nlstate+ndeath;ii++){
3011: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3012: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3013: }
3014: }else{
3015: for (ii=1;ii<=nlstate+ndeath;ii++){
3016: for (j=1;j<=nlstate+ndeath;j++)
3017: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3018: }
3019: /* if(sumnew <0.9){ */
3020: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3021: /* } */
3022: }
3023: k3=0.0; /* We put the last diagonal to 0 */
3024: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3025: doldm[ii][ii]= k3;
3026: }
3027: /* End doldm, At the end doldm is diag[(w_i)] */
3028:
3029: /* left Product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm) */
3030: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* Bug Valgrind */
3031:
3032: /* Diag(Sum_i w^i_x p^ij_x */
3033: /* 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 3034: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3035: sumnew=0.;
1.222 brouard 3036: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3037: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3038: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3039: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3040: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3041: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3042: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3043: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3044: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3045: /* }else */
1.268 brouard 3046: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3047: } /*End ii */
3048: } /* 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 */
3049:
3050: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* Bug Valgrind */
3051: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3052: /* end bmij */
1.266 brouard 3053: return ps; /*pointer is unchanged */
1.218 brouard 3054: }
1.217 brouard 3055: /*************** transition probabilities ***************/
3056:
1.218 brouard 3057: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3058: {
3059: /* According to parameters values stored in x and the covariate's values stored in cov,
3060: computes the probability to be observed in state j being in state i by appying the
3061: model to the ncovmodel covariates (including constant and age).
3062: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3063: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3064: ncth covariate in the global vector x is given by the formula:
3065: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3066: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3067: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3068: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3069: Outputs ps[i][j] the probability to be observed in j being in j according to
3070: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3071: */
3072: double s1, lnpijopii;
3073: /*double t34;*/
3074: int i,j, nc, ii, jj;
3075:
1.234 brouard 3076: for(i=1; i<= nlstate; i++){
3077: for(j=1; j<i;j++){
3078: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3079: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3080: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3081: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3082: }
3083: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3084: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3085: }
3086: for(j=i+1; j<=nlstate+ndeath;j++){
3087: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3088: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3089: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3090: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3091: }
3092: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3093: }
3094: }
3095:
3096: for(i=1; i<= nlstate; i++){
3097: s1=0;
3098: for(j=1; j<i; j++){
3099: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3100: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3101: }
3102: for(j=i+1; j<=nlstate+ndeath; j++){
3103: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3104: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3105: }
3106: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3107: ps[i][i]=1./(s1+1.);
3108: /* Computing other pijs */
3109: for(j=1; j<i; j++)
3110: ps[i][j]= exp(ps[i][j])*ps[i][i];
3111: for(j=i+1; j<=nlstate+ndeath; j++)
3112: ps[i][j]= exp(ps[i][j])*ps[i][i];
3113: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3114: } /* end i */
3115:
3116: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3117: for(jj=1; jj<= nlstate+ndeath; jj++){
3118: ps[ii][jj]=0;
3119: ps[ii][ii]=1;
3120: }
3121: }
3122: /* Added for backcast */ /* Transposed matrix too */
3123: for(jj=1; jj<= nlstate+ndeath; jj++){
3124: s1=0.;
3125: for(ii=1; ii<= nlstate+ndeath; ii++){
3126: s1+=ps[ii][jj];
3127: }
3128: for(ii=1; ii<= nlstate; ii++){
3129: ps[ii][jj]=ps[ii][jj]/s1;
3130: }
3131: }
3132: /* Transposition */
3133: for(jj=1; jj<= nlstate+ndeath; jj++){
3134: for(ii=jj; ii<= nlstate+ndeath; ii++){
3135: s1=ps[ii][jj];
3136: ps[ii][jj]=ps[jj][ii];
3137: ps[jj][ii]=s1;
3138: }
3139: }
3140: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3141: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3142: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3143: /* } */
3144: /* printf("\n "); */
3145: /* } */
3146: /* printf("\n ");printf("%lf ",cov[2]);*/
3147: /*
3148: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3149: goto end;*/
3150: return ps;
1.217 brouard 3151: }
3152:
3153:
1.126 brouard 3154: /**************** Product of 2 matrices ******************/
3155:
1.145 brouard 3156: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3157: {
3158: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3159: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3160: /* in, b, out are matrice of pointers which should have been initialized
3161: before: only the contents of out is modified. The function returns
3162: a pointer to pointers identical to out */
1.145 brouard 3163: int i, j, k;
1.126 brouard 3164: for(i=nrl; i<= nrh; i++)
1.145 brouard 3165: for(k=ncolol; k<=ncoloh; k++){
3166: out[i][k]=0.;
3167: for(j=ncl; j<=nch; j++)
3168: out[i][k] +=in[i][j]*b[j][k];
3169: }
1.126 brouard 3170: return out;
3171: }
3172:
3173:
3174: /************* Higher Matrix Product ***************/
3175:
1.235 brouard 3176: 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 3177: {
1.218 brouard 3178: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3179: 'nhstepm*hstepm*stepm' months (i.e. until
3180: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3181: nhstepm*hstepm matrices.
3182: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3183: (typically every 2 years instead of every month which is too big
3184: for the memory).
3185: Model is determined by parameters x and covariates have to be
3186: included manually here.
3187:
3188: */
3189:
3190: int i, j, d, h, k;
1.131 brouard 3191: double **out, cov[NCOVMAX+1];
1.126 brouard 3192: double **newm;
1.187 brouard 3193: double agexact;
1.214 brouard 3194: double agebegin, ageend;
1.126 brouard 3195:
3196: /* Hstepm could be zero and should return the unit matrix */
3197: for (i=1;i<=nlstate+ndeath;i++)
3198: for (j=1;j<=nlstate+ndeath;j++){
3199: oldm[i][j]=(i==j ? 1.0 : 0.0);
3200: po[i][j][0]=(i==j ? 1.0 : 0.0);
3201: }
3202: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3203: for(h=1; h <=nhstepm; h++){
3204: for(d=1; d <=hstepm; d++){
3205: newm=savm;
3206: /* Covariates have to be included here again */
3207: cov[1]=1.;
1.214 brouard 3208: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3209: cov[2]=agexact;
3210: if(nagesqr==1)
1.227 brouard 3211: cov[3]= agexact*agexact;
1.235 brouard 3212: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3213: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3214: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3215: /* 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)); */
3216: }
3217: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3218: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3219: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3220: /* 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]); */
3221: }
3222: for (k=1; k<=cptcovage;k++){
3223: if(Dummy[Tvar[Tage[k]]]){
3224: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3225: } else{
3226: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3227: }
3228: /* 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]); */
3229: }
3230: for (k=1; k<=cptcovprod;k++){ /* */
3231: /* 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]); */
3232: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3233: }
3234: /* for (k=1; k<=cptcovn;k++) */
3235: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3236: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3237: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3238: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3239: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3240:
3241:
1.126 brouard 3242: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3243: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3244: /* right multiplication of oldm by the current matrix */
1.126 brouard 3245: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3246: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3247: /* if((int)age == 70){ */
3248: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3249: /* for(i=1; i<=nlstate+ndeath; i++) { */
3250: /* printf("%d pmmij ",i); */
3251: /* for(j=1;j<=nlstate+ndeath;j++) { */
3252: /* printf("%f ",pmmij[i][j]); */
3253: /* } */
3254: /* printf(" oldm "); */
3255: /* for(j=1;j<=nlstate+ndeath;j++) { */
3256: /* printf("%f ",oldm[i][j]); */
3257: /* } */
3258: /* printf("\n"); */
3259: /* } */
3260: /* } */
1.126 brouard 3261: savm=oldm;
3262: oldm=newm;
3263: }
3264: for(i=1; i<=nlstate+ndeath; i++)
3265: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3266: po[i][j][h]=newm[i][j];
3267: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3268: }
1.128 brouard 3269: /*printf("h=%d ",h);*/
1.126 brouard 3270: } /* end h */
1.267 brouard 3271: /* printf("\n H=%d \n",h); */
1.126 brouard 3272: return po;
3273: }
3274:
1.217 brouard 3275: /************* Higher Back Matrix Product ***************/
1.218 brouard 3276: /* 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 3277: 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 3278: {
1.266 brouard 3279: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3280: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3281: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3282: nhstepm*hstepm matrices.
3283: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3284: (typically every 2 years instead of every month which is too big
1.217 brouard 3285: for the memory).
1.218 brouard 3286: Model is determined by parameters x and covariates have to be
1.266 brouard 3287: included manually here. Then we use a call to bmij(x and cov)
3288: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3289: */
1.217 brouard 3290:
3291: int i, j, d, h, k;
1.266 brouard 3292: double **out, cov[NCOVMAX+1], **bmij();
3293: double **newm, ***newmm;
1.217 brouard 3294: double agexact;
3295: double agebegin, ageend;
1.222 brouard 3296: double **oldm, **savm;
1.217 brouard 3297:
1.266 brouard 3298: newmm=po; /* To be saved */
3299: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3300: /* Hstepm could be zero and should return the unit matrix */
3301: for (i=1;i<=nlstate+ndeath;i++)
3302: for (j=1;j<=nlstate+ndeath;j++){
3303: oldm[i][j]=(i==j ? 1.0 : 0.0);
3304: po[i][j][0]=(i==j ? 1.0 : 0.0);
3305: }
3306: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3307: for(h=1; h <=nhstepm; h++){
3308: for(d=1; d <=hstepm; d++){
3309: newm=savm;
3310: /* Covariates have to be included here again */
3311: cov[1]=1.;
1.271 brouard 3312: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3313: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3314: cov[2]=agexact;
3315: if(nagesqr==1)
1.222 brouard 3316: cov[3]= agexact*agexact;
1.266 brouard 3317: for (k=1; k<=cptcovn;k++){
3318: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3319: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3320: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3321: /* 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)); */
3322: }
1.267 brouard 3323: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3324: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3325: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3326: /* 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]); */
3327: }
3328: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3329: if(Dummy[Tvar[Tage[k]]]){
3330: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3331: } else{
3332: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3333: }
3334: /* 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]); */
3335: }
3336: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3337: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3338: }
1.217 brouard 3339: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3340: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3341:
1.218 brouard 3342: /* Careful transposed matrix */
1.266 brouard 3343: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3344: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3345: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3346: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3347: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3348: /* if((int)age == 70){ */
3349: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3350: /* for(i=1; i<=nlstate+ndeath; i++) { */
3351: /* printf("%d pmmij ",i); */
3352: /* for(j=1;j<=nlstate+ndeath;j++) { */
3353: /* printf("%f ",pmmij[i][j]); */
3354: /* } */
3355: /* printf(" oldm "); */
3356: /* for(j=1;j<=nlstate+ndeath;j++) { */
3357: /* printf("%f ",oldm[i][j]); */
3358: /* } */
3359: /* printf("\n"); */
3360: /* } */
3361: /* } */
3362: savm=oldm;
3363: oldm=newm;
3364: }
3365: for(i=1; i<=nlstate+ndeath; i++)
3366: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3367: po[i][j][h]=newm[i][j];
1.268 brouard 3368: /* if(h==nhstepm) */
3369: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3370: }
1.268 brouard 3371: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3372: } /* end h */
1.268 brouard 3373: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3374: return po;
3375: }
3376:
3377:
1.162 brouard 3378: #ifdef NLOPT
3379: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3380: double fret;
3381: double *xt;
3382: int j;
3383: myfunc_data *d2 = (myfunc_data *) pd;
3384: /* xt = (p1-1); */
3385: xt=vector(1,n);
3386: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3387:
3388: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3389: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3390: printf("Function = %.12lf ",fret);
3391: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3392: printf("\n");
3393: free_vector(xt,1,n);
3394: return fret;
3395: }
3396: #endif
1.126 brouard 3397:
3398: /*************** log-likelihood *************/
3399: double func( double *x)
3400: {
1.226 brouard 3401: int i, ii, j, k, mi, d, kk;
3402: int ioffset=0;
3403: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3404: double **out;
3405: double lli; /* Individual log likelihood */
3406: int s1, s2;
1.228 brouard 3407: 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 3408: double bbh, survp;
3409: long ipmx;
3410: double agexact;
3411: /*extern weight */
3412: /* We are differentiating ll according to initial status */
3413: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3414: /*for(i=1;i<imx;i++)
3415: printf(" %d\n",s[4][i]);
3416: */
1.162 brouard 3417:
1.226 brouard 3418: ++countcallfunc;
1.162 brouard 3419:
1.226 brouard 3420: cov[1]=1.;
1.126 brouard 3421:
1.226 brouard 3422: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3423: ioffset=0;
1.226 brouard 3424: if(mle==1){
3425: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3426: /* Computes the values of the ncovmodel covariates of the model
3427: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3428: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3429: to be observed in j being in i according to the model.
3430: */
1.243 brouard 3431: ioffset=2+nagesqr ;
1.233 brouard 3432: /* Fixed */
1.234 brouard 3433: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3434: 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)*/
3435: }
1.226 brouard 3436: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3437: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3438: has been calculated etc */
3439: /* For an individual i, wav[i] gives the number of effective waves */
3440: /* We compute the contribution to Likelihood of each effective transition
3441: mw[mi][i] is real wave of the mi th effectve wave */
3442: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3443: s2=s[mw[mi+1][i]][i];
3444: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3445: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3446: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3447: */
3448: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3449: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3450: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3451: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3452: }
3453: for (ii=1;ii<=nlstate+ndeath;ii++)
3454: for (j=1;j<=nlstate+ndeath;j++){
3455: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3456: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3457: }
3458: for(d=0; d<dh[mi][i]; d++){
3459: newm=savm;
3460: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3461: cov[2]=agexact;
3462: if(nagesqr==1)
3463: cov[3]= agexact*agexact; /* Should be changed here */
3464: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3465: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3466: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3467: else
3468: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3469: }
3470: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3471: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3472: savm=oldm;
3473: oldm=newm;
3474: } /* end mult */
3475:
3476: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3477: /* But now since version 0.9 we anticipate for bias at large stepm.
3478: * If stepm is larger than one month (smallest stepm) and if the exact delay
3479: * (in months) between two waves is not a multiple of stepm, we rounded to
3480: * the nearest (and in case of equal distance, to the lowest) interval but now
3481: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3482: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3483: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3484: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3485: * -stepm/2 to stepm/2 .
3486: * For stepm=1 the results are the same as for previous versions of Imach.
3487: * For stepm > 1 the results are less biased than in previous versions.
3488: */
1.234 brouard 3489: s1=s[mw[mi][i]][i];
3490: s2=s[mw[mi+1][i]][i];
3491: bbh=(double)bh[mi][i]/(double)stepm;
3492: /* bias bh is positive if real duration
3493: * is higher than the multiple of stepm and negative otherwise.
3494: */
3495: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3496: if( s2 > nlstate){
3497: /* i.e. if s2 is a death state and if the date of death is known
3498: then the contribution to the likelihood is the probability to
3499: die between last step unit time and current step unit time,
3500: which is also equal to probability to die before dh
3501: minus probability to die before dh-stepm .
3502: In version up to 0.92 likelihood was computed
3503: as if date of death was unknown. Death was treated as any other
3504: health state: the date of the interview describes the actual state
3505: and not the date of a change in health state. The former idea was
3506: to consider that at each interview the state was recorded
3507: (healthy, disable or death) and IMaCh was corrected; but when we
3508: introduced the exact date of death then we should have modified
3509: the contribution of an exact death to the likelihood. This new
3510: contribution is smaller and very dependent of the step unit
3511: stepm. It is no more the probability to die between last interview
3512: and month of death but the probability to survive from last
3513: interview up to one month before death multiplied by the
3514: probability to die within a month. Thanks to Chris
3515: Jackson for correcting this bug. Former versions increased
3516: mortality artificially. The bad side is that we add another loop
3517: which slows down the processing. The difference can be up to 10%
3518: lower mortality.
3519: */
3520: /* If, at the beginning of the maximization mostly, the
3521: cumulative probability or probability to be dead is
3522: constant (ie = 1) over time d, the difference is equal to
3523: 0. out[s1][3] = savm[s1][3]: probability, being at state
3524: s1 at precedent wave, to be dead a month before current
3525: wave is equal to probability, being at state s1 at
3526: precedent wave, to be dead at mont of the current
3527: wave. Then the observed probability (that this person died)
3528: is null according to current estimated parameter. In fact,
3529: it should be very low but not zero otherwise the log go to
3530: infinity.
3531: */
1.183 brouard 3532: /* #ifdef INFINITYORIGINAL */
3533: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3534: /* #else */
3535: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3536: /* lli=log(mytinydouble); */
3537: /* else */
3538: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3539: /* #endif */
1.226 brouard 3540: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3541:
1.226 brouard 3542: } else if ( s2==-1 ) { /* alive */
3543: for (j=1,survp=0. ; j<=nlstate; j++)
3544: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3545: /*survp += out[s1][j]; */
3546: lli= log(survp);
3547: }
3548: else if (s2==-4) {
3549: for (j=3,survp=0. ; j<=nlstate; j++)
3550: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3551: lli= log(survp);
3552: }
3553: else if (s2==-5) {
3554: for (j=1,survp=0. ; j<=2; j++)
3555: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3556: lli= log(survp);
3557: }
3558: else{
3559: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3560: /* 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 */
3561: }
3562: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3563: /*if(lli ==000.0)*/
3564: /*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); */
3565: ipmx +=1;
3566: sw += weight[i];
3567: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3568: /* if (lli < log(mytinydouble)){ */
3569: /* 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); */
3570: /* 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]); */
3571: /* } */
3572: } /* end of wave */
3573: } /* end of individual */
3574: } else if(mle==2){
3575: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3576: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3577: for(mi=1; mi<= wav[i]-1; mi++){
3578: for (ii=1;ii<=nlstate+ndeath;ii++)
3579: for (j=1;j<=nlstate+ndeath;j++){
3580: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3581: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3582: }
3583: for(d=0; d<=dh[mi][i]; d++){
3584: newm=savm;
3585: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3586: cov[2]=agexact;
3587: if(nagesqr==1)
3588: cov[3]= agexact*agexact;
3589: for (kk=1; kk<=cptcovage;kk++) {
3590: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3591: }
3592: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3593: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3594: savm=oldm;
3595: oldm=newm;
3596: } /* end mult */
3597:
3598: s1=s[mw[mi][i]][i];
3599: s2=s[mw[mi+1][i]][i];
3600: bbh=(double)bh[mi][i]/(double)stepm;
3601: 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 */
3602: ipmx +=1;
3603: sw += weight[i];
3604: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3605: } /* end of wave */
3606: } /* end of individual */
3607: } else if(mle==3){ /* exponential inter-extrapolation */
3608: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3609: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3610: for(mi=1; mi<= wav[i]-1; mi++){
3611: for (ii=1;ii<=nlstate+ndeath;ii++)
3612: for (j=1;j<=nlstate+ndeath;j++){
3613: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3614: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3615: }
3616: for(d=0; d<dh[mi][i]; d++){
3617: newm=savm;
3618: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3619: cov[2]=agexact;
3620: if(nagesqr==1)
3621: cov[3]= agexact*agexact;
3622: for (kk=1; kk<=cptcovage;kk++) {
3623: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3624: }
3625: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3626: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3627: savm=oldm;
3628: oldm=newm;
3629: } /* end mult */
3630:
3631: s1=s[mw[mi][i]][i];
3632: s2=s[mw[mi+1][i]][i];
3633: bbh=(double)bh[mi][i]/(double)stepm;
3634: 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 */
3635: ipmx +=1;
3636: sw += weight[i];
3637: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3638: } /* end of wave */
3639: } /* end of individual */
3640: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3641: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3642: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3643: for(mi=1; mi<= wav[i]-1; mi++){
3644: for (ii=1;ii<=nlstate+ndeath;ii++)
3645: for (j=1;j<=nlstate+ndeath;j++){
3646: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3647: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3648: }
3649: for(d=0; d<dh[mi][i]; d++){
3650: newm=savm;
3651: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3652: cov[2]=agexact;
3653: if(nagesqr==1)
3654: cov[3]= agexact*agexact;
3655: for (kk=1; kk<=cptcovage;kk++) {
3656: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3657: }
1.126 brouard 3658:
1.226 brouard 3659: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3660: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3661: savm=oldm;
3662: oldm=newm;
3663: } /* end mult */
3664:
3665: s1=s[mw[mi][i]][i];
3666: s2=s[mw[mi+1][i]][i];
3667: if( s2 > nlstate){
3668: lli=log(out[s1][s2] - savm[s1][s2]);
3669: } else if ( s2==-1 ) { /* alive */
3670: for (j=1,survp=0. ; j<=nlstate; j++)
3671: survp += out[s1][j];
3672: lli= log(survp);
3673: }else{
3674: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3675: }
3676: ipmx +=1;
3677: sw += weight[i];
3678: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3679: /* 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 3680: } /* end of wave */
3681: } /* end of individual */
3682: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3683: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3684: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3685: for(mi=1; mi<= wav[i]-1; mi++){
3686: for (ii=1;ii<=nlstate+ndeath;ii++)
3687: for (j=1;j<=nlstate+ndeath;j++){
3688: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3689: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3690: }
3691: for(d=0; d<dh[mi][i]; d++){
3692: newm=savm;
3693: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3694: cov[2]=agexact;
3695: if(nagesqr==1)
3696: cov[3]= agexact*agexact;
3697: for (kk=1; kk<=cptcovage;kk++) {
3698: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3699: }
1.126 brouard 3700:
1.226 brouard 3701: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3702: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3703: savm=oldm;
3704: oldm=newm;
3705: } /* end mult */
3706:
3707: s1=s[mw[mi][i]][i];
3708: s2=s[mw[mi+1][i]][i];
3709: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3710: ipmx +=1;
3711: sw += weight[i];
3712: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3713: /*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]);*/
3714: } /* end of wave */
3715: } /* end of individual */
3716: } /* End of if */
3717: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3718: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3719: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3720: return -l;
1.126 brouard 3721: }
3722:
3723: /*************** log-likelihood *************/
3724: double funcone( double *x)
3725: {
1.228 brouard 3726: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3727: int i, ii, j, k, mi, d, kk;
1.228 brouard 3728: int ioffset=0;
1.131 brouard 3729: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3730: double **out;
3731: double lli; /* Individual log likelihood */
3732: double llt;
3733: int s1, s2;
1.228 brouard 3734: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3735:
1.126 brouard 3736: double bbh, survp;
1.187 brouard 3737: double agexact;
1.214 brouard 3738: double agebegin, ageend;
1.126 brouard 3739: /*extern weight */
3740: /* We are differentiating ll according to initial status */
3741: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3742: /*for(i=1;i<imx;i++)
3743: printf(" %d\n",s[4][i]);
3744: */
3745: cov[1]=1.;
3746:
3747: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3748: ioffset=0;
3749: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3750: /* ioffset=2+nagesqr+cptcovage; */
3751: ioffset=2+nagesqr;
1.232 brouard 3752: /* Fixed */
1.224 brouard 3753: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3754: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3755: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3756: 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)*/
3757: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3758: /* cov[2+6]=covar[Tvar[6]][i]; */
3759: /* cov[2+6]=covar[2][i]; V2 */
3760: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3761: /* cov[2+7]=covar[Tvar[7]][i]; */
3762: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3763: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3764: /* cov[2+9]=covar[Tvar[9]][i]; */
3765: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3766: }
1.232 brouard 3767: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3768: /* 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?)*\/ */
3769: /* } */
1.231 brouard 3770: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3771: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3772: /* } */
1.225 brouard 3773:
1.233 brouard 3774:
3775: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3776: /* Wave varying (but not age varying) */
3777: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3778: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3779: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3780: }
1.232 brouard 3781: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3782: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3783: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3784: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3785: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3786: /* 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 3787: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3788: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3789: /* /\* 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]); *\/ */
3790: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3791: /* } */
1.126 brouard 3792: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3793: for (j=1;j<=nlstate+ndeath;j++){
3794: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3795: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3796: }
1.214 brouard 3797:
3798: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3799: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3800: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3801: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3802: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3803: and mw[mi+1][i]. dh depends on stepm.*/
3804: newm=savm;
1.247 brouard 3805: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3806: cov[2]=agexact;
3807: if(nagesqr==1)
3808: cov[3]= agexact*agexact;
3809: for (kk=1; kk<=cptcovage;kk++) {
3810: if(!FixedV[Tvar[Tage[kk]]])
3811: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3812: else
3813: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3814: }
3815: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3816: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3817: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3818: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3819: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3820: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3821: savm=oldm;
3822: oldm=newm;
1.126 brouard 3823: } /* end mult */
3824:
3825: s1=s[mw[mi][i]][i];
3826: s2=s[mw[mi+1][i]][i];
1.217 brouard 3827: /* if(s2==-1){ */
1.268 brouard 3828: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3829: /* /\* exit(1); *\/ */
3830: /* } */
1.126 brouard 3831: bbh=(double)bh[mi][i]/(double)stepm;
3832: /* bias is positive if real duration
3833: * is higher than the multiple of stepm and negative otherwise.
3834: */
3835: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3836: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3837: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3838: for (j=1,survp=0. ; j<=nlstate; j++)
3839: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3840: lli= log(survp);
1.126 brouard 3841: }else if (mle==1){
1.242 brouard 3842: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3843: } else if(mle==2){
1.242 brouard 3844: 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 3845: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3846: 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 3847: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3848: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3849: } else{ /* mle=0 back to 1 */
1.242 brouard 3850: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3851: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3852: } /* End of if */
3853: ipmx +=1;
3854: sw += weight[i];
3855: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3856: /*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 3857: if(globpr){
1.246 brouard 3858: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3859: %11.6f %11.6f %11.6f ", \
1.242 brouard 3860: 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 3861: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3862: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3863: llt +=ll[k]*gipmx/gsw;
3864: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3865: }
3866: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3867: }
1.232 brouard 3868: } /* end of wave */
3869: } /* end of individual */
3870: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3871: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3872: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3873: if(globpr==0){ /* First time we count the contributions and weights */
3874: gipmx=ipmx;
3875: gsw=sw;
3876: }
3877: return -l;
1.126 brouard 3878: }
3879:
3880:
3881: /*************** function likelione ***********/
3882: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*funcone)(double []))
3883: {
3884: /* This routine should help understanding what is done with
3885: the selection of individuals/waves and
3886: to check the exact contribution to the likelihood.
3887: Plotting could be done.
3888: */
3889: int k;
3890:
3891: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3892: strcpy(fileresilk,"ILK_");
1.202 brouard 3893: strcat(fileresilk,fileresu);
1.126 brouard 3894: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3895: printf("Problem with resultfile: %s\n", fileresilk);
3896: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3897: }
1.214 brouard 3898: 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");
3899: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3900: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3901: for(k=1; k<=nlstate; k++)
3902: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3903: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3904: }
3905:
3906: *fretone=(*funcone)(p);
3907: if(*globpri !=0){
3908: fclose(ficresilk);
1.205 brouard 3909: if (mle ==0)
3910: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3911: else if(mle >=1)
3912: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3913: 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 3914: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 3915:
3916: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3917: 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 3918: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3919: }
1.207 brouard 3920: 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 3921: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3922: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3923: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3924: fflush(fichtm);
1.205 brouard 3925: }
1.126 brouard 3926: return;
3927: }
3928:
3929:
3930: /*********** Maximum Likelihood Estimation ***************/
3931:
3932: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3933: {
1.165 brouard 3934: int i,j, iter=0;
1.126 brouard 3935: double **xi;
3936: double fret;
3937: double fretone; /* Only one call to likelihood */
3938: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3939:
3940: #ifdef NLOPT
3941: int creturn;
3942: nlopt_opt opt;
3943: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3944: double *lb;
3945: double minf; /* the minimum objective value, upon return */
3946: double * p1; /* Shifted parameters from 0 instead of 1 */
3947: myfunc_data dinst, *d = &dinst;
3948: #endif
3949:
3950:
1.126 brouard 3951: xi=matrix(1,npar,1,npar);
3952: for (i=1;i<=npar;i++)
3953: for (j=1;j<=npar;j++)
3954: xi[i][j]=(i==j ? 1.0 : 0.0);
3955: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3956: strcpy(filerespow,"POW_");
1.126 brouard 3957: strcat(filerespow,fileres);
3958: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3959: printf("Problem with resultfile: %s\n", filerespow);
3960: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3961: }
3962: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3963: for (i=1;i<=nlstate;i++)
3964: for(j=1;j<=nlstate+ndeath;j++)
3965: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3966: fprintf(ficrespow,"\n");
1.162 brouard 3967: #ifdef POWELL
1.126 brouard 3968: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3969: #endif
1.126 brouard 3970:
1.162 brouard 3971: #ifdef NLOPT
3972: #ifdef NEWUOA
3973: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
3974: #else
3975: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
3976: #endif
3977: lb=vector(0,npar-1);
3978: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
3979: nlopt_set_lower_bounds(opt, lb);
3980: nlopt_set_initial_step1(opt, 0.1);
3981:
3982: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
3983: d->function = func;
3984: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
3985: nlopt_set_min_objective(opt, myfunc, d);
3986: nlopt_set_xtol_rel(opt, ftol);
3987: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
3988: printf("nlopt failed! %d\n",creturn);
3989: }
3990: else {
3991: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
3992: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
3993: iter=1; /* not equal */
3994: }
3995: nlopt_destroy(opt);
3996: #endif
1.126 brouard 3997: free_matrix(xi,1,npar,1,npar);
3998: fclose(ficrespow);
1.203 brouard 3999: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
4000: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 4001: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 4002:
4003: }
4004:
4005: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4006: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4007: {
4008: double **a,**y,*x,pd;
1.203 brouard 4009: /* double **hess; */
1.164 brouard 4010: int i, j;
1.126 brouard 4011: int *indx;
4012:
4013: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4014: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4015: void lubksb(double **a, int npar, int *indx, double b[]) ;
4016: void ludcmp(double **a, int npar, int *indx, double *d) ;
4017: double gompertz(double p[]);
1.203 brouard 4018: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4019:
4020: printf("\nCalculation of the hessian matrix. Wait...\n");
4021: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4022: for (i=1;i<=npar;i++){
1.203 brouard 4023: printf("%d-",i);fflush(stdout);
4024: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4025:
4026: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4027:
4028: /* printf(" %f ",p[i]);
4029: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4030: }
4031:
4032: for (i=1;i<=npar;i++) {
4033: for (j=1;j<=npar;j++) {
4034: if (j>i) {
1.203 brouard 4035: printf(".%d-%d",i,j);fflush(stdout);
4036: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4037: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4038:
4039: hess[j][i]=hess[i][j];
4040: /*printf(" %lf ",hess[i][j]);*/
4041: }
4042: }
4043: }
4044: printf("\n");
4045: fprintf(ficlog,"\n");
4046:
4047: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4048: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4049:
4050: a=matrix(1,npar,1,npar);
4051: y=matrix(1,npar,1,npar);
4052: x=vector(1,npar);
4053: indx=ivector(1,npar);
4054: for (i=1;i<=npar;i++)
4055: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4056: ludcmp(a,npar,indx,&pd);
4057:
4058: for (j=1;j<=npar;j++) {
4059: for (i=1;i<=npar;i++) x[i]=0;
4060: x[j]=1;
4061: lubksb(a,npar,indx,x);
4062: for (i=1;i<=npar;i++){
4063: matcov[i][j]=x[i];
4064: }
4065: }
4066:
4067: printf("\n#Hessian matrix#\n");
4068: fprintf(ficlog,"\n#Hessian matrix#\n");
4069: for (i=1;i<=npar;i++) {
4070: for (j=1;j<=npar;j++) {
1.203 brouard 4071: printf("%.6e ",hess[i][j]);
4072: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4073: }
4074: printf("\n");
4075: fprintf(ficlog,"\n");
4076: }
4077:
1.203 brouard 4078: /* printf("\n#Covariance matrix#\n"); */
4079: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4080: /* for (i=1;i<=npar;i++) { */
4081: /* for (j=1;j<=npar;j++) { */
4082: /* printf("%.6e ",matcov[i][j]); */
4083: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4084: /* } */
4085: /* printf("\n"); */
4086: /* fprintf(ficlog,"\n"); */
4087: /* } */
4088:
1.126 brouard 4089: /* Recompute Inverse */
1.203 brouard 4090: /* for (i=1;i<=npar;i++) */
4091: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4092: /* ludcmp(a,npar,indx,&pd); */
4093:
4094: /* printf("\n#Hessian matrix recomputed#\n"); */
4095:
4096: /* for (j=1;j<=npar;j++) { */
4097: /* for (i=1;i<=npar;i++) x[i]=0; */
4098: /* x[j]=1; */
4099: /* lubksb(a,npar,indx,x); */
4100: /* for (i=1;i<=npar;i++){ */
4101: /* y[i][j]=x[i]; */
4102: /* printf("%.3e ",y[i][j]); */
4103: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4104: /* } */
4105: /* printf("\n"); */
4106: /* fprintf(ficlog,"\n"); */
4107: /* } */
4108:
4109: /* Verifying the inverse matrix */
4110: #ifdef DEBUGHESS
4111: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4112:
1.203 brouard 4113: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4114: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4115:
4116: for (j=1;j<=npar;j++) {
4117: for (i=1;i<=npar;i++){
1.203 brouard 4118: printf("%.2f ",y[i][j]);
4119: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4120: }
4121: printf("\n");
4122: fprintf(ficlog,"\n");
4123: }
1.203 brouard 4124: #endif
1.126 brouard 4125:
4126: free_matrix(a,1,npar,1,npar);
4127: free_matrix(y,1,npar,1,npar);
4128: free_vector(x,1,npar);
4129: free_ivector(indx,1,npar);
1.203 brouard 4130: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4131:
4132:
4133: }
4134:
4135: /*************** hessian matrix ****************/
4136: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4137: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4138: int i;
4139: int l=1, lmax=20;
1.203 brouard 4140: double k1,k2, res, fx;
1.132 brouard 4141: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4142: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4143: int k=0,kmax=10;
4144: double l1;
4145:
4146: fx=func(x);
4147: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4148: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4149: l1=pow(10,l);
4150: delts=delt;
4151: for(k=1 ; k <kmax; k=k+1){
4152: delt = delta*(l1*k);
4153: p2[theta]=x[theta] +delt;
1.145 brouard 4154: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4155: p2[theta]=x[theta]-delt;
4156: k2=func(p2)-fx;
4157: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4158: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4159:
1.203 brouard 4160: #ifdef DEBUGHESSII
1.126 brouard 4161: 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);
4162: 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);
4163: #endif
4164: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4165: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4166: k=kmax;
4167: }
4168: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4169: k=kmax; l=lmax*10;
1.126 brouard 4170: }
4171: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4172: delts=delt;
4173: }
1.203 brouard 4174: } /* End loop k */
1.126 brouard 4175: }
4176: delti[theta]=delts;
4177: return res;
4178:
4179: }
4180:
1.203 brouard 4181: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4182: {
4183: int i;
1.164 brouard 4184: int l=1, lmax=20;
1.126 brouard 4185: double k1,k2,k3,k4,res,fx;
1.132 brouard 4186: double p2[MAXPARM+1];
1.203 brouard 4187: int k, kmax=1;
4188: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4189:
4190: int firstime=0;
1.203 brouard 4191:
1.126 brouard 4192: fx=func(x);
1.203 brouard 4193: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4194: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4195: p2[thetai]=x[thetai]+delti[thetai]*k;
4196: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4197: k1=func(p2)-fx;
4198:
1.203 brouard 4199: p2[thetai]=x[thetai]+delti[thetai]*k;
4200: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4201: k2=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: k3=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: k4=func(p2)-fx;
1.203 brouard 4210: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4211: if(k1*k2*k3*k4 <0.){
1.208 brouard 4212: firstime=1;
1.203 brouard 4213: kmax=kmax+10;
1.208 brouard 4214: }
4215: if(kmax >=10 || firstime ==1){
1.246 brouard 4216: 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);
4217: 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 4218: 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);
4219: 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);
4220: }
4221: #ifdef DEBUGHESSIJ
4222: v1=hess[thetai][thetai];
4223: v2=hess[thetaj][thetaj];
4224: cv12=res;
4225: /* Computing eigen value of Hessian matrix */
4226: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4227: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4228: if ((lc2 <0) || (lc1 <0) ){
4229: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4230: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4231: 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);
4232: 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);
4233: }
1.126 brouard 4234: #endif
4235: }
4236: return res;
4237: }
4238:
1.203 brouard 4239: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4240: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4241: /* { */
4242: /* int i; */
4243: /* int l=1, lmax=20; */
4244: /* double k1,k2,k3,k4,res,fx; */
4245: /* double p2[MAXPARM+1]; */
4246: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4247: /* int k=0,kmax=10; */
4248: /* double l1; */
4249:
4250: /* fx=func(x); */
4251: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4252: /* l1=pow(10,l); */
4253: /* delts=delt; */
4254: /* for(k=1 ; k <kmax; k=k+1){ */
4255: /* delt = delti*(l1*k); */
4256: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4257: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4258: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4259: /* k1=func(p2)-fx; */
4260:
4261: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4262: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4263: /* k2=func(p2)-fx; */
4264:
4265: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4266: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4267: /* k3=func(p2)-fx; */
4268:
4269: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4270: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4271: /* k4=func(p2)-fx; */
4272: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4273: /* #ifdef DEBUGHESSIJ */
4274: /* 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); */
4275: /* 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); */
4276: /* #endif */
4277: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4278: /* k=kmax; */
4279: /* } */
4280: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4281: /* k=kmax; l=lmax*10; */
4282: /* } */
4283: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4284: /* delts=delt; */
4285: /* } */
4286: /* } /\* End loop k *\/ */
4287: /* } */
4288: /* delti[theta]=delts; */
4289: /* return res; */
4290: /* } */
4291:
4292:
1.126 brouard 4293: /************** Inverse of matrix **************/
4294: void ludcmp(double **a, int n, int *indx, double *d)
4295: {
4296: int i,imax,j,k;
4297: double big,dum,sum,temp;
4298: double *vv;
4299:
4300: vv=vector(1,n);
4301: *d=1.0;
4302: for (i=1;i<=n;i++) {
4303: big=0.0;
4304: for (j=1;j<=n;j++)
4305: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4306: if (big == 0.0){
4307: printf(" Singular Hessian matrix at row %d:\n",i);
4308: for (j=1;j<=n;j++) {
4309: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4310: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4311: }
4312: fflush(ficlog);
4313: fclose(ficlog);
4314: nrerror("Singular matrix in routine ludcmp");
4315: }
1.126 brouard 4316: vv[i]=1.0/big;
4317: }
4318: for (j=1;j<=n;j++) {
4319: for (i=1;i<j;i++) {
4320: sum=a[i][j];
4321: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4322: a[i][j]=sum;
4323: }
4324: big=0.0;
4325: for (i=j;i<=n;i++) {
4326: sum=a[i][j];
4327: for (k=1;k<j;k++)
4328: sum -= a[i][k]*a[k][j];
4329: a[i][j]=sum;
4330: if ( (dum=vv[i]*fabs(sum)) >= big) {
4331: big=dum;
4332: imax=i;
4333: }
4334: }
4335: if (j != imax) {
4336: for (k=1;k<=n;k++) {
4337: dum=a[imax][k];
4338: a[imax][k]=a[j][k];
4339: a[j][k]=dum;
4340: }
4341: *d = -(*d);
4342: vv[imax]=vv[j];
4343: }
4344: indx[j]=imax;
4345: if (a[j][j] == 0.0) a[j][j]=TINY;
4346: if (j != n) {
4347: dum=1.0/(a[j][j]);
4348: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4349: }
4350: }
4351: free_vector(vv,1,n); /* Doesn't work */
4352: ;
4353: }
4354:
4355: void lubksb(double **a, int n, int *indx, double b[])
4356: {
4357: int i,ii=0,ip,j;
4358: double sum;
4359:
4360: for (i=1;i<=n;i++) {
4361: ip=indx[i];
4362: sum=b[ip];
4363: b[ip]=b[i];
4364: if (ii)
4365: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4366: else if (sum) ii=i;
4367: b[i]=sum;
4368: }
4369: for (i=n;i>=1;i--) {
4370: sum=b[i];
4371: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4372: b[i]=sum/a[i][i];
4373: }
4374: }
4375:
4376: void pstamp(FILE *fichier)
4377: {
1.196 brouard 4378: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4379: }
4380:
1.253 brouard 4381:
4382:
1.126 brouard 4383: /************ Frequencies ********************/
1.251 brouard 4384: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4385: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4386: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4387: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4388:
1.265 brouard 4389: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4390: int iind=0, iage=0;
4391: int mi; /* Effective wave */
4392: int first;
4393: double ***freq; /* Frequencies */
1.268 brouard 4394: 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 */
4395: 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 4396: double *meanq, *stdq, *idq;
1.226 brouard 4397: double **meanqt;
4398: double *pp, **prop, *posprop, *pospropt;
4399: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4400: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4401: double agebegin, ageend;
4402:
4403: pp=vector(1,nlstate);
1.251 brouard 4404: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4405: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4406: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4407: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4408: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4409: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4410: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4411: meanqt=matrix(1,lastpass,1,nqtveff);
4412: strcpy(fileresp,"P_");
4413: strcat(fileresp,fileresu);
4414: /*strcat(fileresphtm,fileresu);*/
4415: if((ficresp=fopen(fileresp,"w"))==NULL) {
4416: printf("Problem with prevalence resultfile: %s\n", fileresp);
4417: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4418: exit(0);
4419: }
1.240 brouard 4420:
1.226 brouard 4421: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4422: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4423: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4424: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4425: fflush(ficlog);
4426: exit(70);
4427: }
4428: else{
4429: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4430: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4431: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4432: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4433: }
1.237 brouard 4434: 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 4435:
1.226 brouard 4436: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4437: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4438: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4439: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4440: fflush(ficlog);
4441: exit(70);
1.240 brouard 4442: } else{
1.226 brouard 4443: 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 4444: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4445: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4446: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4447: }
1.240 brouard 4448: 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);
4449:
1.253 brouard 4450: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4451: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4452: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4453: j1=0;
1.126 brouard 4454:
1.227 brouard 4455: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4456: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4457: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4458:
4459:
1.226 brouard 4460: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4461: reference=low_education V1=0,V2=0
4462: med_educ V1=1 V2=0,
4463: high_educ V1=0 V2=1
4464: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4465: */
1.249 brouard 4466: dateintsum=0;
4467: k2cpt=0;
4468:
1.253 brouard 4469: if(cptcoveff == 0 )
1.265 brouard 4470: nl=1; /* Constant and age model only */
1.253 brouard 4471: else
4472: nl=2;
1.265 brouard 4473:
4474: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4475: /* Loop on nj=1 or 2 if dummy covariates j!=0
4476: * Loop on j1(1 to 2**cptcoveff) covariate combination
4477: * freq[s1][s2][iage] =0.
4478: * Loop on iind
4479: * ++freq[s1][s2][iage] weighted
4480: * end iind
4481: * if covariate and j!0
4482: * headers Variable on one line
4483: * endif cov j!=0
4484: * header of frequency table by age
4485: * Loop on age
4486: * pp[s1]+=freq[s1][s2][iage] weighted
4487: * pos+=freq[s1][s2][iage] weighted
4488: * Loop on s1 initial state
4489: * fprintf(ficresp
4490: * end s1
4491: * end age
4492: * if j!=0 computes starting values
4493: * end compute starting values
4494: * end j1
4495: * end nl
4496: */
1.253 brouard 4497: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4498: if(nj==1)
4499: j=0; /* First pass for the constant */
1.265 brouard 4500: else{
1.253 brouard 4501: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4502: }
1.251 brouard 4503: first=1;
1.265 brouard 4504: 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 4505: posproptt=0.;
4506: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4507: scanf("%d", i);*/
4508: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4509: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4510: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4511: freq[i][s2][m]=0;
1.251 brouard 4512:
4513: for (i=1; i<=nlstate; i++) {
1.240 brouard 4514: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4515: prop[i][m]=0;
4516: posprop[i]=0;
4517: pospropt[i]=0;
4518: }
1.283 brouard 4519: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4520: idq[z1]=0.;
4521: meanq[z1]=0.;
4522: stdq[z1]=0.;
1.283 brouard 4523: }
4524: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4525: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4526: /* meanqt[m][z1]=0.; */
4527: /* } */
4528: /* } */
1.251 brouard 4529: /* dateintsum=0; */
4530: /* k2cpt=0; */
4531:
1.265 brouard 4532: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4533: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4534: bool=1;
4535: if(j !=0){
4536: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4537: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4538: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4539: /* if(Tvaraff[z1] ==-20){ */
4540: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4541: /* }else if(Tvaraff[z1] ==-10){ */
4542: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4543: /* }else */
4544: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4545: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4546: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4547: /* 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",
4548: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4549: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4550: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4551: } /* Onlyf fixed */
4552: } /* end z1 */
4553: } /* cptcovn > 0 */
4554: } /* end any */
4555: }/* end j==0 */
1.265 brouard 4556: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4557: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4558: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4559: m=mw[mi][iind];
4560: if(j!=0){
4561: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4562: for (z1=1; z1<=cptcoveff; z1++) {
4563: if( Fixed[Tmodelind[z1]]==1){
4564: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4565: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4566: value is -1, we don't select. It differs from the
4567: constant and age model which counts them. */
4568: bool=0; /* not selected */
4569: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4570: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4571: bool=0;
4572: }
4573: }
4574: }
4575: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4576: } /* end j==0 */
4577: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4578: if(bool==1){ /*Selected */
1.251 brouard 4579: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4580: and mw[mi+1][iind]. dh depends on stepm. */
4581: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4582: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4583: if(m >=firstpass && m <=lastpass){
4584: k2=anint[m][iind]+(mint[m][iind]/12.);
4585: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4586: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4587: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4588: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4589: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4590: if (m<lastpass) {
4591: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4592: /* 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]); */
4593: if(s[m][iind]==-1)
4594: 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.));
4595: 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 4596: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean */
4597: idq[z1]=idq[z1]+weight[iind];
4598: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
4599: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
4600: }
1.251 brouard 4601: /* if((int)agev[m][iind] == 55) */
4602: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4603: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4604: 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 4605: }
1.251 brouard 4606: } /* end if between passes */
4607: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4608: dateintsum=dateintsum+k2; /* on all covariates ?*/
4609: k2cpt++;
4610: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4611: }
1.251 brouard 4612: }else{
4613: bool=1;
4614: }/* end bool 2 */
4615: } /* end m */
1.284 brouard 4616: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
4617: /* idq[z1]=idq[z1]+weight[iind]; */
4618: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
4619: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
4620: /* } */
1.251 brouard 4621: } /* end bool */
4622: } /* end iind = 1 to imx */
4623: /* prop[s][age] is feeded for any initial and valid live state as well as
4624: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4625:
4626:
4627: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4628: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4629: pstamp(ficresp);
1.251 brouard 4630: if (cptcoveff>0 && j!=0){
1.265 brouard 4631: pstamp(ficresp);
1.251 brouard 4632: printf( "\n#********** Variable ");
4633: fprintf(ficresp, "\n#********** Variable ");
4634: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4635: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4636: fprintf(ficlog, "\n#********** Variable ");
4637: for (z1=1; z1<=cptcoveff; z1++){
4638: if(!FixedV[Tvaraff[z1]]){
4639: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4640: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4641: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4642: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4643: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4644: }else{
1.251 brouard 4645: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4646: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4647: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4648: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4649: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4650: }
4651: }
4652: printf( "**********\n#");
4653: fprintf(ficresp, "**********\n#");
4654: fprintf(ficresphtm, "**********</h3>\n");
4655: fprintf(ficresphtmfr, "**********</h3>\n");
4656: fprintf(ficlog, "**********\n");
4657: }
1.284 brouard 4658: /*
4659: Printing means of quantitative variables if any
4660: */
4661: for (z1=1; z1<= nqfveff; z1++) {
1.285 brouard 4662: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.0f individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.284 brouard 4663: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
4664: if(weightopt==1){
4665: printf(" Weighted mean and standard deviation of");
4666: fprintf(ficlog," Weighted mean and standard deviation of");
4667: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
4668: }
1.285 brouard 4669: 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]));
4670: 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]));
4671: 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 4672: }
4673: /* for (z1=1; z1<= nqtveff; z1++) { */
4674: /* for(m=1;m<=lastpass;m++){ */
4675: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
4676: /* } */
4677: /* } */
1.283 brouard 4678:
1.251 brouard 4679: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4680: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4681: fprintf(ficresp, " Age");
4682: 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 4683: for(i=1; i<=nlstate;i++) {
1.265 brouard 4684: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4685: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4686: }
1.265 brouard 4687: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4688: fprintf(ficresphtm, "\n");
4689:
4690: /* Header of frequency table by age */
4691: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4692: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4693: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4694: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4695: if(s2!=0 && m!=0)
4696: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4697: }
1.226 brouard 4698: }
1.251 brouard 4699: fprintf(ficresphtmfr, "\n");
4700:
4701: /* For each age */
4702: for(iage=iagemin; iage <= iagemax+3; iage++){
4703: fprintf(ficresphtm,"<tr>");
4704: if(iage==iagemax+1){
4705: fprintf(ficlog,"1");
4706: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4707: }else if(iage==iagemax+2){
4708: fprintf(ficlog,"0");
4709: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4710: }else if(iage==iagemax+3){
4711: fprintf(ficlog,"Total");
4712: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4713: }else{
1.240 brouard 4714: if(first==1){
1.251 brouard 4715: first=0;
4716: printf("See log file for details...\n");
4717: }
4718: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4719: fprintf(ficlog,"Age %d", iage);
4720: }
1.265 brouard 4721: for(s1=1; s1 <=nlstate ; s1++){
4722: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4723: pp[s1] += freq[s1][m][iage];
1.251 brouard 4724: }
1.265 brouard 4725: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4726: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4727: pos += freq[s1][m][iage];
4728: if(pp[s1]>=1.e-10){
1.251 brouard 4729: if(first==1){
1.265 brouard 4730: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4731: }
1.265 brouard 4732: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4733: }else{
4734: if(first==1)
1.265 brouard 4735: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4736: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4737: }
4738: }
4739:
1.265 brouard 4740: for(s1=1; s1 <=nlstate ; s1++){
4741: /* posprop[s1]=0; */
4742: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4743: pp[s1] += freq[s1][m][iage];
4744: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4745:
4746: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4747: pos += pp[s1]; /* pos is the total number of transitions until this age */
4748: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4749: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4750: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4751: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4752: }
4753:
4754: /* Writing ficresp */
4755: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4756: if( iage <= iagemax){
4757: fprintf(ficresp," %d",iage);
4758: }
4759: }else if( nj==2){
4760: if( iage <= iagemax){
4761: fprintf(ficresp," %d",iage);
4762: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4763: }
1.240 brouard 4764: }
1.265 brouard 4765: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4766: if(pos>=1.e-5){
1.251 brouard 4767: if(first==1)
1.265 brouard 4768: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4769: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4770: }else{
4771: if(first==1)
1.265 brouard 4772: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4773: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4774: }
4775: if( iage <= iagemax){
4776: if(pos>=1.e-5){
1.265 brouard 4777: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4778: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4779: }else if( nj==2){
4780: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4781: }
4782: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4783: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4784: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4785: } else{
4786: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4787: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4788: }
1.240 brouard 4789: }
1.265 brouard 4790: pospropt[s1] +=posprop[s1];
4791: } /* end loop s1 */
1.251 brouard 4792: /* pospropt=0.; */
1.265 brouard 4793: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4794: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4795: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4796: if(first==1){
1.265 brouard 4797: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4798: }
1.265 brouard 4799: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4800: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4801: }
1.265 brouard 4802: if(s1!=0 && m!=0)
4803: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4804: }
1.265 brouard 4805: } /* end loop s1 */
1.251 brouard 4806: posproptt=0.;
1.265 brouard 4807: for(s1=1; s1 <=nlstate; s1++){
4808: posproptt += pospropt[s1];
1.251 brouard 4809: }
4810: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4811: fprintf(ficresphtm,"</tr>\n");
4812: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4813: if(iage <= iagemax)
4814: fprintf(ficresp,"\n");
1.240 brouard 4815: }
1.251 brouard 4816: if(first==1)
4817: printf("Others in log...\n");
4818: fprintf(ficlog,"\n");
4819: } /* end loop age iage */
1.265 brouard 4820:
1.251 brouard 4821: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4822: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4823: if(posproptt < 1.e-5){
1.265 brouard 4824: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4825: }else{
1.265 brouard 4826: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4827: }
1.226 brouard 4828: }
1.251 brouard 4829: fprintf(ficresphtm,"</tr>\n");
4830: fprintf(ficresphtm,"</table>\n");
4831: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4832: if(posproptt < 1.e-5){
1.251 brouard 4833: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4834: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4835: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4836: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4837: invalidvarcomb[j1]=1;
1.226 brouard 4838: }else{
1.251 brouard 4839: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4840: invalidvarcomb[j1]=0;
1.226 brouard 4841: }
1.251 brouard 4842: fprintf(ficresphtmfr,"</table>\n");
4843: fprintf(ficlog,"\n");
4844: if(j!=0){
4845: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4846: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4847: for(k=1; k <=(nlstate+ndeath); k++){
4848: if (k != i) {
1.265 brouard 4849: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4850: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4851: if(j1==1){ /* All dummy covariates to zero */
4852: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4853: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4854: printf("%d%d ",i,k);
4855: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4856: 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]));
4857: 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]));
4858: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4859: }
1.253 brouard 4860: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4861: for(iage=iagemin; iage <= iagemax+3; iage++){
4862: x[iage]= (double)iage;
4863: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4864: /* 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 4865: }
1.268 brouard 4866: /* Some are not finite, but linreg will ignore these ages */
4867: no=0;
1.253 brouard 4868: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4869: pstart[s1]=b;
4870: pstart[s1-1]=a;
1.252 brouard 4871: }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 */
4872: 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]);
4873: 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 4874: 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 4875: printf("%d%d ",i,k);
4876: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4877: 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 4878: }else{ /* Other cases, like quantitative fixed or varying covariates */
4879: ;
4880: }
4881: /* printf("%12.7f )", param[i][jj][k]); */
4882: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4883: s1++;
1.251 brouard 4884: } /* end jj */
4885: } /* end k!= i */
4886: } /* end k */
1.265 brouard 4887: } /* end i, s1 */
1.251 brouard 4888: } /* end j !=0 */
4889: } /* end selected combination of covariate j1 */
4890: if(j==0){ /* We can estimate starting values from the occurences in each case */
4891: printf("#Freqsummary: Starting values for the constants:\n");
4892: fprintf(ficlog,"\n");
1.265 brouard 4893: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4894: for(k=1; k <=(nlstate+ndeath); k++){
4895: if (k != i) {
4896: printf("%d%d ",i,k);
4897: fprintf(ficlog,"%d%d ",i,k);
4898: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 4899: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 4900: if(jj==1){ /* Age has to be done */
1.265 brouard 4901: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
4902: 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]));
4903: 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 4904: }
4905: /* printf("%12.7f )", param[i][jj][k]); */
4906: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4907: s1++;
1.250 brouard 4908: }
1.251 brouard 4909: printf("\n");
4910: fprintf(ficlog,"\n");
1.250 brouard 4911: }
4912: }
1.284 brouard 4913: } /* end of state i */
1.251 brouard 4914: printf("#Freqsummary\n");
4915: fprintf(ficlog,"\n");
1.265 brouard 4916: for(s1=-1; s1 <=nlstate+ndeath; s1++){
4917: for(s2=-1; s2 <=nlstate+ndeath; s2++){
4918: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
4919: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4920: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4921: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
4922: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
4923: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 4924: /* } */
4925: }
1.265 brouard 4926: } /* end loop s1 */
1.251 brouard 4927:
4928: printf("\n");
4929: fprintf(ficlog,"\n");
4930: } /* end j=0 */
1.249 brouard 4931: } /* end j */
1.252 brouard 4932:
1.253 brouard 4933: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 4934: for(i=1, jk=1; i <=nlstate; i++){
4935: for(j=1; j <=nlstate+ndeath; j++){
4936: if(j!=i){
4937: /*ca[0]= k+'a'-1;ca[1]='\0';*/
4938: printf("%1d%1d",i,j);
4939: fprintf(ficparo,"%1d%1d",i,j);
4940: for(k=1; k<=ncovmodel;k++){
4941: /* printf(" %lf",param[i][j][k]); */
4942: /* fprintf(ficparo," %lf",param[i][j][k]); */
4943: p[jk]=pstart[jk];
4944: printf(" %f ",pstart[jk]);
4945: fprintf(ficparo," %f ",pstart[jk]);
4946: jk++;
4947: }
4948: printf("\n");
4949: fprintf(ficparo,"\n");
4950: }
4951: }
4952: }
4953: } /* end mle=-2 */
1.226 brouard 4954: dateintmean=dateintsum/k2cpt;
1.240 brouard 4955:
1.226 brouard 4956: fclose(ficresp);
4957: fclose(ficresphtm);
4958: fclose(ficresphtmfr);
1.283 brouard 4959: free_vector(idq,1,nqfveff);
1.226 brouard 4960: free_vector(meanq,1,nqfveff);
1.284 brouard 4961: free_vector(stdq,1,nqfveff);
1.226 brouard 4962: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 4963: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
4964: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 4965: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4966: free_vector(pospropt,1,nlstate);
4967: free_vector(posprop,1,nlstate);
1.251 brouard 4968: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4969: free_vector(pp,1,nlstate);
4970: /* End of freqsummary */
4971: }
1.126 brouard 4972:
1.268 brouard 4973: /* Simple linear regression */
4974: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
4975:
4976: /* y=a+bx regression */
4977: double sumx = 0.0; /* sum of x */
4978: double sumx2 = 0.0; /* sum of x**2 */
4979: double sumxy = 0.0; /* sum of x * y */
4980: double sumy = 0.0; /* sum of y */
4981: double sumy2 = 0.0; /* sum of y**2 */
4982: double sume2 = 0.0; /* sum of square or residuals */
4983: double yhat;
4984:
4985: double denom=0;
4986: int i;
4987: int ne=*no;
4988:
4989: for ( i=ifi, ne=0;i<=ila;i++) {
4990: if(!isfinite(x[i]) || !isfinite(y[i])){
4991: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
4992: continue;
4993: }
4994: ne=ne+1;
4995: sumx += x[i];
4996: sumx2 += x[i]*x[i];
4997: sumxy += x[i] * y[i];
4998: sumy += y[i];
4999: sumy2 += y[i]*y[i];
5000: denom = (ne * sumx2 - sumx*sumx);
5001: /* 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); */
5002: }
5003:
5004: denom = (ne * sumx2 - sumx*sumx);
5005: if (denom == 0) {
5006: // vertical, slope m is infinity
5007: *b = INFINITY;
5008: *a = 0;
5009: if (r) *r = 0;
5010: return 1;
5011: }
5012:
5013: *b = (ne * sumxy - sumx * sumy) / denom;
5014: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5015: if (r!=NULL) {
5016: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5017: sqrt((sumx2 - sumx*sumx/ne) *
5018: (sumy2 - sumy*sumy/ne));
5019: }
5020: *no=ne;
5021: for ( i=ifi, ne=0;i<=ila;i++) {
5022: if(!isfinite(x[i]) || !isfinite(y[i])){
5023: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5024: continue;
5025: }
5026: ne=ne+1;
5027: yhat = y[i] - *a -*b* x[i];
5028: sume2 += yhat * yhat ;
5029:
5030: denom = (ne * sumx2 - sumx*sumx);
5031: /* 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); */
5032: }
5033: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5034: *sa= *sb * sqrt(sumx2/ne);
5035:
5036: return 0;
5037: }
5038:
1.126 brouard 5039: /************ Prevalence ********************/
1.227 brouard 5040: 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)
5041: {
5042: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5043: in each health status at the date of interview (if between dateprev1 and dateprev2).
5044: We still use firstpass and lastpass as another selection.
5045: */
1.126 brouard 5046:
1.227 brouard 5047: int i, m, jk, j1, bool, z1,j, iv;
5048: int mi; /* Effective wave */
5049: int iage;
5050: double agebegin, ageend;
5051:
5052: double **prop;
5053: double posprop;
5054: double y2; /* in fractional years */
5055: int iagemin, iagemax;
5056: int first; /** to stop verbosity which is redirected to log file */
5057:
5058: iagemin= (int) agemin;
5059: iagemax= (int) agemax;
5060: /*pp=vector(1,nlstate);*/
1.251 brouard 5061: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5062: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5063: j1=0;
1.222 brouard 5064:
1.227 brouard 5065: /*j=cptcoveff;*/
5066: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5067:
1.288 brouard 5068: first=0;
1.227 brouard 5069: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5070: for (i=1; i<=nlstate; i++)
1.251 brouard 5071: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5072: prop[i][iage]=0.0;
5073: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5074: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5075: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5076:
5077: for (i=1; i<=imx; i++) { /* Each individual */
5078: bool=1;
5079: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5080: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5081: m=mw[mi][i];
5082: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5083: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5084: for (z1=1; z1<=cptcoveff; z1++){
5085: if( Fixed[Tmodelind[z1]]==1){
5086: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5087: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5088: bool=0;
5089: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5090: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5091: bool=0;
5092: }
5093: }
5094: if(bool==1){ /* Otherwise we skip that wave/person */
5095: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5096: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5097: if(m >=firstpass && m <=lastpass){
5098: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5099: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5100: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5101: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5102: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5103: 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);
5104: exit(1);
5105: }
5106: if (s[m][i]>0 && s[m][i]<=nlstate) {
5107: /*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]]);*/
5108: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5109: prop[s[m][i]][iagemax+3] += weight[i];
5110: } /* end valid statuses */
5111: } /* end selection of dates */
5112: } /* end selection of waves */
5113: } /* end bool */
5114: } /* end wave */
5115: } /* end individual */
5116: for(i=iagemin; i <= iagemax+3; i++){
5117: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5118: posprop += prop[jk][i];
5119: }
5120:
5121: for(jk=1; jk <=nlstate ; jk++){
5122: if( i <= iagemax){
5123: if(posprop>=1.e-5){
5124: probs[i][jk][j1]= prop[jk][i]/posprop;
5125: } else{
1.288 brouard 5126: if(!first){
5127: first=1;
1.266 brouard 5128: 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]);
5129: }else{
1.288 brouard 5130: 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 5131: }
5132: }
5133: }
5134: }/* end jk */
5135: }/* end i */
1.222 brouard 5136: /*} *//* end i1 */
1.227 brouard 5137: } /* end j1 */
1.222 brouard 5138:
1.227 brouard 5139: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5140: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5141: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5142: } /* End of prevalence */
1.126 brouard 5143:
5144: /************* Waves Concatenation ***************/
5145:
5146: 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)
5147: {
5148: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
5149: Death is a valid wave (if date is known).
5150: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5151: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
5152: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 5153: */
1.126 brouard 5154:
1.224 brouard 5155: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5156: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5157: double sum=0., jmean=0.;*/
1.224 brouard 5158: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5159: int j, k=0,jk, ju, jl;
5160: double sum=0.;
5161: first=0;
1.214 brouard 5162: firstwo=0;
1.217 brouard 5163: firsthree=0;
1.218 brouard 5164: firstfour=0;
1.164 brouard 5165: jmin=100000;
1.126 brouard 5166: jmax=-1;
5167: jmean=0.;
1.224 brouard 5168:
5169: /* Treating live states */
1.214 brouard 5170: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5171: mi=0; /* First valid wave */
1.227 brouard 5172: mli=0; /* Last valid wave */
1.126 brouard 5173: m=firstpass;
1.214 brouard 5174: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 5175: 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 */
5176: mli=m-1;/* mw[++mi][i]=m-1; */
5177: }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 */
5178: mw[++mi][i]=m;
5179: mli=m;
1.224 brouard 5180: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5181: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5182: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5183: }
1.227 brouard 5184: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 5185: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5186: break;
1.224 brouard 5187: #else
1.227 brouard 5188: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
5189: if(firsthree == 0){
1.262 brouard 5190: 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 5191: firsthree=1;
5192: }
1.262 brouard 5193: 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 5194: mw[++mi][i]=m;
5195: mli=m;
5196: }
5197: if(s[m][i]==-2){ /* Vital status is really unknown */
5198: nbwarn++;
5199: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
5200: 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);
5201: 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);
5202: }
5203: break;
5204: }
5205: break;
1.224 brouard 5206: #endif
1.227 brouard 5207: }/* End m >= lastpass */
1.126 brouard 5208: }/* end while */
1.224 brouard 5209:
1.227 brouard 5210: /* 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 5211: /* After last pass */
1.224 brouard 5212: /* Treating death states */
1.214 brouard 5213: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5214: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5215: /* } */
1.126 brouard 5216: mi++; /* Death is another wave */
5217: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5218: /* Only death is a correct wave */
1.126 brouard 5219: mw[mi][i]=m;
1.257 brouard 5220: } /* else not in a death state */
1.224 brouard 5221: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5222: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5223: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 5224: 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 */
5225: nbwarn++;
5226: if(firstfiv==0){
5227: 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 );
5228: firstfiv=1;
5229: }else{
5230: 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 );
5231: }
5232: }else{ /* Death occured afer last wave potential bias */
5233: nberr++;
5234: if(firstwo==0){
1.257 brouard 5235: 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 5236: firstwo=1;
5237: }
1.257 brouard 5238: 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 5239: }
1.257 brouard 5240: }else{ /* if date of interview is unknown */
1.227 brouard 5241: /* death is known but not confirmed by death status at any wave */
5242: if(firstfour==0){
5243: 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 );
5244: firstfour=1;
5245: }
5246: 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 5247: }
1.224 brouard 5248: } /* end if date of death is known */
5249: #endif
5250: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5251: /* wav[i]=mw[mi][i]; */
1.126 brouard 5252: if(mi==0){
5253: nbwarn++;
5254: if(first==0){
1.227 brouard 5255: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5256: first=1;
1.126 brouard 5257: }
5258: if(first==1){
1.227 brouard 5259: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5260: }
5261: } /* end mi==0 */
5262: } /* End individuals */
1.214 brouard 5263: /* wav and mw are no more changed */
1.223 brouard 5264:
1.214 brouard 5265:
1.126 brouard 5266: for(i=1; i<=imx; i++){
5267: for(mi=1; mi<wav[i];mi++){
5268: if (stepm <=0)
1.227 brouard 5269: dh[mi][i]=1;
1.126 brouard 5270: else{
1.260 brouard 5271: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5272: if (agedc[i] < 2*AGESUP) {
5273: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5274: if(j==0) j=1; /* Survives at least one month after exam */
5275: else if(j<0){
5276: nberr++;
5277: 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]);
5278: j=1; /* Temporary Dangerous patch */
5279: 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);
5280: 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]);
5281: 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);
5282: }
5283: k=k+1;
5284: if (j >= jmax){
5285: jmax=j;
5286: ijmax=i;
5287: }
5288: if (j <= jmin){
5289: jmin=j;
5290: ijmin=i;
5291: }
5292: sum=sum+j;
5293: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5294: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5295: }
5296: }
5297: else{
5298: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5299: /* 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 5300:
1.227 brouard 5301: k=k+1;
5302: if (j >= jmax) {
5303: jmax=j;
5304: ijmax=i;
5305: }
5306: else if (j <= jmin){
5307: jmin=j;
5308: ijmin=i;
5309: }
5310: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5311: /*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]);*/
5312: if(j<0){
5313: nberr++;
5314: 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]);
5315: 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]);
5316: }
5317: sum=sum+j;
5318: }
5319: jk= j/stepm;
5320: jl= j -jk*stepm;
5321: ju= j -(jk+1)*stepm;
5322: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5323: if(jl==0){
5324: dh[mi][i]=jk;
5325: bh[mi][i]=0;
5326: }else{ /* We want a negative bias in order to only have interpolation ie
5327: * to avoid the price of an extra matrix product in likelihood */
5328: dh[mi][i]=jk+1;
5329: bh[mi][i]=ju;
5330: }
5331: }else{
5332: if(jl <= -ju){
5333: dh[mi][i]=jk;
5334: bh[mi][i]=jl; /* bias is positive if real duration
5335: * is higher than the multiple of stepm and negative otherwise.
5336: */
5337: }
5338: else{
5339: dh[mi][i]=jk+1;
5340: bh[mi][i]=ju;
5341: }
5342: if(dh[mi][i]==0){
5343: dh[mi][i]=1; /* At least one step */
5344: bh[mi][i]=ju; /* At least one step */
5345: /* 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);*/
5346: }
5347: } /* end if mle */
1.126 brouard 5348: }
5349: } /* end wave */
5350: }
5351: jmean=sum/k;
5352: 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 5353: 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 5354: }
1.126 brouard 5355:
5356: /*********** Tricode ****************************/
1.220 brouard 5357: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5358: {
5359: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5360: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5361: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5362: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5363: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5364: */
1.130 brouard 5365:
1.242 brouard 5366: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5367: int modmaxcovj=0; /* Modality max of covariates j */
5368: int cptcode=0; /* Modality max of covariates j */
5369: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5370:
5371:
1.242 brouard 5372: /* cptcoveff=0; */
5373: /* *cptcov=0; */
1.126 brouard 5374:
1.242 brouard 5375: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5376: for (k=1; k <= maxncov; k++)
5377: for(j=1; j<=2; j++)
5378: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5379:
1.242 brouard 5380: /* Loop on covariates without age and products and no quantitative variable */
5381: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5382: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5383: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5384: switch(Fixed[k]) {
5385: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5386: 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*/
5387: ij=(int)(covar[Tvar[k]][i]);
5388: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5389: * If product of Vn*Vm, still boolean *:
5390: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5391: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5392: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5393: modality of the nth covariate of individual i. */
5394: if (ij > modmaxcovj)
5395: modmaxcovj=ij;
5396: else if (ij < modmincovj)
5397: modmincovj=ij;
1.287 brouard 5398: if (ij <0 || ij >1 ){
5399: printf("Information, IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5400: fprintf(ficlog,"Information, currently IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5401: }
5402: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5403: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5404: exit(1);
5405: }else
5406: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5407: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5408: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5409: /* getting the maximum value of the modality of the covariate
5410: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5411: female ies 1, then modmaxcovj=1.
5412: */
5413: } /* end for loop on individuals i */
5414: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5415: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5416: cptcode=modmaxcovj;
5417: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5418: /*for (i=0; i<=cptcode; i++) {*/
5419: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5420: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5421: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5422: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5423: if( j != -1){
5424: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5425: covariate for which somebody answered excluding
5426: undefined. Usually 2: 0 and 1. */
5427: }
5428: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5429: covariate for which somebody answered including
5430: undefined. Usually 3: -1, 0 and 1. */
5431: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5432: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5433: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5434:
1.242 brouard 5435: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5436: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5437: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5438: /* modmincovj=3; modmaxcovj = 7; */
5439: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5440: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5441: /* defining two dummy variables: variables V1_1 and V1_2.*/
5442: /* nbcode[Tvar[j]][ij]=k; */
5443: /* nbcode[Tvar[j]][1]=0; */
5444: /* nbcode[Tvar[j]][2]=1; */
5445: /* nbcode[Tvar[j]][3]=2; */
5446: /* To be continued (not working yet). */
5447: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5448:
5449: /* 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*/
5450: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5451: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5452: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5453: /*, could be restored in the future */
5454: 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 5455: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5456: break;
5457: }
5458: ij++;
1.287 brouard 5459: 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 5460: cptcode = ij; /* New max modality for covar j */
5461: } /* end of loop on modality i=-1 to 1 or more */
5462: break;
5463: case 1: /* Testing on varying covariate, could be simple and
5464: * should look at waves or product of fixed *
5465: * varying. No time to test -1, assuming 0 and 1 only */
5466: ij=0;
5467: for(i=0; i<=1;i++){
5468: nbcode[Tvar[k]][++ij]=i;
5469: }
5470: break;
5471: default:
5472: break;
5473: } /* end switch */
5474: } /* end dummy test */
1.287 brouard 5475: } /* 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 5476:
5477: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5478: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5479: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5480: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5481: 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 */
5482: 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 */
5483: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5484: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5485:
5486: ij=0;
5487: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5488: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5489: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5490: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5491: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5492: /* If product not in single variable we don't print results */
5493: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5494: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5495: 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*/
5496: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5497: 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 */
5498: if(Fixed[k]!=0)
5499: anyvaryingduminmodel=1;
5500: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5501: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5502: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5503: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5504: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5505: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5506: }
5507: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5508: /* ij--; */
5509: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5510: *cptcov=ij; /*Number of total real effective covariates: effective
5511: * because they can be excluded from the model and real
5512: * if in the model but excluded because missing values, but how to get k from ij?*/
5513: for(j=ij+1; j<= cptcovt; j++){
5514: Tvaraff[j]=0;
5515: Tmodelind[j]=0;
5516: }
5517: for(j=ntveff+1; j<= cptcovt; j++){
5518: TmodelInvind[j]=0;
5519: }
5520: /* To be sorted */
5521: ;
5522: }
1.126 brouard 5523:
1.145 brouard 5524:
1.126 brouard 5525: /*********** Health Expectancies ****************/
5526:
1.235 brouard 5527: 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 5528:
5529: {
5530: /* Health expectancies, no variances */
1.164 brouard 5531: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5532: int nhstepma, nstepma; /* Decreasing with age */
5533: double age, agelim, hf;
5534: double ***p3mat;
5535: double eip;
5536:
1.238 brouard 5537: /* pstamp(ficreseij); */
1.126 brouard 5538: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5539: fprintf(ficreseij,"# Age");
5540: for(i=1; i<=nlstate;i++){
5541: for(j=1; j<=nlstate;j++){
5542: fprintf(ficreseij," e%1d%1d ",i,j);
5543: }
5544: fprintf(ficreseij," e%1d. ",i);
5545: }
5546: fprintf(ficreseij,"\n");
5547:
5548:
5549: if(estepm < stepm){
5550: printf ("Problem %d lower than %d\n",estepm, stepm);
5551: }
5552: else hstepm=estepm;
5553: /* We compute the life expectancy from trapezoids spaced every estepm months
5554: * This is mainly to measure the difference between two models: for example
5555: * if stepm=24 months pijx are given only every 2 years and by summing them
5556: * we are calculating an estimate of the Life Expectancy assuming a linear
5557: * progression in between and thus overestimating or underestimating according
5558: * to the curvature of the survival function. If, for the same date, we
5559: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5560: * to compare the new estimate of Life expectancy with the same linear
5561: * hypothesis. A more precise result, taking into account a more precise
5562: * curvature will be obtained if estepm is as small as stepm. */
5563:
5564: /* For example we decided to compute the life expectancy with the smallest unit */
5565: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5566: nhstepm is the number of hstepm from age to agelim
5567: nstepm is the number of stepm from age to agelin.
1.270 brouard 5568: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5569: and note for a fixed period like estepm months */
5570: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5571: survival function given by stepm (the optimization length). Unfortunately it
5572: means that if the survival funtion is printed only each two years of age and if
5573: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5574: results. So we changed our mind and took the option of the best precision.
5575: */
5576: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5577:
5578: agelim=AGESUP;
5579: /* If stepm=6 months */
5580: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5581: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5582:
5583: /* nhstepm age range expressed in number of stepm */
5584: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5585: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5586: /* if (stepm >= YEARM) hstepm=1;*/
5587: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5588: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5589:
5590: for (age=bage; age<=fage; age ++){
5591: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5592: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5593: /* if (stepm >= YEARM) hstepm=1;*/
5594: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5595:
5596: /* If stepm=6 months */
5597: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5598: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5599:
1.235 brouard 5600: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5601:
5602: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5603:
5604: printf("%d|",(int)age);fflush(stdout);
5605: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5606:
5607: /* Computing expectancies */
5608: for(i=1; i<=nlstate;i++)
5609: for(j=1; j<=nlstate;j++)
5610: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5611: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5612:
5613: /* 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]);*/
5614:
5615: }
5616:
5617: fprintf(ficreseij,"%3.0f",age );
5618: for(i=1; i<=nlstate;i++){
5619: eip=0;
5620: for(j=1; j<=nlstate;j++){
5621: eip +=eij[i][j][(int)age];
5622: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5623: }
5624: fprintf(ficreseij,"%9.4f", eip );
5625: }
5626: fprintf(ficreseij,"\n");
5627:
5628: }
5629: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5630: printf("\n");
5631: fprintf(ficlog,"\n");
5632:
5633: }
5634:
1.235 brouard 5635: 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 5636:
5637: {
5638: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5639: to initial status i, ei. .
1.126 brouard 5640: */
5641: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5642: int nhstepma, nstepma; /* Decreasing with age */
5643: double age, agelim, hf;
5644: double ***p3matp, ***p3matm, ***varhe;
5645: double **dnewm,**doldm;
5646: double *xp, *xm;
5647: double **gp, **gm;
5648: double ***gradg, ***trgradg;
5649: int theta;
5650:
5651: double eip, vip;
5652:
5653: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5654: xp=vector(1,npar);
5655: xm=vector(1,npar);
5656: dnewm=matrix(1,nlstate*nlstate,1,npar);
5657: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5658:
5659: pstamp(ficresstdeij);
5660: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5661: fprintf(ficresstdeij,"# Age");
5662: for(i=1; i<=nlstate;i++){
5663: for(j=1; j<=nlstate;j++)
5664: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5665: fprintf(ficresstdeij," e%1d. ",i);
5666: }
5667: fprintf(ficresstdeij,"\n");
5668:
5669: pstamp(ficrescveij);
5670: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5671: fprintf(ficrescveij,"# Age");
5672: for(i=1; i<=nlstate;i++)
5673: for(j=1; j<=nlstate;j++){
5674: cptj= (j-1)*nlstate+i;
5675: for(i2=1; i2<=nlstate;i2++)
5676: for(j2=1; j2<=nlstate;j2++){
5677: cptj2= (j2-1)*nlstate+i2;
5678: if(cptj2 <= cptj)
5679: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5680: }
5681: }
5682: fprintf(ficrescveij,"\n");
5683:
5684: if(estepm < stepm){
5685: printf ("Problem %d lower than %d\n",estepm, stepm);
5686: }
5687: else hstepm=estepm;
5688: /* We compute the life expectancy from trapezoids spaced every estepm months
5689: * This is mainly to measure the difference between two models: for example
5690: * if stepm=24 months pijx are given only every 2 years and by summing them
5691: * we are calculating an estimate of the Life Expectancy assuming a linear
5692: * progression in between and thus overestimating or underestimating according
5693: * to the curvature of the survival function. If, for the same date, we
5694: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5695: * to compare the new estimate of Life expectancy with the same linear
5696: * hypothesis. A more precise result, taking into account a more precise
5697: * curvature will be obtained if estepm is as small as stepm. */
5698:
5699: /* For example we decided to compute the life expectancy with the smallest unit */
5700: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5701: nhstepm is the number of hstepm from age to agelim
5702: nstepm is the number of stepm from age to agelin.
5703: Look at hpijx to understand the reason of that which relies in memory size
5704: and note for a fixed period like estepm months */
5705: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5706: survival function given by stepm (the optimization length). Unfortunately it
5707: means that if the survival funtion is printed only each two years of age and if
5708: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5709: results. So we changed our mind and took the option of the best precision.
5710: */
5711: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5712:
5713: /* If stepm=6 months */
5714: /* nhstepm age range expressed in number of stepm */
5715: agelim=AGESUP;
5716: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5717: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5718: /* if (stepm >= YEARM) hstepm=1;*/
5719: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5720:
5721: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5722: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5723: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5724: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5725: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5726: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5727:
5728: for (age=bage; age<=fage; age ++){
5729: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5730: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5731: /* if (stepm >= YEARM) hstepm=1;*/
5732: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5733:
1.126 brouard 5734: /* If stepm=6 months */
5735: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5736: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5737:
5738: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5739:
1.126 brouard 5740: /* Computing Variances of health expectancies */
5741: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5742: decrease memory allocation */
5743: for(theta=1; theta <=npar; theta++){
5744: for(i=1; i<=npar; i++){
1.222 brouard 5745: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5746: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5747: }
1.235 brouard 5748: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5749: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5750:
1.126 brouard 5751: for(j=1; j<= nlstate; j++){
1.222 brouard 5752: for(i=1; i<=nlstate; i++){
5753: for(h=0; h<=nhstepm-1; h++){
5754: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5755: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5756: }
5757: }
1.126 brouard 5758: }
1.218 brouard 5759:
1.126 brouard 5760: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5761: for(h=0; h<=nhstepm-1; h++){
5762: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5763: }
1.126 brouard 5764: }/* End theta */
5765:
5766:
5767: for(h=0; h<=nhstepm-1; h++)
5768: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5769: for(theta=1; theta <=npar; theta++)
5770: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5771:
1.218 brouard 5772:
1.222 brouard 5773: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5774: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5775: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5776:
1.222 brouard 5777: printf("%d|",(int)age);fflush(stdout);
5778: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5779: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5780: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5781: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5782: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5783: for(ij=1;ij<=nlstate*nlstate;ij++)
5784: for(ji=1;ji<=nlstate*nlstate;ji++)
5785: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5786: }
5787: }
1.218 brouard 5788:
1.126 brouard 5789: /* Computing expectancies */
1.235 brouard 5790: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5791: for(i=1; i<=nlstate;i++)
5792: for(j=1; j<=nlstate;j++)
1.222 brouard 5793: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5794: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5795:
1.222 brouard 5796: /* 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 5797:
1.222 brouard 5798: }
1.269 brouard 5799:
5800: /* Standard deviation of expectancies ij */
1.126 brouard 5801: fprintf(ficresstdeij,"%3.0f",age );
5802: for(i=1; i<=nlstate;i++){
5803: eip=0.;
5804: vip=0.;
5805: for(j=1; j<=nlstate;j++){
1.222 brouard 5806: eip += eij[i][j][(int)age];
5807: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5808: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5809: 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 5810: }
5811: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5812: }
5813: fprintf(ficresstdeij,"\n");
1.218 brouard 5814:
1.269 brouard 5815: /* Variance of expectancies ij */
1.126 brouard 5816: fprintf(ficrescveij,"%3.0f",age );
5817: for(i=1; i<=nlstate;i++)
5818: for(j=1; j<=nlstate;j++){
1.222 brouard 5819: cptj= (j-1)*nlstate+i;
5820: for(i2=1; i2<=nlstate;i2++)
5821: for(j2=1; j2<=nlstate;j2++){
5822: cptj2= (j2-1)*nlstate+i2;
5823: if(cptj2 <= cptj)
5824: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5825: }
1.126 brouard 5826: }
5827: fprintf(ficrescveij,"\n");
1.218 brouard 5828:
1.126 brouard 5829: }
5830: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5831: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5832: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5833: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5834: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5835: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5836: printf("\n");
5837: fprintf(ficlog,"\n");
1.218 brouard 5838:
1.126 brouard 5839: free_vector(xm,1,npar);
5840: free_vector(xp,1,npar);
5841: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5842: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5843: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5844: }
1.218 brouard 5845:
1.126 brouard 5846: /************ Variance ******************/
1.235 brouard 5847: 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 5848: {
1.279 brouard 5849: /** Variance of health expectancies
5850: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
5851: * double **newm;
5852: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
5853: */
1.218 brouard 5854:
5855: /* int movingaverage(); */
5856: double **dnewm,**doldm;
5857: double **dnewmp,**doldmp;
5858: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 5859: int first=0;
1.218 brouard 5860: int k;
5861: double *xp;
1.279 brouard 5862: double **gp, **gm; /**< for var eij */
5863: double ***gradg, ***trgradg; /**< for var eij */
5864: double **gradgp, **trgradgp; /**< for var p point j */
5865: double *gpp, *gmp; /**< for var p point j */
5866: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 5867: double ***p3mat;
5868: double age,agelim, hf;
5869: /* double ***mobaverage; */
5870: int theta;
5871: char digit[4];
5872: char digitp[25];
5873:
5874: char fileresprobmorprev[FILENAMELENGTH];
5875:
5876: if(popbased==1){
5877: if(mobilav!=0)
5878: strcpy(digitp,"-POPULBASED-MOBILAV_");
5879: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5880: }
5881: else
5882: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5883:
1.218 brouard 5884: /* if (mobilav!=0) { */
5885: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5886: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5887: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5888: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5889: /* } */
5890: /* } */
5891:
5892: strcpy(fileresprobmorprev,"PRMORPREV-");
5893: sprintf(digit,"%-d",ij);
5894: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5895: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5896: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5897: strcat(fileresprobmorprev,fileresu);
5898: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5899: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5900: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5901: }
5902: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5903: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5904: pstamp(ficresprobmorprev);
5905: 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 5906: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5907: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5908: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5909: }
5910: for(j=1;j<=cptcoveff;j++)
5911: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5912: fprintf(ficresprobmorprev,"\n");
5913:
1.218 brouard 5914: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5915: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5916: fprintf(ficresprobmorprev," p.%-d SE",j);
5917: for(i=1; i<=nlstate;i++)
5918: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5919: }
5920: fprintf(ficresprobmorprev,"\n");
5921:
5922: fprintf(ficgp,"\n# Routine varevsij");
5923: fprintf(ficgp,"\nunset title \n");
5924: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5925: 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");
5926: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 5927:
1.218 brouard 5928: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5929: pstamp(ficresvij);
5930: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5931: if(popbased==1)
5932: 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);
5933: else
5934: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5935: fprintf(ficresvij,"# Age");
5936: for(i=1; i<=nlstate;i++)
5937: for(j=1; j<=nlstate;j++)
5938: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5939: fprintf(ficresvij,"\n");
5940:
5941: xp=vector(1,npar);
5942: dnewm=matrix(1,nlstate,1,npar);
5943: doldm=matrix(1,nlstate,1,nlstate);
5944: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5945: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5946:
5947: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5948: gpp=vector(nlstate+1,nlstate+ndeath);
5949: gmp=vector(nlstate+1,nlstate+ndeath);
5950: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5951:
1.218 brouard 5952: if(estepm < stepm){
5953: printf ("Problem %d lower than %d\n",estepm, stepm);
5954: }
5955: else hstepm=estepm;
5956: /* For example we decided to compute the life expectancy with the smallest unit */
5957: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5958: nhstepm is the number of hstepm from age to agelim
5959: nstepm is the number of stepm from age to agelim.
5960: Look at function hpijx to understand why because of memory size limitations,
5961: we decided (b) to get a life expectancy respecting the most precise curvature of the
5962: survival function given by stepm (the optimization length). Unfortunately it
5963: means that if the survival funtion is printed every two years of age and if
5964: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5965: results. So we changed our mind and took the option of the best precision.
5966: */
5967: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5968: agelim = AGESUP;
5969: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5970: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5971: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5972: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5973: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
5974: gp=matrix(0,nhstepm,1,nlstate);
5975: gm=matrix(0,nhstepm,1,nlstate);
5976:
5977:
5978: for(theta=1; theta <=npar; theta++){
5979: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
5980: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5981: }
1.279 brouard 5982: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
5983: * returns into prlim .
1.288 brouard 5984: */
1.242 brouard 5985: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 5986:
5987: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 5988: if (popbased==1) {
5989: if(mobilav ==0){
5990: for(i=1; i<=nlstate;i++)
5991: prlim[i][i]=probs[(int)age][i][ij];
5992: }else{ /* mobilav */
5993: for(i=1; i<=nlstate;i++)
5994: prlim[i][i]=mobaverage[(int)age][i][ij];
5995: }
5996: }
1.279 brouard 5997: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}_x\f$ at horizon h.
5998: */
5999: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Returns p3mat[i][j][h] for h=0 to nhstepm */
6000: /**< And for each alive state j, sums over i \f$ w^i_x {}{h}_p^{ij}_x\f$, which are the probability
6001: * at horizon h in state j including mortality.
6002: */
1.218 brouard 6003: for(j=1; j<= nlstate; j++){
6004: for(h=0; h<=nhstepm; h++){
6005: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6006: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6007: }
6008: }
1.279 brouard 6009: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6010: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6011: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6012: */
6013: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6014: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6015: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6016: }
6017:
6018: /* Again with minus shift */
1.218 brouard 6019:
6020: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6021: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6022:
1.242 brouard 6023: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6024:
6025: if (popbased==1) {
6026: if(mobilav ==0){
6027: for(i=1; i<=nlstate;i++)
6028: prlim[i][i]=probs[(int)age][i][ij];
6029: }else{ /* mobilav */
6030: for(i=1; i<=nlstate;i++)
6031: prlim[i][i]=mobaverage[(int)age][i][ij];
6032: }
6033: }
6034:
1.235 brouard 6035: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6036:
6037: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6038: for(h=0; h<=nhstepm; h++){
6039: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6040: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6041: }
6042: }
6043: /* This for computing probability of death (h=1 means
6044: computed over hstepm matrices product = hstepm*stepm months)
6045: as a weighted average of prlim.
6046: */
6047: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6048: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6049: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6050: }
1.279 brouard 6051: /* end shifting computations */
6052:
6053: /**< Computing gradient matrix at horizon h
6054: */
1.218 brouard 6055: for(j=1; j<= nlstate; j++) /* vareij */
6056: for(h=0; h<=nhstepm; h++){
6057: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6058: }
1.279 brouard 6059: /**< Gradient of overall mortality p.3 (or p.j)
6060: */
6061: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6062: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6063: }
6064:
6065: } /* End theta */
1.279 brouard 6066:
6067: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6068: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6069:
6070: for(h=0; h<=nhstepm; h++) /* veij */
6071: for(j=1; j<=nlstate;j++)
6072: for(theta=1; theta <=npar; theta++)
6073: trgradg[h][j][theta]=gradg[h][theta][j];
6074:
6075: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6076: for(theta=1; theta <=npar; theta++)
6077: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6078: /**< as well as its transposed matrix
6079: */
1.218 brouard 6080:
6081: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6082: for(i=1;i<=nlstate;i++)
6083: for(j=1;j<=nlstate;j++)
6084: vareij[i][j][(int)age] =0.;
1.279 brouard 6085:
6086: /* Computing trgradg by matcov by gradg at age and summing over h
6087: * and k (nhstepm) formula 15 of article
6088: * Lievre-Brouard-Heathcote
6089: */
6090:
1.218 brouard 6091: for(h=0;h<=nhstepm;h++){
6092: for(k=0;k<=nhstepm;k++){
6093: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6094: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6095: for(i=1;i<=nlstate;i++)
6096: for(j=1;j<=nlstate;j++)
6097: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6098: }
6099: }
6100:
1.279 brouard 6101: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6102: * p.j overall mortality formula 49 but computed directly because
6103: * we compute the grad (wix pijx) instead of grad (pijx),even if
6104: * wix is independent of theta.
6105: */
1.218 brouard 6106: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6107: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6108: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6109: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6110: varppt[j][i]=doldmp[j][i];
6111: /* end ppptj */
6112: /* x centered again */
6113:
1.242 brouard 6114: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6115:
6116: if (popbased==1) {
6117: if(mobilav ==0){
6118: for(i=1; i<=nlstate;i++)
6119: prlim[i][i]=probs[(int)age][i][ij];
6120: }else{ /* mobilav */
6121: for(i=1; i<=nlstate;i++)
6122: prlim[i][i]=mobaverage[(int)age][i][ij];
6123: }
6124: }
6125:
6126: /* This for computing probability of death (h=1 means
6127: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6128: as a weighted average of prlim.
6129: */
1.235 brouard 6130: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6131: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6132: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6133: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6134: }
6135: /* end probability of death */
6136:
6137: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6138: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6139: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6140: for(i=1; i<=nlstate;i++){
6141: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6142: }
6143: }
6144: fprintf(ficresprobmorprev,"\n");
6145:
6146: fprintf(ficresvij,"%.0f ",age );
6147: for(i=1; i<=nlstate;i++)
6148: for(j=1; j<=nlstate;j++){
6149: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6150: }
6151: fprintf(ficresvij,"\n");
6152: free_matrix(gp,0,nhstepm,1,nlstate);
6153: free_matrix(gm,0,nhstepm,1,nlstate);
6154: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6155: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6156: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6157: } /* End age */
6158: free_vector(gpp,nlstate+1,nlstate+ndeath);
6159: free_vector(gmp,nlstate+1,nlstate+ndeath);
6160: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6161: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6162: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6163: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6164: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6165: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6166: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6167: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6168: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6169: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6170: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6171: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6172: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6173: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6174: 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);
6175: /* 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 6176: */
1.218 brouard 6177: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6178: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6179:
1.218 brouard 6180: free_vector(xp,1,npar);
6181: free_matrix(doldm,1,nlstate,1,nlstate);
6182: free_matrix(dnewm,1,nlstate,1,npar);
6183: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6184: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6185: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6186: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6187: fclose(ficresprobmorprev);
6188: fflush(ficgp);
6189: fflush(fichtm);
6190: } /* end varevsij */
1.126 brouard 6191:
6192: /************ Variance of prevlim ******************/
1.269 brouard 6193: 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 6194: {
1.205 brouard 6195: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6196: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6197:
1.268 brouard 6198: double **dnewmpar,**doldm;
1.126 brouard 6199: int i, j, nhstepm, hstepm;
6200: double *xp;
6201: double *gp, *gm;
6202: double **gradg, **trgradg;
1.208 brouard 6203: double **mgm, **mgp;
1.126 brouard 6204: double age,agelim;
6205: int theta;
6206:
6207: pstamp(ficresvpl);
1.288 brouard 6208: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6209: fprintf(ficresvpl,"# Age ");
6210: if(nresult >=1)
6211: fprintf(ficresvpl," Result# ");
1.126 brouard 6212: for(i=1; i<=nlstate;i++)
6213: fprintf(ficresvpl," %1d-%1d",i,i);
6214: fprintf(ficresvpl,"\n");
6215:
6216: xp=vector(1,npar);
1.268 brouard 6217: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6218: doldm=matrix(1,nlstate,1,nlstate);
6219:
6220: hstepm=1*YEARM; /* Every year of age */
6221: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6222: agelim = AGESUP;
6223: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6224: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6225: if (stepm >= YEARM) hstepm=1;
6226: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6227: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6228: mgp=matrix(1,npar,1,nlstate);
6229: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6230: gp=vector(1,nlstate);
6231: gm=vector(1,nlstate);
6232:
6233: for(theta=1; theta <=npar; theta++){
6234: for(i=1; i<=npar; i++){ /* Computes gradient */
6235: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6236: }
1.288 brouard 6237: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6238: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6239: /* else */
6240: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6241: for(i=1;i<=nlstate;i++){
1.126 brouard 6242: gp[i] = prlim[i][i];
1.208 brouard 6243: mgp[theta][i] = prlim[i][i];
6244: }
1.126 brouard 6245: for(i=1; i<=npar; i++) /* Computes gradient */
6246: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 6247: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
6248: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
6249: /* else */
6250: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6251: for(i=1;i<=nlstate;i++){
1.126 brouard 6252: gm[i] = prlim[i][i];
1.208 brouard 6253: mgm[theta][i] = prlim[i][i];
6254: }
1.126 brouard 6255: for(i=1;i<=nlstate;i++)
6256: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6257: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6258: } /* End theta */
6259:
6260: trgradg =matrix(1,nlstate,1,npar);
6261:
6262: for(j=1; j<=nlstate;j++)
6263: for(theta=1; theta <=npar; theta++)
6264: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6265: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6266: /* printf("\nmgm mgp %d ",(int)age); */
6267: /* for(j=1; j<=nlstate;j++){ */
6268: /* printf(" %d ",j); */
6269: /* for(theta=1; theta <=npar; theta++) */
6270: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6271: /* printf("\n "); */
6272: /* } */
6273: /* } */
6274: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6275: /* printf("\n gradg %d ",(int)age); */
6276: /* for(j=1; j<=nlstate;j++){ */
6277: /* printf("%d ",j); */
6278: /* for(theta=1; theta <=npar; theta++) */
6279: /* printf("%d %lf ",theta,gradg[theta][j]); */
6280: /* printf("\n "); */
6281: /* } */
6282: /* } */
1.126 brouard 6283:
6284: for(i=1;i<=nlstate;i++)
6285: varpl[i][(int)age] =0.;
1.209 brouard 6286: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6287: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6288: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6289: }else{
1.268 brouard 6290: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6291: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6292: }
1.126 brouard 6293: for(i=1;i<=nlstate;i++)
6294: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6295:
6296: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6297: if(nresult >=1)
6298: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 6299: for(i=1; i<=nlstate;i++){
1.126 brouard 6300: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 6301: /* for(j=1;j<=nlstate;j++) */
6302: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
6303: }
1.126 brouard 6304: fprintf(ficresvpl,"\n");
6305: free_vector(gp,1,nlstate);
6306: free_vector(gm,1,nlstate);
1.208 brouard 6307: free_matrix(mgm,1,npar,1,nlstate);
6308: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6309: free_matrix(gradg,1,npar,1,nlstate);
6310: free_matrix(trgradg,1,nlstate,1,npar);
6311: } /* End age */
6312:
6313: free_vector(xp,1,npar);
6314: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6315: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6316:
6317: }
6318:
6319:
6320: /************ Variance of backprevalence limit ******************/
1.269 brouard 6321: 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 6322: {
6323: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6324: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6325:
6326: double **dnewmpar,**doldm;
6327: int i, j, nhstepm, hstepm;
6328: double *xp;
6329: double *gp, *gm;
6330: double **gradg, **trgradg;
6331: double **mgm, **mgp;
6332: double age,agelim;
6333: int theta;
6334:
6335: pstamp(ficresvbl);
6336: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6337: fprintf(ficresvbl,"# Age ");
6338: if(nresult >=1)
6339: fprintf(ficresvbl," Result# ");
6340: for(i=1; i<=nlstate;i++)
6341: fprintf(ficresvbl," %1d-%1d",i,i);
6342: fprintf(ficresvbl,"\n");
6343:
6344: xp=vector(1,npar);
6345: dnewmpar=matrix(1,nlstate,1,npar);
6346: doldm=matrix(1,nlstate,1,nlstate);
6347:
6348: hstepm=1*YEARM; /* Every year of age */
6349: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6350: agelim = AGEINF;
6351: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6352: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6353: if (stepm >= YEARM) hstepm=1;
6354: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6355: gradg=matrix(1,npar,1,nlstate);
6356: mgp=matrix(1,npar,1,nlstate);
6357: mgm=matrix(1,npar,1,nlstate);
6358: gp=vector(1,nlstate);
6359: gm=vector(1,nlstate);
6360:
6361: for(theta=1; theta <=npar; theta++){
6362: for(i=1; i<=npar; i++){ /* Computes gradient */
6363: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6364: }
6365: if(mobilavproj > 0 )
6366: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6367: else
6368: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6369: for(i=1;i<=nlstate;i++){
6370: gp[i] = bprlim[i][i];
6371: mgp[theta][i] = bprlim[i][i];
6372: }
6373: for(i=1; i<=npar; i++) /* Computes gradient */
6374: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6375: if(mobilavproj > 0 )
6376: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6377: else
6378: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6379: for(i=1;i<=nlstate;i++){
6380: gm[i] = bprlim[i][i];
6381: mgm[theta][i] = bprlim[i][i];
6382: }
6383: for(i=1;i<=nlstate;i++)
6384: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6385: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6386: } /* End theta */
6387:
6388: trgradg =matrix(1,nlstate,1,npar);
6389:
6390: for(j=1; j<=nlstate;j++)
6391: for(theta=1; theta <=npar; theta++)
6392: trgradg[j][theta]=gradg[theta][j];
6393: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6394: /* printf("\nmgm mgp %d ",(int)age); */
6395: /* for(j=1; j<=nlstate;j++){ */
6396: /* printf(" %d ",j); */
6397: /* for(theta=1; theta <=npar; theta++) */
6398: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6399: /* printf("\n "); */
6400: /* } */
6401: /* } */
6402: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6403: /* printf("\n gradg %d ",(int)age); */
6404: /* for(j=1; j<=nlstate;j++){ */
6405: /* printf("%d ",j); */
6406: /* for(theta=1; theta <=npar; theta++) */
6407: /* printf("%d %lf ",theta,gradg[theta][j]); */
6408: /* printf("\n "); */
6409: /* } */
6410: /* } */
6411:
6412: for(i=1;i<=nlstate;i++)
6413: varbpl[i][(int)age] =0.;
6414: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6415: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6416: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6417: }else{
6418: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6419: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6420: }
6421: for(i=1;i<=nlstate;i++)
6422: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6423:
6424: fprintf(ficresvbl,"%.0f ",age );
6425: if(nresult >=1)
6426: fprintf(ficresvbl,"%d ",nres );
6427: for(i=1; i<=nlstate;i++)
6428: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6429: fprintf(ficresvbl,"\n");
6430: free_vector(gp,1,nlstate);
6431: free_vector(gm,1,nlstate);
6432: free_matrix(mgm,1,npar,1,nlstate);
6433: free_matrix(mgp,1,npar,1,nlstate);
6434: free_matrix(gradg,1,npar,1,nlstate);
6435: free_matrix(trgradg,1,nlstate,1,npar);
6436: } /* End age */
6437:
6438: free_vector(xp,1,npar);
6439: free_matrix(doldm,1,nlstate,1,npar);
6440: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6441:
6442: }
6443:
6444: /************ Variance of one-step probabilities ******************/
6445: 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 6446: {
6447: int i, j=0, k1, l1, tj;
6448: int k2, l2, j1, z1;
6449: int k=0, l;
6450: int first=1, first1, first2;
6451: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6452: double **dnewm,**doldm;
6453: double *xp;
6454: double *gp, *gm;
6455: double **gradg, **trgradg;
6456: double **mu;
6457: double age, cov[NCOVMAX+1];
6458: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6459: int theta;
6460: char fileresprob[FILENAMELENGTH];
6461: char fileresprobcov[FILENAMELENGTH];
6462: char fileresprobcor[FILENAMELENGTH];
6463: double ***varpij;
6464:
6465: strcpy(fileresprob,"PROB_");
6466: strcat(fileresprob,fileres);
6467: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6468: printf("Problem with resultfile: %s\n", fileresprob);
6469: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6470: }
6471: strcpy(fileresprobcov,"PROBCOV_");
6472: strcat(fileresprobcov,fileresu);
6473: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6474: printf("Problem with resultfile: %s\n", fileresprobcov);
6475: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6476: }
6477: strcpy(fileresprobcor,"PROBCOR_");
6478: strcat(fileresprobcor,fileresu);
6479: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6480: printf("Problem with resultfile: %s\n", fileresprobcor);
6481: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6482: }
6483: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6484: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6485: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6486: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6487: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6488: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6489: pstamp(ficresprob);
6490: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6491: fprintf(ficresprob,"# Age");
6492: pstamp(ficresprobcov);
6493: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6494: fprintf(ficresprobcov,"# Age");
6495: pstamp(ficresprobcor);
6496: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6497: fprintf(ficresprobcor,"# Age");
1.126 brouard 6498:
6499:
1.222 brouard 6500: for(i=1; i<=nlstate;i++)
6501: for(j=1; j<=(nlstate+ndeath);j++){
6502: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6503: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6504: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6505: }
6506: /* fprintf(ficresprob,"\n");
6507: fprintf(ficresprobcov,"\n");
6508: fprintf(ficresprobcor,"\n");
6509: */
6510: xp=vector(1,npar);
6511: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6512: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6513: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6514: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6515: first=1;
6516: fprintf(ficgp,"\n# Routine varprob");
6517: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6518: fprintf(fichtm,"\n");
6519:
1.288 brouard 6520: 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 6521: 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);
6522: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6523: and drawn. It helps understanding how is the covariance between two incidences.\
6524: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6525: 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 6526: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6527: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6528: standard deviations wide on each axis. <br>\
6529: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6530: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6531: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6532:
1.222 brouard 6533: cov[1]=1;
6534: /* tj=cptcoveff; */
1.225 brouard 6535: tj = (int) pow(2,cptcoveff);
1.222 brouard 6536: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6537: j1=0;
1.224 brouard 6538: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6539: if (cptcovn>0) {
6540: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6541: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6542: fprintf(ficresprob, "**********\n#\n");
6543: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6544: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6545: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6546:
1.222 brouard 6547: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6548: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6549: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6550:
6551:
1.222 brouard 6552: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6553: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6554: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6555:
1.222 brouard 6556: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6557: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6558: fprintf(ficresprobcor, "**********\n#");
6559: if(invalidvarcomb[j1]){
6560: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6561: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6562: continue;
6563: }
6564: }
6565: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6566: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6567: gp=vector(1,(nlstate)*(nlstate+ndeath));
6568: gm=vector(1,(nlstate)*(nlstate+ndeath));
6569: for (age=bage; age<=fage; age ++){
6570: cov[2]=age;
6571: if(nagesqr==1)
6572: cov[3]= age*age;
6573: for (k=1; k<=cptcovn;k++) {
6574: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6575: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6576: * 1 1 1 1 1
6577: * 2 2 1 1 1
6578: * 3 1 2 1 1
6579: */
6580: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6581: }
6582: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6583: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6584: for (k=1; k<=cptcovprod;k++)
6585: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6586:
6587:
1.222 brouard 6588: for(theta=1; theta <=npar; theta++){
6589: for(i=1; i<=npar; i++)
6590: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6591:
1.222 brouard 6592: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6593:
1.222 brouard 6594: k=0;
6595: for(i=1; i<= (nlstate); i++){
6596: for(j=1; j<=(nlstate+ndeath);j++){
6597: k=k+1;
6598: gp[k]=pmmij[i][j];
6599: }
6600: }
1.220 brouard 6601:
1.222 brouard 6602: for(i=1; i<=npar; i++)
6603: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6604:
1.222 brouard 6605: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6606: k=0;
6607: for(i=1; i<=(nlstate); i++){
6608: for(j=1; j<=(nlstate+ndeath);j++){
6609: k=k+1;
6610: gm[k]=pmmij[i][j];
6611: }
6612: }
1.220 brouard 6613:
1.222 brouard 6614: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6615: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6616: }
1.126 brouard 6617:
1.222 brouard 6618: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6619: for(theta=1; theta <=npar; theta++)
6620: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6621:
1.222 brouard 6622: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6623: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6624:
1.222 brouard 6625: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6626:
1.222 brouard 6627: k=0;
6628: for(i=1; i<=(nlstate); i++){
6629: for(j=1; j<=(nlstate+ndeath);j++){
6630: k=k+1;
6631: mu[k][(int) age]=pmmij[i][j];
6632: }
6633: }
6634: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6635: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6636: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6637:
1.222 brouard 6638: /*printf("\n%d ",(int)age);
6639: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6640: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6641: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6642: }*/
1.220 brouard 6643:
1.222 brouard 6644: fprintf(ficresprob,"\n%d ",(int)age);
6645: fprintf(ficresprobcov,"\n%d ",(int)age);
6646: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6647:
1.222 brouard 6648: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6649: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6650: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6651: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6652: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6653: }
6654: i=0;
6655: for (k=1; k<=(nlstate);k++){
6656: for (l=1; l<=(nlstate+ndeath);l++){
6657: i++;
6658: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6659: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6660: for (j=1; j<=i;j++){
6661: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6662: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6663: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6664: }
6665: }
6666: }/* end of loop for state */
6667: } /* end of loop for age */
6668: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6669: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6670: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6671: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6672:
6673: /* Confidence intervalle of pij */
6674: /*
6675: fprintf(ficgp,"\nunset parametric;unset label");
6676: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6677: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6678: 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);
6679: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6680: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6681: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6682: */
6683:
6684: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6685: first1=1;first2=2;
6686: for (k2=1; k2<=(nlstate);k2++){
6687: for (l2=1; l2<=(nlstate+ndeath);l2++){
6688: if(l2==k2) continue;
6689: j=(k2-1)*(nlstate+ndeath)+l2;
6690: for (k1=1; k1<=(nlstate);k1++){
6691: for (l1=1; l1<=(nlstate+ndeath);l1++){
6692: if(l1==k1) continue;
6693: i=(k1-1)*(nlstate+ndeath)+l1;
6694: if(i<=j) continue;
6695: for (age=bage; age<=fage; age ++){
6696: if ((int)age %5==0){
6697: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6698: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6699: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6700: mu1=mu[i][(int) age]/stepm*YEARM ;
6701: mu2=mu[j][(int) age]/stepm*YEARM;
6702: c12=cv12/sqrt(v1*v2);
6703: /* Computing eigen value of matrix of covariance */
6704: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6705: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6706: if ((lc2 <0) || (lc1 <0) ){
6707: if(first2==1){
6708: first1=0;
6709: 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);
6710: }
6711: 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);
6712: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6713: /* lc2=fabs(lc2); */
6714: }
1.220 brouard 6715:
1.222 brouard 6716: /* Eigen vectors */
1.280 brouard 6717: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
6718: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6719: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6720: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
6721: }else
6722: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 6723: /*v21=sqrt(1.-v11*v11); *//* error */
6724: v21=(lc1-v1)/cv12*v11;
6725: v12=-v21;
6726: v22=v11;
6727: tnalp=v21/v11;
6728: if(first1==1){
6729: first1=0;
6730: 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);
6731: }
6732: 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);
6733: /*printf(fignu*/
6734: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6735: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6736: if(first==1){
6737: first=0;
6738: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6739: fprintf(ficgp,"\nset parametric;unset label");
6740: 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);
6741: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6742: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6743: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6744: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6745: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6746: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6747: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6748: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6749: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6750: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6751: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6752: 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 6753: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
6754: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6755: }else{
6756: first=0;
6757: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6758: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6759: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6760: 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 6761: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6762: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6763: }/* if first */
6764: } /* age mod 5 */
6765: } /* end loop age */
6766: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6767: first=1;
6768: } /*l12 */
6769: } /* k12 */
6770: } /*l1 */
6771: }/* k1 */
6772: } /* loop on combination of covariates j1 */
6773: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6774: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6775: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6776: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6777: free_vector(xp,1,npar);
6778: fclose(ficresprob);
6779: fclose(ficresprobcov);
6780: fclose(ficresprobcor);
6781: fflush(ficgp);
6782: fflush(fichtmcov);
6783: }
1.126 brouard 6784:
6785:
6786: /******************* Printing html file ***********/
1.201 brouard 6787: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6788: int lastpass, int stepm, int weightopt, char model[],\
6789: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.258 brouard 6790: int popforecast, int mobilav, int prevfcast, int mobilavproj, int backcast, int estepm , \
1.273 brouard 6791: double jprev1, double mprev1,double anprev1, double dateprev1, double dateproj1, double dateback1, \
6792: double jprev2, double mprev2,double anprev2, double dateprev2, double dateproj2, double dateback2){
1.237 brouard 6793: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6794:
6795: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6796: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6797: </ul>");
1.237 brouard 6798: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6799: </ul>", model);
1.214 brouard 6800: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6801: 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",
6802: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6803: 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 6804: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6805: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6806: fprintf(fichtm,"\
6807: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6808: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6809: fprintf(fichtm,"\
1.217 brouard 6810: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6811: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6812: fprintf(fichtm,"\
1.288 brouard 6813: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6814: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6815: fprintf(fichtm,"\
1.288 brouard 6816: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 6817: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6818: fprintf(fichtm,"\
1.211 brouard 6819: - (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 6820: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6821: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6822: if(prevfcast==1){
6823: fprintf(fichtm,"\
6824: - Prevalence projections by age and states: \
1.201 brouard 6825: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6826: }
1.126 brouard 6827:
6828:
1.225 brouard 6829: m=pow(2,cptcoveff);
1.222 brouard 6830: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6831:
1.264 brouard 6832: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6833:
6834: jj1=0;
6835:
6836: fprintf(fichtm," \n<ul>");
6837: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6838: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6839: if(m != 1 && TKresult[nres]!= k1)
6840: continue;
6841: jj1++;
6842: if (cptcovn > 0) {
6843: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6844: for (cpt=1; cpt<=cptcoveff;cpt++){
6845: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6846: }
6847: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6848: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6849: }
6850: fprintf(fichtm,"\">");
6851:
6852: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6853: fprintf(fichtm,"************ Results for covariates");
6854: for (cpt=1; cpt<=cptcoveff;cpt++){
6855: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6856: }
6857: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6858: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6859: }
6860: if(invalidvarcomb[k1]){
6861: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
6862: continue;
6863: }
6864: fprintf(fichtm,"</a></li>");
6865: } /* cptcovn >0 */
6866: }
6867: fprintf(fichtm," \n</ul>");
6868:
1.222 brouard 6869: jj1=0;
1.237 brouard 6870:
6871: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6872: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6873: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6874: continue;
1.220 brouard 6875:
1.222 brouard 6876: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6877: jj1++;
6878: if (cptcovn > 0) {
1.264 brouard 6879: fprintf(fichtm,"\n<p><a name=\"rescov");
6880: for (cpt=1; cpt<=cptcoveff;cpt++){
6881: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6882: }
6883: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6884: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6885: }
6886: fprintf(fichtm,"\"</a>");
6887:
1.222 brouard 6888: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6889: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6890: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6891: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6892: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6893: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6894: }
1.237 brouard 6895: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6896: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6897: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6898: }
6899:
1.230 brouard 6900: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6901: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6902: if(invalidvarcomb[k1]){
6903: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6904: printf("\nCombination (%d) ignored because no cases \n",k1);
6905: continue;
6906: }
6907: }
6908: /* aij, bij */
1.259 brouard 6909: 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 6910: <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 6911: /* Pij */
1.241 brouard 6912: 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> \
6913: <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 6914: /* Quasi-incidences */
6915: 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 6916: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6917: 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 6918: 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> \
6919: <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 6920: /* Survival functions (period) in state j */
6921: for(cpt=1; cpt<=nlstate;cpt++){
1.241 brouard 6922: 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> \
6923: <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 6924: }
6925: /* State specific survival functions (period) */
6926: for(cpt=1; cpt<=nlstate;cpt++){
6927: fprintf(fichtm,"<br>\n- Survival functions from state %d in each live state and total.\
1.220 brouard 6928: Or probability to survive in various states (1 to %d) being in state %d at different ages. \
1.283 brouard 6929: <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 6930: }
1.288 brouard 6931: /* Period (forward stable) prevalence in each health state */
1.222 brouard 6932: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6933: 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> \
6934: <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 6935: }
6936: if(backcast==1){
1.288 brouard 6937: /* Backward prevalence in each health state */
1.222 brouard 6938: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6939: 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 6940: <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 6941: }
1.217 brouard 6942: }
1.222 brouard 6943: if(prevfcast==1){
1.288 brouard 6944: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 6945: for(cpt=1; cpt<=nlstate;cpt++){
1.288 brouard 6946: 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 6947: <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 6948: }
6949: }
1.268 brouard 6950: if(backcast==1){
6951: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
6952: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 6953: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
6954: 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 \
6955: 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) \
6956: with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
6957: <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 6958: }
6959: }
1.220 brouard 6960:
1.222 brouard 6961: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 6962: 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> \
6963: <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 6964: }
6965: /* } /\* end i1 *\/ */
6966: }/* End k1 */
6967: fprintf(fichtm,"</ul>");
1.126 brouard 6968:
1.222 brouard 6969: fprintf(fichtm,"\
1.126 brouard 6970: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 6971: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 6972: - 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 6973: But because parameters are usually highly correlated (a higher incidence of disability \
6974: and a higher incidence of recovery can give very close observed transition) it might \
6975: be very useful to look not only at linear confidence intervals estimated from the \
6976: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
6977: (parameters) of the logistic regression, it might be more meaningful to visualize the \
6978: covariance matrix of the one-step probabilities. \
6979: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 6980:
1.222 brouard 6981: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
6982: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
6983: fprintf(fichtm,"\
1.126 brouard 6984: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6985: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 6986:
1.222 brouard 6987: fprintf(fichtm,"\
1.126 brouard 6988: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6989: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
6990: fprintf(fichtm,"\
1.126 brouard 6991: - 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): \
6992: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6993: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 6994: fprintf(fichtm,"\
1.126 brouard 6995: - (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): \
6996: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6997: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 6998: fprintf(fichtm,"\
1.288 brouard 6999: - 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 7000: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
7001: fprintf(fichtm,"\
1.128 brouard 7002: - 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 7003: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7004: fprintf(fichtm,"\
1.288 brouard 7005: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7006: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7007:
7008: /* if(popforecast==1) fprintf(fichtm,"\n */
7009: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7010: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7011: /* <br>",fileres,fileres,fileres,fileres); */
7012: /* else */
7013: /* 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 7014: fflush(fichtm);
7015: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 7016:
1.225 brouard 7017: m=pow(2,cptcoveff);
1.222 brouard 7018: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7019:
1.222 brouard 7020: jj1=0;
1.237 brouard 7021:
1.241 brouard 7022: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7023: for(k1=1; k1<=m;k1++){
1.253 brouard 7024: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7025: continue;
1.222 brouard 7026: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7027: jj1++;
1.126 brouard 7028: if (cptcovn > 0) {
7029: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7030: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 7031: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
7032: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7033: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7034: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7035: }
7036:
1.126 brouard 7037: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 7038:
1.222 brouard 7039: if(invalidvarcomb[k1]){
7040: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7041: continue;
7042: }
1.126 brouard 7043: }
7044: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7045: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 7046: 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 7047: <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 7048: }
7049: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 7050: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
7051: true period expectancies (those weighted with period prevalences are also\
7052: drawn in addition to the population based expectancies computed using\
1.241 brouard 7053: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
7054: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7055: /* } /\* end i1 *\/ */
7056: }/* End k1 */
1.241 brouard 7057: }/* End nres */
1.222 brouard 7058: fprintf(fichtm,"</ul>");
7059: fflush(fichtm);
1.126 brouard 7060: }
7061:
7062: /******************* Gnuplot file **************/
1.270 brouard 7063: 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 7064:
7065: char dirfileres[132],optfileres[132];
1.264 brouard 7066: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7067: 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 7068: int lv=0, vlv=0, kl=0;
1.130 brouard 7069: int ng=0;
1.201 brouard 7070: int vpopbased;
1.223 brouard 7071: int ioffset; /* variable offset for columns */
1.270 brouard 7072: int iyearc=1; /* variable column for year of projection */
7073: int iagec=1; /* variable column for age of projection */
1.235 brouard 7074: int nres=0; /* Index of resultline */
1.266 brouard 7075: int istart=1; /* For starting graphs in projections */
1.219 brouard 7076:
1.126 brouard 7077: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7078: /* printf("Problem with file %s",optionfilegnuplot); */
7079: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7080: /* } */
7081:
7082: /*#ifdef windows */
7083: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7084: /*#endif */
1.225 brouard 7085: m=pow(2,cptcoveff);
1.126 brouard 7086:
1.274 brouard 7087: /* diagram of the model */
7088: fprintf(ficgp,"\n#Diagram of the model \n");
7089: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7090: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7091: 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);
7092:
7093: 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);
7094: fprintf(ficgp,"\n#show arrow\nunset label\n");
7095: 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);
7096: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7097: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7098: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7099: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7100:
1.202 brouard 7101: /* Contribution to likelihood */
7102: /* Plot the probability implied in the likelihood */
1.223 brouard 7103: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7104: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7105: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7106: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7107: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7108: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7109: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7110: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7111: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7112: 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));
7113: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7114: 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));
7115: for (i=1; i<= nlstate ; i ++) {
7116: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7117: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7118: 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);
7119: for (j=2; j<= nlstate+ndeath ; j ++) {
7120: 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);
7121: }
7122: fprintf(ficgp,";\nset out; unset ylabel;\n");
7123: }
7124: /* 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 */
7125: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7126: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7127: fprintf(ficgp,"\nset out;unset log\n");
7128: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7129:
1.126 brouard 7130: strcpy(dirfileres,optionfilefiname);
7131: strcpy(optfileres,"vpl");
1.223 brouard 7132: /* 1eme*/
1.238 brouard 7133: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7134: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7135: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7136: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7137: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7138: continue;
7139: /* We are interested in selected combination by the resultline */
1.246 brouard 7140: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 7141: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7142: strcpy(gplotlabel,"(");
1.238 brouard 7143: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7144: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7145: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7146: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7147: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7148: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7149: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7150: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7151: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7152: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7153: }
7154: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7155: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7156: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7157: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7158: }
7159: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7160: /* printf("\n#\n"); */
1.238 brouard 7161: fprintf(ficgp,"\n#\n");
7162: if(invalidvarcomb[k1]){
1.260 brouard 7163: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7164: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7165: continue;
7166: }
1.235 brouard 7167:
1.241 brouard 7168: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7169: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7170: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
7171: fprintf(ficgp,"set title \"Alive state %d %s\" font \"Helvetica,12\"\n",cpt,gplotlabel);
1.260 brouard 7172: 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);
7173: /* 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); */
7174: /* k1-1 error should be nres-1*/
1.238 brouard 7175: for (i=1; i<= nlstate ; i ++) {
7176: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7177: else fprintf(ficgp," %%*lf (%%*lf)");
7178: }
1.288 brouard 7179: 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 7180: for (i=1; i<= nlstate ; i ++) {
7181: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7182: else fprintf(ficgp," %%*lf (%%*lf)");
7183: }
1.260 brouard 7184: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7185: for (i=1; i<= nlstate ; i ++) {
7186: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7187: else fprintf(ficgp," %%*lf (%%*lf)");
7188: }
1.265 brouard 7189: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7190:
7191: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7192: if(cptcoveff ==0){
1.271 brouard 7193: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7194: }else{
7195: kl=0;
7196: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7197: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7198: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7199: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7200: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7201: vlv= nbcode[Tvaraff[k]][lv];
7202: kl++;
7203: /* 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 *\/ */
7204: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7205: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7206: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7207: if(k==cptcoveff){
7208: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7209: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7210: }else{
7211: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7212: kl++;
7213: }
7214: } /* end covariate */
7215: } /* end if no covariate */
7216:
1.238 brouard 7217: if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
7218: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7219: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7220: if(cptcoveff ==0){
1.245 brouard 7221: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7222: }else{
7223: kl=0;
7224: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7225: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7226: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7227: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7228: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7229: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7230: kl++;
1.238 brouard 7231: /* 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 *\/ */
7232: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7233: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7234: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7235: if(k==cptcoveff){
1.245 brouard 7236: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7237: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7238: }else{
7239: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7240: kl++;
7241: }
7242: } /* end covariate */
7243: } /* end if no covariate */
1.268 brouard 7244: if(backcast == 1){
7245: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7246: /* k1-1 error should be nres-1*/
7247: for (i=1; i<= nlstate ; i ++) {
7248: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7249: else fprintf(ficgp," %%*lf (%%*lf)");
7250: }
1.271 brouard 7251: 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 7252: for (i=1; i<= nlstate ; i ++) {
7253: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7254: else fprintf(ficgp," %%*lf (%%*lf)");
7255: }
1.276 brouard 7256: 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 7257: for (i=1; i<= nlstate ; i ++) {
7258: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7259: else fprintf(ficgp," %%*lf (%%*lf)");
7260: }
1.274 brouard 7261: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7262: } /* end if backprojcast */
1.238 brouard 7263: } /* end if backcast */
1.276 brouard 7264: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7265: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7266: } /* nres */
1.201 brouard 7267: } /* k1 */
7268: } /* cpt */
1.235 brouard 7269:
7270:
1.126 brouard 7271: /*2 eme*/
1.238 brouard 7272: for (k1=1; k1<= m ; k1 ++){
7273: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7274: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7275: continue;
7276: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7277: strcpy(gplotlabel,"(");
1.238 brouard 7278: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7279: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7280: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7281: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7282: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7283: vlv= nbcode[Tvaraff[k]][lv];
7284: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7285: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7286: }
1.237 brouard 7287: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7288: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7289: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7290: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7291: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7292: }
1.264 brouard 7293: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7294: fprintf(ficgp,"\n#\n");
1.223 brouard 7295: if(invalidvarcomb[k1]){
7296: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7297: continue;
7298: }
1.219 brouard 7299:
1.241 brouard 7300: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7301: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7302: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7303: if(vpopbased==0){
1.238 brouard 7304: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7305: }else
1.238 brouard 7306: fprintf(ficgp,"\nreplot ");
7307: for (i=1; i<= nlstate+1 ; i ++) {
7308: k=2*i;
1.261 brouard 7309: 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 7310: for (j=1; j<= nlstate+1 ; j ++) {
7311: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7312: else fprintf(ficgp," %%*lf (%%*lf)");
7313: }
7314: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7315: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7316: 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 7317: for (j=1; j<= nlstate+1 ; j ++) {
7318: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7319: else fprintf(ficgp," %%*lf (%%*lf)");
7320: }
7321: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7322: 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 7323: for (j=1; j<= nlstate+1 ; j ++) {
7324: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7325: else fprintf(ficgp," %%*lf (%%*lf)");
7326: }
7327: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7328: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7329: } /* state */
7330: } /* vpopbased */
1.264 brouard 7331: 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 7332: } /* end nres */
7333: } /* k1 end 2 eme*/
7334:
7335:
7336: /*3eme*/
7337: for (k1=1; k1<= m ; k1 ++){
7338: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7339: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7340: continue;
7341:
7342: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7343: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7344: strcpy(gplotlabel,"(");
1.238 brouard 7345: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7346: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7347: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7348: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7349: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7350: vlv= nbcode[Tvaraff[k]][lv];
7351: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7352: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7353: }
7354: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7355: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7356: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7357: }
1.264 brouard 7358: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7359: fprintf(ficgp,"\n#\n");
7360: if(invalidvarcomb[k1]){
7361: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7362: continue;
7363: }
7364:
7365: /* k=2+nlstate*(2*cpt-2); */
7366: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7367: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7368: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7369: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7370: 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 7371: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7372: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7373: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7374: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7375: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7376: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7377:
1.238 brouard 7378: */
7379: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7380: 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 7381: /* 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 7382:
1.238 brouard 7383: }
1.261 brouard 7384: 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 7385: }
1.264 brouard 7386: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7387: } /* end nres */
7388: } /* end kl 3eme */
1.126 brouard 7389:
1.223 brouard 7390: /* 4eme */
1.201 brouard 7391: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7392: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7393: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7394: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7395: continue;
1.238 brouard 7396: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7397: strcpy(gplotlabel,"(");
1.238 brouard 7398: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7399: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7400: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7401: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7402: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7403: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7404: vlv= nbcode[Tvaraff[k]][lv];
7405: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7406: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7407: }
7408: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7409: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7410: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7411: }
1.264 brouard 7412: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7413: fprintf(ficgp,"\n#\n");
7414: if(invalidvarcomb[k1]){
7415: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7416: continue;
1.223 brouard 7417: }
1.238 brouard 7418:
1.241 brouard 7419: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7420: 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 7421: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7422: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7423: k=3;
7424: for (i=1; i<= nlstate ; i ++){
7425: if(i==1){
7426: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7427: }else{
7428: fprintf(ficgp,", '' ");
7429: }
7430: l=(nlstate+ndeath)*(i-1)+1;
7431: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7432: for (j=2; j<= nlstate+ndeath ; j ++)
7433: fprintf(ficgp,"+$%d",k+l+j-1);
7434: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7435: } /* nlstate */
1.264 brouard 7436: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7437: } /* end cpt state*/
7438: } /* end nres */
7439: } /* end covariate k1 */
7440:
1.220 brouard 7441: /* 5eme */
1.201 brouard 7442: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7443: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7444: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7445: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7446: continue;
1.238 brouard 7447: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7448: strcpy(gplotlabel,"(");
1.238 brouard 7449: 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);
7450: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7451: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7452: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7453: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7454: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7455: vlv= nbcode[Tvaraff[k]][lv];
7456: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7457: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7458: }
7459: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7460: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7461: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7462: }
1.264 brouard 7463: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7464: fprintf(ficgp,"\n#\n");
7465: if(invalidvarcomb[k1]){
7466: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7467: continue;
7468: }
1.227 brouard 7469:
1.241 brouard 7470: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7471: 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 7472: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7473: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7474: k=3;
7475: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7476: if(j==1)
7477: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7478: else
7479: fprintf(ficgp,", '' ");
7480: l=(nlstate+ndeath)*(cpt-1) +j;
7481: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7482: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7483: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7484: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7485: } /* nlstate */
7486: fprintf(ficgp,", '' ");
7487: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7488: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7489: l=(nlstate+ndeath)*(cpt-1) +j;
7490: if(j < nlstate)
7491: fprintf(ficgp,"$%d +",k+l);
7492: else
7493: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7494: }
1.264 brouard 7495: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7496: } /* end cpt state*/
7497: } /* end covariate */
7498: } /* end nres */
1.227 brouard 7499:
1.220 brouard 7500: /* 6eme */
1.202 brouard 7501: /* CV preval stable (period) for each covariate */
1.237 brouard 7502: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7503: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7504: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7505: continue;
1.255 brouard 7506: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7507: strcpy(gplotlabel,"(");
1.288 brouard 7508: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7509: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7510: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7511: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7512: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7513: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7514: vlv= nbcode[Tvaraff[k]][lv];
7515: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7516: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7517: }
1.237 brouard 7518: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7519: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7520: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7521: }
1.264 brouard 7522: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7523: fprintf(ficgp,"\n#\n");
1.223 brouard 7524: if(invalidvarcomb[k1]){
1.227 brouard 7525: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7526: continue;
1.223 brouard 7527: }
1.227 brouard 7528:
1.241 brouard 7529: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7530: 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 7531: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7532: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7533: k=3; /* Offset */
1.255 brouard 7534: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7535: if(i==1)
7536: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7537: else
7538: fprintf(ficgp,", '' ");
1.255 brouard 7539: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7540: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7541: for (j=2; j<= nlstate ; j ++)
7542: fprintf(ficgp,"+$%d",k+l+j-1);
7543: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7544: } /* nlstate */
1.264 brouard 7545: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7546: } /* end cpt state*/
7547: } /* end covariate */
1.227 brouard 7548:
7549:
1.220 brouard 7550: /* 7eme */
1.218 brouard 7551: if(backcast == 1){
1.288 brouard 7552: /* CV backward prevalence for each covariate */
1.237 brouard 7553: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7554: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7555: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7556: continue;
1.268 brouard 7557: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7558: strcpy(gplotlabel,"(");
1.288 brouard 7559: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7560: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7561: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7562: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7563: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7564: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7565: vlv= nbcode[Tvaraff[k]][lv];
7566: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7567: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7568: }
1.237 brouard 7569: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7570: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7571: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7572: }
1.264 brouard 7573: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7574: fprintf(ficgp,"\n#\n");
7575: if(invalidvarcomb[k1]){
7576: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7577: continue;
7578: }
7579:
1.241 brouard 7580: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7581: 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 7582: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7583: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7584: k=3; /* Offset */
1.268 brouard 7585: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7586: if(i==1)
7587: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7588: else
7589: fprintf(ficgp,", '' ");
7590: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7591: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7592: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7593: /* 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 7594: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7595: /* for (j=2; j<= nlstate ; j ++) */
7596: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7597: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7598: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7599: } /* nlstate */
1.264 brouard 7600: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7601: } /* end cpt state*/
7602: } /* end covariate */
7603: } /* End if backcast */
7604:
1.223 brouard 7605: /* 8eme */
1.218 brouard 7606: if(prevfcast==1){
1.288 brouard 7607: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 7608:
1.237 brouard 7609: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7610: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7611: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7612: continue;
1.211 brouard 7613: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7614: strcpy(gplotlabel,"(");
1.288 brouard 7615: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7616: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7617: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7618: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7619: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7620: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7621: vlv= nbcode[Tvaraff[k]][lv];
7622: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7623: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7624: }
1.237 brouard 7625: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7626: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7627: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7628: }
1.264 brouard 7629: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7630: fprintf(ficgp,"\n#\n");
7631: if(invalidvarcomb[k1]){
7632: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7633: continue;
7634: }
7635:
7636: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7637: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7638: 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 7639: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7640: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7641:
7642: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7643: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7644: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7645: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7646: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7647: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7648: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7649: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7650: if(i==istart){
1.227 brouard 7651: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7652: }else{
7653: fprintf(ficgp,",\\\n '' ");
7654: }
7655: if(cptcoveff ==0){ /* No covariate */
7656: ioffset=2; /* Age is in 2 */
7657: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7658: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7659: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7660: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7661: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7662: if(i==nlstate+1){
1.270 brouard 7663: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 7664: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7665: fprintf(ficgp,",\\\n '' ");
7666: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7667: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 7668: offyear, \
1.268 brouard 7669: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7670: }else
1.227 brouard 7671: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7672: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7673: }else{ /* more than 2 covariates */
1.270 brouard 7674: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7675: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7676: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7677: iyearc=ioffset-1;
7678: iagec=ioffset;
1.227 brouard 7679: fprintf(ficgp," u %d:(",ioffset);
7680: kl=0;
7681: strcpy(gplotcondition,"(");
7682: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7683: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7684: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7685: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7686: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7687: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7688: kl++;
7689: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7690: kl++;
7691: if(k <cptcoveff && cptcoveff>1)
7692: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7693: }
7694: strcpy(gplotcondition+strlen(gplotcondition),")");
7695: /* 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 *\/ */
7696: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7697: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7698: /* '' 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*/
7699: if(i==nlstate+1){
1.270 brouard 7700: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
7701: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 7702: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7703: fprintf(ficgp," u %d:(",iagec);
7704: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
7705: iyearc, iagec, offyear, \
7706: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 7707: /* '' 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 7708: }else{
7709: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7710: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7711: }
7712: } /* end if covariate */
7713: } /* nlstate */
1.264 brouard 7714: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7715: } /* end cpt state*/
7716: } /* end covariate */
7717: } /* End if prevfcast */
1.227 brouard 7718:
1.268 brouard 7719: if(backcast==1){
7720: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7721:
7722: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7723: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7724: if(m != 1 && TKresult[nres]!= k1)
7725: continue;
7726: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7727: strcpy(gplotlabel,"(");
7728: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7729: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7730: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7731: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7732: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7733: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7734: vlv= nbcode[Tvaraff[k]][lv];
7735: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7736: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7737: }
7738: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7739: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7740: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7741: }
7742: strcpy(gplotlabel+strlen(gplotlabel),")");
7743: fprintf(ficgp,"\n#\n");
7744: if(invalidvarcomb[k1]){
7745: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7746: continue;
7747: }
7748:
7749: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7750: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7751: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7752: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7753: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7754:
7755: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7756: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7757: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7758: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7759: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7760: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7761: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7762: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7763: if(i==istart){
7764: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
7765: }else{
7766: fprintf(ficgp,",\\\n '' ");
7767: }
7768: if(cptcoveff ==0){ /* No covariate */
7769: ioffset=2; /* Age is in 2 */
7770: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7771: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7772: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7773: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7774: fprintf(ficgp," u %d:(", ioffset);
7775: if(i==nlstate+1){
1.270 brouard 7776: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 7777: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7778: fprintf(ficgp,",\\\n '' ");
7779: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7780: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 7781: offbyear, \
7782: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7783: }else
7784: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
7785: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
7786: }else{ /* more than 2 covariates */
1.270 brouard 7787: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7788: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7789: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7790: iyearc=ioffset-1;
7791: iagec=ioffset;
1.268 brouard 7792: fprintf(ficgp," u %d:(",ioffset);
7793: kl=0;
7794: strcpy(gplotcondition,"(");
7795: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7796: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7797: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7798: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7799: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7800: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7801: kl++;
7802: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7803: kl++;
7804: if(k <cptcoveff && cptcoveff>1)
7805: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7806: }
7807: strcpy(gplotcondition+strlen(gplotcondition),")");
7808: /* 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 *\/ */
7809: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7810: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7811: /* '' 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*/
7812: if(i==nlstate+1){
1.270 brouard 7813: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
7814: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 7815: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7816: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 7817: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 7818: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
7819: iyearc,iagec,offbyear, \
7820: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 7821: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
7822: }else{
7823: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
7824: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
7825: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
7826: }
7827: } /* end if covariate */
7828: } /* nlstate */
7829: fprintf(ficgp,"\nset out; unset label;\n");
7830: } /* end cpt state*/
7831: } /* end covariate */
7832: } /* End if backcast */
7833:
1.227 brouard 7834:
1.238 brouard 7835: /* 9eme writing MLE parameters */
7836: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7837: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7838: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7839: for(k=1; k <=(nlstate+ndeath); k++){
7840: if (k != i) {
1.227 brouard 7841: fprintf(ficgp,"# current state %d\n",k);
7842: for(j=1; j <=ncovmodel; j++){
7843: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7844: jk++;
7845: }
7846: fprintf(ficgp,"\n");
1.126 brouard 7847: }
7848: }
1.223 brouard 7849: }
1.187 brouard 7850: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7851:
1.145 brouard 7852: /*goto avoid;*/
1.238 brouard 7853: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7854: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7855: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7856: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7857: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7858: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7859: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7860: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7861: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7862: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7863: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7864: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7865: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7866: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7867: fprintf(ficgp,"#\n");
1.223 brouard 7868: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7869: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7870: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7871: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 7872: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
7873: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7874: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 7875: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7876: continue;
1.264 brouard 7877: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
7878: strcpy(gplotlabel,"(");
1.276 brouard 7879: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 7880: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7881: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7882: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7883: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7884: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7885: vlv= nbcode[Tvaraff[k]][lv];
7886: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7887: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7888: }
1.237 brouard 7889: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7890: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7891: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7892: }
1.264 brouard 7893: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7894: fprintf(ficgp,"\n#\n");
1.264 brouard 7895: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 7896: fprintf(ficgp,"\nset key outside ");
7897: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
7898: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7899: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7900: if (ng==1){
7901: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7902: fprintf(ficgp,"\nunset log y");
7903: }else if (ng==2){
7904: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7905: fprintf(ficgp,"\nset log y");
7906: }else if (ng==3){
7907: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7908: fprintf(ficgp,"\nset log y");
7909: }else
7910: fprintf(ficgp,"\nunset title ");
7911: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7912: i=1;
7913: for(k2=1; k2<=nlstate; k2++) {
7914: k3=i;
7915: for(k=1; k<=(nlstate+ndeath); k++) {
7916: if (k != k2){
7917: switch( ng) {
7918: case 1:
7919: if(nagesqr==0)
7920: fprintf(ficgp," p%d+p%d*x",i,i+1);
7921: else /* nagesqr =1 */
7922: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7923: break;
7924: case 2: /* ng=2 */
7925: if(nagesqr==0)
7926: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
7927: else /* nagesqr =1 */
7928: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7929: break;
7930: case 3:
7931: if(nagesqr==0)
7932: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
7933: else /* nagesqr =1 */
7934: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
7935: break;
7936: }
7937: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 7938: ijp=1; /* product no age */
7939: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
7940: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 7941: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 7942: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7943: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
7944: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7945: if(DummyV[j]==0){
7946: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
7947: }else{ /* quantitative */
7948: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
7949: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7950: }
7951: ij++;
1.237 brouard 7952: }
1.268 brouard 7953: }
7954: }else if(cptcovprod >0){
7955: if(j==Tprod[ijp]) { /* */
7956: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
7957: if(ijp <=cptcovprod) { /* Product */
7958: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
7959: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
7960: /* 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)]); */
7961: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
7962: }else{ /* Vn is dummy and Vm is quanti */
7963: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
7964: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7965: }
7966: }else{ /* Vn*Vm Vn is quanti */
7967: if(DummyV[Tvard[ijp][2]]==0){
7968: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
7969: }else{ /* Both quanti */
7970: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7971: }
1.237 brouard 7972: }
1.268 brouard 7973: ijp++;
1.237 brouard 7974: }
1.268 brouard 7975: } /* end Tprod */
1.237 brouard 7976: } else{ /* simple covariate */
1.264 brouard 7977: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 7978: if(Dummy[j]==0){
7979: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
7980: }else{ /* quantitative */
7981: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 7982: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 7983: }
1.237 brouard 7984: } /* end simple */
7985: } /* end j */
1.223 brouard 7986: }else{
7987: i=i-ncovmodel;
7988: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
7989: fprintf(ficgp," (1.");
7990: }
1.227 brouard 7991:
1.223 brouard 7992: if(ng != 1){
7993: fprintf(ficgp,")/(1");
1.227 brouard 7994:
1.264 brouard 7995: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 7996: if(nagesqr==0)
1.264 brouard 7997: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 7998: else /* nagesqr =1 */
1.264 brouard 7999: 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 8000:
1.223 brouard 8001: ij=1;
8002: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 8003: if(cptcovage >0){
8004: if((j-2)==Tage[ij]) { /* Bug valgrind */
8005: if(ij <=cptcovage) { /* Bug valgrind */
8006: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
8007: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8008: ij++;
8009: }
8010: }
8011: }else
8012: 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 8013: }
8014: fprintf(ficgp,")");
8015: }
8016: fprintf(ficgp,")");
8017: if(ng ==2)
1.276 brouard 8018: 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 8019: else /* ng= 3 */
1.276 brouard 8020: 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 8021: }else{ /* end ng <> 1 */
8022: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8023: 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 8024: }
8025: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8026: fprintf(ficgp,",");
8027: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8028: fprintf(ficgp,",");
8029: i=i+ncovmodel;
8030: } /* end k */
8031: } /* end k2 */
1.276 brouard 8032: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8033: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8034: } /* end k1 */
1.223 brouard 8035: } /* end ng */
8036: /* avoid: */
8037: fflush(ficgp);
1.126 brouard 8038: } /* end gnuplot */
8039:
8040:
8041: /*************** Moving average **************/
1.219 brouard 8042: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8043: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8044:
1.222 brouard 8045: int i, cpt, cptcod;
8046: int modcovmax =1;
8047: int mobilavrange, mob;
8048: int iage=0;
1.288 brouard 8049: int firstA1=0, firstA2=0;
1.222 brouard 8050:
1.266 brouard 8051: double sum=0., sumr=0.;
1.222 brouard 8052: double age;
1.266 brouard 8053: double *sumnewp, *sumnewm, *sumnewmr;
8054: double *agemingood, *agemaxgood;
8055: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8056:
8057:
1.278 brouard 8058: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8059: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8060:
8061: sumnewp = vector(1,ncovcombmax);
8062: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8063: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8064: agemingood = vector(1,ncovcombmax);
1.266 brouard 8065: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8066: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8067: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8068:
8069: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8070: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8071: sumnewp[cptcod]=0.;
1.266 brouard 8072: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8073: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8074: }
8075: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8076:
1.266 brouard 8077: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8078: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8079: else mobilavrange=mobilav;
8080: for (age=bage; age<=fage; age++)
8081: for (i=1; i<=nlstate;i++)
8082: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8083: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8084: /* We keep the original values on the extreme ages bage, fage and for
8085: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8086: we use a 5 terms etc. until the borders are no more concerned.
8087: */
8088: for (mob=3;mob <=mobilavrange;mob=mob+2){
8089: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8090: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8091: sumnewm[cptcod]=0.;
8092: for (i=1; i<=nlstate;i++){
1.222 brouard 8093: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8094: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8095: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8096: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8097: }
8098: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8099: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8100: } /* end i */
8101: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8102: } /* end cptcod */
1.222 brouard 8103: }/* end age */
8104: }/* end mob */
1.266 brouard 8105: }else{
8106: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8107: return -1;
1.266 brouard 8108: }
8109:
8110: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8111: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8112: if(invalidvarcomb[cptcod]){
8113: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8114: continue;
8115: }
1.219 brouard 8116:
1.266 brouard 8117: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8118: sumnewm[cptcod]=0.;
8119: sumnewmr[cptcod]=0.;
8120: for (i=1; i<=nlstate;i++){
8121: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8122: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8123: }
8124: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8125: agemingoodr[cptcod]=age;
8126: }
8127: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8128: agemingood[cptcod]=age;
8129: }
8130: } /* age */
8131: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8132: sumnewm[cptcod]=0.;
1.266 brouard 8133: sumnewmr[cptcod]=0.;
1.222 brouard 8134: for (i=1; i<=nlstate;i++){
8135: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8136: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8137: }
8138: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8139: agemaxgoodr[cptcod]=age;
1.222 brouard 8140: }
8141: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8142: agemaxgood[cptcod]=age;
8143: }
8144: } /* age */
8145: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8146: /* but they will change */
1.288 brouard 8147: firstA1=0;firstA2=0;
1.266 brouard 8148: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8149: sumnewm[cptcod]=0.;
8150: sumnewmr[cptcod]=0.;
8151: for (i=1; i<=nlstate;i++){
8152: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8153: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8154: }
8155: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8156: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8157: agemaxgoodr[cptcod]=age; /* age min */
8158: for (i=1; i<=nlstate;i++)
8159: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8160: }else{ /* bad we change the value with the values of good ages */
8161: for (i=1; i<=nlstate;i++){
8162: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8163: } /* i */
8164: } /* end bad */
8165: }else{
8166: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8167: agemaxgood[cptcod]=age;
8168: }else{ /* bad we change the value with the values of good ages */
8169: for (i=1; i<=nlstate;i++){
8170: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8171: } /* i */
8172: } /* end bad */
8173: }/* end else */
8174: sum=0.;sumr=0.;
8175: for (i=1; i<=nlstate;i++){
8176: sum+=mobaverage[(int)age][i][cptcod];
8177: sumr+=probs[(int)age][i][cptcod];
8178: }
8179: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 8180: if(!firstA1){
8181: firstA1=1;
8182: 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);
8183: }
8184: 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 8185: } /* end bad */
8186: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8187: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 8188: if(!firstA2){
8189: firstA2=1;
8190: 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);
8191: }
8192: 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 8193: } /* end bad */
8194: }/* age */
1.266 brouard 8195:
8196: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8197: sumnewm[cptcod]=0.;
1.266 brouard 8198: sumnewmr[cptcod]=0.;
1.222 brouard 8199: for (i=1; i<=nlstate;i++){
8200: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8201: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8202: }
8203: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8204: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8205: agemingoodr[cptcod]=age;
8206: for (i=1; i<=nlstate;i++)
8207: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8208: }else{ /* bad we change the value with the values of good ages */
8209: for (i=1; i<=nlstate;i++){
8210: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8211: } /* i */
8212: } /* end bad */
8213: }else{
8214: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8215: agemingood[cptcod]=age;
8216: }else{ /* bad */
8217: for (i=1; i<=nlstate;i++){
8218: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8219: } /* i */
8220: } /* end bad */
8221: }/* end else */
8222: sum=0.;sumr=0.;
8223: for (i=1; i<=nlstate;i++){
8224: sum+=mobaverage[(int)age][i][cptcod];
8225: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8226: }
1.266 brouard 8227: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8228: 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 8229: } /* end bad */
8230: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8231: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8232: 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 8233: } /* end bad */
8234: }/* age */
1.266 brouard 8235:
1.222 brouard 8236:
8237: for (age=bage; age<=fage; age++){
1.235 brouard 8238: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8239: sumnewp[cptcod]=0.;
8240: sumnewm[cptcod]=0.;
8241: for (i=1; i<=nlstate;i++){
8242: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8243: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8244: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8245: }
8246: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8247: }
8248: /* printf("\n"); */
8249: /* } */
1.266 brouard 8250:
1.222 brouard 8251: /* brutal averaging */
1.266 brouard 8252: /* for (i=1; i<=nlstate;i++){ */
8253: /* for (age=1; age<=bage; age++){ */
8254: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8255: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8256: /* } */
8257: /* for (age=fage; age<=AGESUP; age++){ */
8258: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[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: /* } /\* end i status *\/ */
8262: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8263: /* for (age=1; age<=AGESUP; age++){ */
8264: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8265: /* mobaverage[(int)age][i][cptcod]=0.; */
8266: /* } */
8267: /* } */
1.222 brouard 8268: }/* end cptcod */
1.266 brouard 8269: free_vector(agemaxgoodr,1, ncovcombmax);
8270: free_vector(agemaxgood,1, ncovcombmax);
8271: free_vector(agemingood,1, ncovcombmax);
8272: free_vector(agemingoodr,1, ncovcombmax);
8273: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8274: free_vector(sumnewm,1, ncovcombmax);
8275: free_vector(sumnewp,1, ncovcombmax);
8276: return 0;
8277: }/* End movingaverage */
1.218 brouard 8278:
1.126 brouard 8279:
8280: /************** Forecasting ******************/
1.269 brouard 8281: 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 8282: /* proj1, year, month, day of starting projection
8283: agemin, agemax range of age
8284: dateprev1 dateprev2 range of dates during which prevalence is computed
8285: anproj2 year of en of projection (same day and month as proj1).
8286: */
1.267 brouard 8287: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8288: double agec; /* generic age */
8289: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
8290: double *popeffectif,*popcount;
8291: double ***p3mat;
1.218 brouard 8292: /* double ***mobaverage; */
1.126 brouard 8293: char fileresf[FILENAMELENGTH];
8294:
8295: agelim=AGESUP;
1.211 brouard 8296: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8297: in each health status at the date of interview (if between dateprev1 and dateprev2).
8298: We still use firstpass and lastpass as another selection.
8299: */
1.214 brouard 8300: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8301: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8302:
1.201 brouard 8303: strcpy(fileresf,"F_");
8304: strcat(fileresf,fileresu);
1.126 brouard 8305: if((ficresf=fopen(fileresf,"w"))==NULL) {
8306: printf("Problem with forecast resultfile: %s\n", fileresf);
8307: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8308: }
1.235 brouard 8309: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8310: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8311:
1.225 brouard 8312: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8313:
8314:
8315: stepsize=(int) (stepm+YEARM-1)/YEARM;
8316: if (stepm<=12) stepsize=1;
8317: if(estepm < stepm){
8318: printf ("Problem %d lower than %d\n",estepm, stepm);
8319: }
1.270 brouard 8320: else{
8321: hstepm=estepm;
8322: }
8323: if(estepm > stepm){ /* Yes every two year */
8324: stepsize=2;
8325: }
1.126 brouard 8326:
8327: hstepm=hstepm/stepm;
8328: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8329: fractional in yp1 */
8330: anprojmean=yp;
8331: yp2=modf((yp1*12),&yp);
8332: mprojmean=yp;
8333: yp1=modf((yp2*30.5),&yp);
8334: jprojmean=yp;
8335: if(jprojmean==0) jprojmean=1;
8336: if(mprojmean==0) jprojmean=1;
8337:
1.227 brouard 8338: i1=pow(2,cptcoveff);
1.126 brouard 8339: if (cptcovn < 1){i1=1;}
8340:
8341: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
8342:
8343: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8344:
1.126 brouard 8345: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8346: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8347: for(k=1; k<=i1;k++){
1.253 brouard 8348: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8349: continue;
1.227 brouard 8350: if(invalidvarcomb[k]){
8351: printf("\nCombination (%d) projection ignored because no cases \n",k);
8352: continue;
8353: }
8354: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8355: for(j=1;j<=cptcoveff;j++) {
8356: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8357: }
1.235 brouard 8358: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8359: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8360: }
1.227 brouard 8361: fprintf(ficresf," yearproj age");
8362: for(j=1; j<=nlstate+ndeath;j++){
8363: for(i=1; i<=nlstate;i++)
8364: fprintf(ficresf," p%d%d",i,j);
8365: fprintf(ficresf," wp.%d",j);
8366: }
8367: for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {
8368: fprintf(ficresf,"\n");
8369: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
1.270 brouard 8370: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8371: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8372: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8373: nhstepm = nhstepm/hstepm;
8374: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8375: oldm=oldms;savm=savms;
1.268 brouard 8376: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8377: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8378: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8379: for (h=0; h<=nhstepm; h++){
8380: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8381: break;
8382: }
8383: }
8384: fprintf(ficresf,"\n");
8385: for(j=1;j<=cptcoveff;j++)
8386: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8387: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
8388:
8389: for(j=1; j<=nlstate+ndeath;j++) {
8390: ppij=0.;
8391: for(i=1; i<=nlstate;i++) {
1.278 brouard 8392: if (mobilav>=1)
8393: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8394: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8395: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8396: }
1.268 brouard 8397: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8398: } /* end i */
8399: fprintf(ficresf," %.3f", ppij);
8400: }/* end j */
1.227 brouard 8401: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8402: } /* end agec */
1.266 brouard 8403: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8404: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8405: } /* end yearp */
8406: } /* end k */
1.219 brouard 8407:
1.126 brouard 8408: fclose(ficresf);
1.215 brouard 8409: printf("End of Computing forecasting \n");
8410: fprintf(ficlog,"End of Computing forecasting\n");
8411:
1.126 brouard 8412: }
8413:
1.269 brouard 8414: /************** Back Forecasting ******************/
8415: 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 8416: /* back1, year, month, day of starting backection
8417: agemin, agemax range of age
8418: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8419: anback2 year of end of backprojection (same day and month as back1).
8420: prevacurrent and prev are prevalences.
1.267 brouard 8421: */
8422: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8423: double agec; /* generic age */
1.268 brouard 8424: double agelim, ppij, ppi, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
1.267 brouard 8425: double *popeffectif,*popcount;
8426: double ***p3mat;
8427: /* double ***mobaverage; */
8428: char fileresfb[FILENAMELENGTH];
8429:
1.268 brouard 8430: agelim=AGEINF;
1.267 brouard 8431: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8432: in each health status at the date of interview (if between dateprev1 and dateprev2).
8433: We still use firstpass and lastpass as another selection.
8434: */
8435: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8436: /* firstpass, lastpass, stepm, weightopt, model); */
8437:
8438: /*Do we need to compute prevalence again?*/
8439:
8440: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8441:
8442: strcpy(fileresfb,"FB_");
8443: strcat(fileresfb,fileresu);
8444: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8445: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8446: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8447: }
8448: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8449: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8450:
8451: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8452:
8453:
8454: stepsize=(int) (stepm+YEARM-1)/YEARM;
8455: if (stepm<=12) stepsize=1;
8456: if(estepm < stepm){
8457: printf ("Problem %d lower than %d\n",estepm, stepm);
8458: }
1.270 brouard 8459: else{
8460: hstepm=estepm;
8461: }
8462: if(estepm >= stepm){ /* Yes every two year */
8463: stepsize=2;
8464: }
1.267 brouard 8465:
8466: hstepm=hstepm/stepm;
8467: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8468: fractional in yp1 */
8469: anprojmean=yp;
8470: yp2=modf((yp1*12),&yp);
8471: mprojmean=yp;
8472: yp1=modf((yp2*30.5),&yp);
8473: jprojmean=yp;
8474: if(jprojmean==0) jprojmean=1;
8475: if(mprojmean==0) jprojmean=1;
8476:
8477: i1=pow(2,cptcoveff);
8478: if (cptcovn < 1){i1=1;}
8479:
8480: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.268 brouard 8481: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8482:
8483: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8484:
8485: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8486: for(k=1; k<=i1;k++){
8487: if(i1 != 1 && TKresult[nres]!= k)
8488: continue;
8489: if(invalidvarcomb[k]){
8490: printf("\nCombination (%d) projection ignored because no cases \n",k);
8491: continue;
8492: }
1.268 brouard 8493: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8494: for(j=1;j<=cptcoveff;j++) {
8495: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8496: }
8497: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8498: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8499: }
8500: fprintf(ficresfb," yearbproj age");
8501: for(j=1; j<=nlstate+ndeath;j++){
8502: for(i=1; i<=nlstate;i++)
1.268 brouard 8503: fprintf(ficresfb," b%d%d",i,j);
8504: fprintf(ficresfb," b.%d",j);
1.267 brouard 8505: }
8506: for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) {
8507: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8508: fprintf(ficresfb,"\n");
8509: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp);
1.273 brouard 8510: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8511: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8512: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8513: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8514: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8515: nhstepm = nhstepm/hstepm;
8516: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8517: oldm=oldms;savm=savms;
1.268 brouard 8518: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8519: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8520: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8521: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8522: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8523: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8524: for (h=0; h<=nhstepm; h++){
1.268 brouard 8525: if (h*hstepm/YEARM*stepm ==-yearp) {
8526: break;
8527: }
8528: }
8529: fprintf(ficresfb,"\n");
8530: for(j=1;j<=cptcoveff;j++)
8531: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8532: fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec-h*hstepm/YEARM*stepm);
8533: for(i=1; i<=nlstate+ndeath;i++) {
8534: ppij=0.;ppi=0.;
8535: for(j=1; j<=nlstate;j++) {
8536: /* if (mobilav==1) */
1.269 brouard 8537: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8538: ppi=ppi+prevacurrent[(int)agec][j][k];
8539: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8540: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8541: /* else { */
8542: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8543: /* } */
1.268 brouard 8544: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8545: } /* end j */
8546: if(ppi <0.99){
8547: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8548: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8549: }
8550: fprintf(ficresfb," %.3f", ppij);
8551: }/* end j */
1.267 brouard 8552: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8553: } /* end agec */
8554: } /* end yearp */
8555: } /* end k */
1.217 brouard 8556:
1.267 brouard 8557: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8558:
1.267 brouard 8559: fclose(ficresfb);
8560: printf("End of Computing Back forecasting \n");
8561: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8562:
1.267 brouard 8563: }
1.217 brouard 8564:
1.269 brouard 8565: /* Variance of prevalence limit: varprlim */
8566: 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 8567: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 8568:
8569: char fileresvpl[FILENAMELENGTH];
8570: FILE *ficresvpl;
8571: double **oldm, **savm;
8572: double **varpl; /* Variances of prevalence limits by age */
8573: int i1, k, nres, j ;
8574:
8575: strcpy(fileresvpl,"VPL_");
8576: strcat(fileresvpl,fileresu);
8577: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 8578: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 8579: exit(0);
8580: }
1.288 brouard 8581: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8582: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 8583:
8584: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8585: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8586:
8587: i1=pow(2,cptcoveff);
8588: if (cptcovn < 1){i1=1;}
8589:
8590: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8591: for(k=1; k<=i1;k++){
8592: if(i1 != 1 && TKresult[nres]!= k)
8593: continue;
8594: fprintf(ficresvpl,"\n#****** ");
8595: printf("\n#****** ");
8596: fprintf(ficlog,"\n#****** ");
8597: for(j=1;j<=cptcoveff;j++) {
8598: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8599: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8600: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8601: }
8602: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8603: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8604: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8605: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8606: }
8607: fprintf(ficresvpl,"******\n");
8608: printf("******\n");
8609: fprintf(ficlog,"******\n");
8610:
8611: varpl=matrix(1,nlstate,(int) bage, (int) fage);
8612: oldm=oldms;savm=savms;
8613: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
8614: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
8615: /*}*/
8616: }
8617:
8618: fclose(ficresvpl);
1.288 brouard 8619: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
8620: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 8621:
8622: }
8623: /* Variance of back prevalence: varbprlim */
8624: 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){
8625: /*------- Variance of back (stable) prevalence------*/
8626:
8627: char fileresvbl[FILENAMELENGTH];
8628: FILE *ficresvbl;
8629:
8630: double **oldm, **savm;
8631: double **varbpl; /* Variances of back prevalence limits by age */
8632: int i1, k, nres, j ;
8633:
8634: strcpy(fileresvbl,"VBL_");
8635: strcat(fileresvbl,fileresu);
8636: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
8637: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
8638: exit(0);
8639: }
8640: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
8641: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
8642:
8643:
8644: i1=pow(2,cptcoveff);
8645: if (cptcovn < 1){i1=1;}
8646:
8647: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8648: for(k=1; k<=i1;k++){
8649: if(i1 != 1 && TKresult[nres]!= k)
8650: continue;
8651: fprintf(ficresvbl,"\n#****** ");
8652: printf("\n#****** ");
8653: fprintf(ficlog,"\n#****** ");
8654: for(j=1;j<=cptcoveff;j++) {
8655: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8656: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8657: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8658: }
8659: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8660: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8661: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8662: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8663: }
8664: fprintf(ficresvbl,"******\n");
8665: printf("******\n");
8666: fprintf(ficlog,"******\n");
8667:
8668: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
8669: oldm=oldms;savm=savms;
8670:
8671: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
8672: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
8673: /*}*/
8674: }
8675:
8676: fclose(ficresvbl);
8677: printf("done variance-covariance of back prevalence\n");fflush(stdout);
8678: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
8679:
8680: } /* End of varbprlim */
8681:
1.126 brouard 8682: /************** Forecasting *****not tested NB*************/
1.227 brouard 8683: /* 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 8684:
1.227 brouard 8685: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8686: /* int *popage; */
8687: /* double calagedatem, agelim, kk1, kk2; */
8688: /* double *popeffectif,*popcount; */
8689: /* double ***p3mat,***tabpop,***tabpopprev; */
8690: /* /\* double ***mobaverage; *\/ */
8691: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8692:
1.227 brouard 8693: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8694: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8695: /* agelim=AGESUP; */
8696: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8697:
1.227 brouard 8698: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8699:
8700:
1.227 brouard 8701: /* strcpy(filerespop,"POP_"); */
8702: /* strcat(filerespop,fileresu); */
8703: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8704: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8705: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8706: /* } */
8707: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8708: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8709:
1.227 brouard 8710: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8711:
1.227 brouard 8712: /* /\* if (mobilav!=0) { *\/ */
8713: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8714: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8715: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8716: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8717: /* /\* } *\/ */
8718: /* /\* } *\/ */
1.126 brouard 8719:
1.227 brouard 8720: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8721: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8722:
1.227 brouard 8723: /* agelim=AGESUP; */
1.126 brouard 8724:
1.227 brouard 8725: /* hstepm=1; */
8726: /* hstepm=hstepm/stepm; */
1.218 brouard 8727:
1.227 brouard 8728: /* if (popforecast==1) { */
8729: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8730: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8731: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8732: /* } */
8733: /* popage=ivector(0,AGESUP); */
8734: /* popeffectif=vector(0,AGESUP); */
8735: /* popcount=vector(0,AGESUP); */
1.126 brouard 8736:
1.227 brouard 8737: /* i=1; */
8738: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8739:
1.227 brouard 8740: /* imx=i; */
8741: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8742: /* } */
1.218 brouard 8743:
1.227 brouard 8744: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8745: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8746: /* k=k+1; */
8747: /* fprintf(ficrespop,"\n#******"); */
8748: /* for(j=1;j<=cptcoveff;j++) { */
8749: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8750: /* } */
8751: /* fprintf(ficrespop,"******\n"); */
8752: /* fprintf(ficrespop,"# Age"); */
8753: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8754: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8755:
1.227 brouard 8756: /* for (cpt=0; cpt<=0;cpt++) { */
8757: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8758:
1.227 brouard 8759: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8760: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8761: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8762:
1.227 brouard 8763: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8764: /* oldm=oldms;savm=savms; */
8765: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8766:
1.227 brouard 8767: /* for (h=0; h<=nhstepm; h++){ */
8768: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8769: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8770: /* } */
8771: /* for(j=1; j<=nlstate+ndeath;j++) { */
8772: /* kk1=0.;kk2=0; */
8773: /* for(i=1; i<=nlstate;i++) { */
8774: /* if (mobilav==1) */
8775: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8776: /* else { */
8777: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8778: /* } */
8779: /* } */
8780: /* if (h==(int)(calagedatem+12*cpt)){ */
8781: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8782: /* /\*fprintf(ficrespop," %.3f", kk1); */
8783: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8784: /* } */
8785: /* } */
8786: /* for(i=1; i<=nlstate;i++){ */
8787: /* kk1=0.; */
8788: /* for(j=1; j<=nlstate;j++){ */
8789: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8790: /* } */
8791: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8792: /* } */
1.218 brouard 8793:
1.227 brouard 8794: /* if (h==(int)(calagedatem+12*cpt)) */
8795: /* for(j=1; j<=nlstate;j++) */
8796: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8797: /* } */
8798: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8799: /* } */
8800: /* } */
1.218 brouard 8801:
1.227 brouard 8802: /* /\******\/ */
1.218 brouard 8803:
1.227 brouard 8804: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8805: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8806: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8807: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8808: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8809:
1.227 brouard 8810: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8811: /* oldm=oldms;savm=savms; */
8812: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8813: /* for (h=0; h<=nhstepm; h++){ */
8814: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8815: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8816: /* } */
8817: /* for(j=1; j<=nlstate+ndeath;j++) { */
8818: /* kk1=0.;kk2=0; */
8819: /* for(i=1; i<=nlstate;i++) { */
8820: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8821: /* } */
8822: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8823: /* } */
8824: /* } */
8825: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8826: /* } */
8827: /* } */
8828: /* } */
8829: /* } */
1.218 brouard 8830:
1.227 brouard 8831: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8832:
1.227 brouard 8833: /* if (popforecast==1) { */
8834: /* free_ivector(popage,0,AGESUP); */
8835: /* free_vector(popeffectif,0,AGESUP); */
8836: /* free_vector(popcount,0,AGESUP); */
8837: /* } */
8838: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8839: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8840: /* fclose(ficrespop); */
8841: /* } /\* End of popforecast *\/ */
1.218 brouard 8842:
1.126 brouard 8843: int fileappend(FILE *fichier, char *optionfich)
8844: {
8845: if((fichier=fopen(optionfich,"a"))==NULL) {
8846: printf("Problem with file: %s\n", optionfich);
8847: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8848: return (0);
8849: }
8850: fflush(fichier);
8851: return (1);
8852: }
8853:
8854:
8855: /**************** function prwizard **********************/
8856: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8857: {
8858:
8859: /* Wizard to print covariance matrix template */
8860:
1.164 brouard 8861: char ca[32], cb[32];
8862: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8863: int numlinepar;
8864:
8865: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8866: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8867: for(i=1; i <=nlstate; i++){
8868: jj=0;
8869: for(j=1; j <=nlstate+ndeath; j++){
8870: if(j==i) continue;
8871: jj++;
8872: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8873: printf("%1d%1d",i,j);
8874: fprintf(ficparo,"%1d%1d",i,j);
8875: for(k=1; k<=ncovmodel;k++){
8876: /* printf(" %lf",param[i][j][k]); */
8877: /* fprintf(ficparo," %lf",param[i][j][k]); */
8878: printf(" 0.");
8879: fprintf(ficparo," 0.");
8880: }
8881: printf("\n");
8882: fprintf(ficparo,"\n");
8883: }
8884: }
8885: printf("# Scales (for hessian or gradient estimation)\n");
8886: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8887: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8888: for(i=1; i <=nlstate; i++){
8889: jj=0;
8890: for(j=1; j <=nlstate+ndeath; j++){
8891: if(j==i) continue;
8892: jj++;
8893: fprintf(ficparo,"%1d%1d",i,j);
8894: printf("%1d%1d",i,j);
8895: fflush(stdout);
8896: for(k=1; k<=ncovmodel;k++){
8897: /* printf(" %le",delti3[i][j][k]); */
8898: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8899: printf(" 0.");
8900: fprintf(ficparo," 0.");
8901: }
8902: numlinepar++;
8903: printf("\n");
8904: fprintf(ficparo,"\n");
8905: }
8906: }
8907: printf("# Covariance matrix\n");
8908: /* # 121 Var(a12)\n\ */
8909: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8910: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
8911: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
8912: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
8913: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
8914: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
8915: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8916: fflush(stdout);
8917: fprintf(ficparo,"# Covariance matrix\n");
8918: /* # 121 Var(a12)\n\ */
8919: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8920: /* # ...\n\ */
8921: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8922:
8923: for(itimes=1;itimes<=2;itimes++){
8924: jj=0;
8925: for(i=1; i <=nlstate; i++){
8926: for(j=1; j <=nlstate+ndeath; j++){
8927: if(j==i) continue;
8928: for(k=1; k<=ncovmodel;k++){
8929: jj++;
8930: ca[0]= k+'a'-1;ca[1]='\0';
8931: if(itimes==1){
8932: printf("#%1d%1d%d",i,j,k);
8933: fprintf(ficparo,"#%1d%1d%d",i,j,k);
8934: }else{
8935: printf("%1d%1d%d",i,j,k);
8936: fprintf(ficparo,"%1d%1d%d",i,j,k);
8937: /* printf(" %.5le",matcov[i][j]); */
8938: }
8939: ll=0;
8940: for(li=1;li <=nlstate; li++){
8941: for(lj=1;lj <=nlstate+ndeath; lj++){
8942: if(lj==li) continue;
8943: for(lk=1;lk<=ncovmodel;lk++){
8944: ll++;
8945: if(ll<=jj){
8946: cb[0]= lk +'a'-1;cb[1]='\0';
8947: if(ll<jj){
8948: if(itimes==1){
8949: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8950: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8951: }else{
8952: printf(" 0.");
8953: fprintf(ficparo," 0.");
8954: }
8955: }else{
8956: if(itimes==1){
8957: printf(" Var(%s%1d%1d)",ca,i,j);
8958: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
8959: }else{
8960: printf(" 0.");
8961: fprintf(ficparo," 0.");
8962: }
8963: }
8964: }
8965: } /* end lk */
8966: } /* end lj */
8967: } /* end li */
8968: printf("\n");
8969: fprintf(ficparo,"\n");
8970: numlinepar++;
8971: } /* end k*/
8972: } /*end j */
8973: } /* end i */
8974: } /* end itimes */
8975:
8976: } /* end of prwizard */
8977: /******************* Gompertz Likelihood ******************************/
8978: double gompertz(double x[])
8979: {
8980: double A,B,L=0.0,sump=0.,num=0.;
8981: int i,n=0; /* n is the size of the sample */
8982:
1.220 brouard 8983: for (i=1;i<=imx ; i++) {
1.126 brouard 8984: sump=sump+weight[i];
8985: /* sump=sump+1;*/
8986: num=num+1;
8987: }
8988:
8989:
8990: /* for (i=0; i<=imx; i++)
8991: 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]);*/
8992:
8993: for (i=1;i<=imx ; i++)
8994: {
8995: if (cens[i] == 1 && wav[i]>1)
8996: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
8997:
8998: if (cens[i] == 0 && wav[i]>1)
8999: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
9000: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
9001:
9002: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9003: if (wav[i] > 1 ) { /* ??? */
9004: L=L+A*weight[i];
9005: /* 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]);*/
9006: }
9007: }
9008:
9009: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9010:
9011: return -2*L*num/sump;
9012: }
9013:
1.136 brouard 9014: #ifdef GSL
9015: /******************* Gompertz_f Likelihood ******************************/
9016: double gompertz_f(const gsl_vector *v, void *params)
9017: {
9018: double A,B,LL=0.0,sump=0.,num=0.;
9019: double *x= (double *) v->data;
9020: int i,n=0; /* n is the size of the sample */
9021:
9022: for (i=0;i<=imx-1 ; i++) {
9023: sump=sump+weight[i];
9024: /* sump=sump+1;*/
9025: num=num+1;
9026: }
9027:
9028:
9029: /* for (i=0; i<=imx; i++)
9030: 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]);*/
9031: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9032: for (i=1;i<=imx ; i++)
9033: {
9034: if (cens[i] == 1 && wav[i]>1)
9035: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9036:
9037: if (cens[i] == 0 && wav[i]>1)
9038: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9039: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9040:
9041: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9042: if (wav[i] > 1 ) { /* ??? */
9043: LL=LL+A*weight[i];
9044: /* 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]);*/
9045: }
9046: }
9047:
9048: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9049: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9050:
9051: return -2*LL*num/sump;
9052: }
9053: #endif
9054:
1.126 brouard 9055: /******************* Printing html file ***********/
1.201 brouard 9056: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9057: int lastpass, int stepm, int weightopt, char model[],\
9058: int imx, double p[],double **matcov,double agemortsup){
9059: int i,k;
9060:
9061: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9062: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9063: for (i=1;i<=2;i++)
9064: 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 9065: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9066: fprintf(fichtm,"</ul>");
9067:
9068: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9069:
9070: 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>");
9071:
9072: for (k=agegomp;k<(agemortsup-2);k++)
9073: 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]);
9074:
9075:
9076: fflush(fichtm);
9077: }
9078:
9079: /******************* Gnuplot file **************/
1.201 brouard 9080: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9081:
9082: char dirfileres[132],optfileres[132];
1.164 brouard 9083:
1.126 brouard 9084: int ng;
9085:
9086:
9087: /*#ifdef windows */
9088: fprintf(ficgp,"cd \"%s\" \n",pathc);
9089: /*#endif */
9090:
9091:
9092: strcpy(dirfileres,optionfilefiname);
9093: strcpy(optfileres,"vpl");
1.199 brouard 9094: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9095: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9096: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9097: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9098: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9099:
9100: }
9101:
1.136 brouard 9102: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9103: {
1.126 brouard 9104:
1.136 brouard 9105: /*-------- data file ----------*/
9106: FILE *fic;
9107: char dummy[]=" ";
1.240 brouard 9108: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9109: int lstra;
1.136 brouard 9110: int linei, month, year,iout;
9111: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9112: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9113: char *stratrunc;
1.223 brouard 9114:
1.240 brouard 9115: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9116: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9117:
1.240 brouard 9118: for(v=1; v <=ncovcol;v++){
9119: DummyV[v]=0;
9120: FixedV[v]=0;
9121: }
9122: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9123: DummyV[v]=1;
9124: FixedV[v]=0;
9125: }
9126: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9127: DummyV[v]=0;
9128: FixedV[v]=1;
9129: }
9130: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9131: DummyV[v]=1;
9132: FixedV[v]=1;
9133: }
9134: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9135: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9136: 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]);
9137: }
1.126 brouard 9138:
1.136 brouard 9139: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9140: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9141: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9142: }
1.126 brouard 9143:
1.136 brouard 9144: i=1;
9145: linei=0;
9146: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9147: linei=linei+1;
9148: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9149: if(line[j] == '\t')
9150: line[j] = ' ';
9151: }
9152: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9153: ;
9154: };
9155: line[j+1]=0; /* Trims blanks at end of line */
9156: if(line[0]=='#'){
9157: fprintf(ficlog,"Comment line\n%s\n",line);
9158: printf("Comment line\n%s\n",line);
9159: continue;
9160: }
9161: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9162: strcpy(line, linetmp);
1.223 brouard 9163:
9164: /* Loops on waves */
9165: for (j=maxwav;j>=1;j--){
9166: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9167: cutv(stra, strb, line, ' ');
9168: if(strb[0]=='.') { /* Missing value */
9169: lval=-1;
9170: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9171: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9172: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9173: 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);
9174: 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);
9175: return 1;
9176: }
9177: }else{
9178: errno=0;
9179: /* what_kind_of_number(strb); */
9180: dval=strtod(strb,&endptr);
9181: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9182: /* if(strb != endptr && *endptr == '\0') */
9183: /* dval=dlval; */
9184: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9185: if( strb[0]=='\0' || (*endptr != '\0')){
9186: 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);
9187: 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);
9188: return 1;
9189: }
9190: cotqvar[j][iv][i]=dval;
9191: cotvar[j][ntv+iv][i]=dval;
9192: }
9193: strcpy(line,stra);
1.223 brouard 9194: }/* end loop ntqv */
1.225 brouard 9195:
1.223 brouard 9196: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9197: cutv(stra, strb, line, ' ');
9198: if(strb[0]=='.') { /* Missing value */
9199: lval=-1;
9200: }else{
9201: errno=0;
9202: lval=strtol(strb,&endptr,10);
9203: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9204: if( strb[0]=='\0' || (*endptr != '\0')){
9205: 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);
9206: 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);
9207: return 1;
9208: }
9209: }
9210: if(lval <-1 || lval >1){
9211: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9212: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9213: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9214: For example, for multinomial values like 1, 2 and 3,\n \
9215: build V1=0 V2=0 for the reference value (1),\n \
9216: V1=1 V2=0 for (2) \n \
1.223 brouard 9217: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9218: output of IMaCh is often meaningless.\n \
1.223 brouard 9219: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9220: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9221: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9222: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9223: For example, for multinomial values like 1, 2 and 3,\n \
9224: build V1=0 V2=0 for the reference value (1),\n \
9225: V1=1 V2=0 for (2) \n \
1.223 brouard 9226: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9227: output of IMaCh is often meaningless.\n \
1.223 brouard 9228: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 9229: return 1;
9230: }
9231: cotvar[j][iv][i]=(double)(lval);
9232: strcpy(line,stra);
1.223 brouard 9233: }/* end loop ntv */
1.225 brouard 9234:
1.223 brouard 9235: /* Statuses at wave */
1.137 brouard 9236: cutv(stra, strb, line, ' ');
1.223 brouard 9237: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9238: lval=-1;
1.136 brouard 9239: }else{
1.238 brouard 9240: errno=0;
9241: lval=strtol(strb,&endptr,10);
9242: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9243: if( strb[0]=='\0' || (*endptr != '\0')){
9244: 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);
9245: 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);
9246: return 1;
9247: }
1.136 brouard 9248: }
1.225 brouard 9249:
1.136 brouard 9250: s[j][i]=lval;
1.225 brouard 9251:
1.223 brouard 9252: /* Date of Interview */
1.136 brouard 9253: strcpy(line,stra);
9254: cutv(stra, strb,line,' ');
1.169 brouard 9255: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9256: }
1.169 brouard 9257: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9258: month=99;
9259: year=9999;
1.136 brouard 9260: }else{
1.225 brouard 9261: 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);
9262: 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);
9263: return 1;
1.136 brouard 9264: }
9265: anint[j][i]= (double) year;
9266: mint[j][i]= (double)month;
9267: strcpy(line,stra);
1.223 brouard 9268: } /* End loop on waves */
1.225 brouard 9269:
1.223 brouard 9270: /* Date of death */
1.136 brouard 9271: cutv(stra, strb,line,' ');
1.169 brouard 9272: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9273: }
1.169 brouard 9274: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9275: month=99;
9276: year=9999;
9277: }else{
1.141 brouard 9278: 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 9279: 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);
9280: return 1;
1.136 brouard 9281: }
9282: andc[i]=(double) year;
9283: moisdc[i]=(double) month;
9284: strcpy(line,stra);
9285:
1.223 brouard 9286: /* Date of birth */
1.136 brouard 9287: cutv(stra, strb,line,' ');
1.169 brouard 9288: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9289: }
1.169 brouard 9290: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9291: month=99;
9292: year=9999;
9293: }else{
1.141 brouard 9294: 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);
9295: 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 9296: return 1;
1.136 brouard 9297: }
9298: if (year==9999) {
1.141 brouard 9299: 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);
9300: 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 9301: return 1;
9302:
1.136 brouard 9303: }
9304: annais[i]=(double)(year);
9305: moisnais[i]=(double)(month);
9306: strcpy(line,stra);
1.225 brouard 9307:
1.223 brouard 9308: /* Sample weight */
1.136 brouard 9309: cutv(stra, strb,line,' ');
9310: errno=0;
9311: dval=strtod(strb,&endptr);
9312: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9313: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9314: 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 9315: fflush(ficlog);
9316: return 1;
9317: }
9318: weight[i]=dval;
9319: strcpy(line,stra);
1.225 brouard 9320:
1.223 brouard 9321: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9322: cutv(stra, strb, line, ' ');
9323: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9324: lval=-1;
1.223 brouard 9325: }else{
1.225 brouard 9326: errno=0;
9327: /* what_kind_of_number(strb); */
9328: dval=strtod(strb,&endptr);
9329: /* if(strb != endptr && *endptr == '\0') */
9330: /* dval=dlval; */
9331: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9332: if( strb[0]=='\0' || (*endptr != '\0')){
9333: 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);
9334: 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);
9335: return 1;
9336: }
9337: coqvar[iv][i]=dval;
1.226 brouard 9338: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9339: }
9340: strcpy(line,stra);
9341: }/* end loop nqv */
1.136 brouard 9342:
1.223 brouard 9343: /* Covariate values */
1.136 brouard 9344: for (j=ncovcol;j>=1;j--){
9345: cutv(stra, strb,line,' ');
1.223 brouard 9346: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9347: lval=-1;
1.136 brouard 9348: }else{
1.225 brouard 9349: errno=0;
9350: lval=strtol(strb,&endptr,10);
9351: if( strb[0]=='\0' || (*endptr != '\0')){
9352: 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);
9353: 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);
9354: return 1;
9355: }
1.136 brouard 9356: }
9357: if(lval <-1 || lval >1){
1.225 brouard 9358: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9359: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9360: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9361: For example, for multinomial values like 1, 2 and 3,\n \
9362: build V1=0 V2=0 for the reference value (1),\n \
9363: V1=1 V2=0 for (2) \n \
1.136 brouard 9364: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9365: output of IMaCh is often meaningless.\n \
1.136 brouard 9366: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9367: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9368: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9369: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9370: For example, for multinomial values like 1, 2 and 3,\n \
9371: build V1=0 V2=0 for the reference value (1),\n \
9372: V1=1 V2=0 for (2) \n \
1.136 brouard 9373: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9374: output of IMaCh is often meaningless.\n \
1.136 brouard 9375: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9376: return 1;
1.136 brouard 9377: }
9378: covar[j][i]=(double)(lval);
9379: strcpy(line,stra);
9380: }
9381: lstra=strlen(stra);
1.225 brouard 9382:
1.136 brouard 9383: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9384: stratrunc = &(stra[lstra-9]);
9385: num[i]=atol(stratrunc);
9386: }
9387: else
9388: num[i]=atol(stra);
9389: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9390: 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;}*/
9391:
9392: i=i+1;
9393: } /* End loop reading data */
1.225 brouard 9394:
1.136 brouard 9395: *imax=i-1; /* Number of individuals */
9396: fclose(fic);
1.225 brouard 9397:
1.136 brouard 9398: return (0);
1.164 brouard 9399: /* endread: */
1.225 brouard 9400: printf("Exiting readdata: ");
9401: fclose(fic);
9402: return (1);
1.223 brouard 9403: }
1.126 brouard 9404:
1.234 brouard 9405: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9406: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9407: while (*p2 == ' ')
1.234 brouard 9408: p2++;
9409: /* while ((*p1++ = *p2++) !=0) */
9410: /* ; */
9411: /* do */
9412: /* while (*p2 == ' ') */
9413: /* p2++; */
9414: /* while (*p1++ == *p2++); */
9415: *stri=p2;
1.145 brouard 9416: }
9417:
1.235 brouard 9418: int decoderesult ( char resultline[], int nres)
1.230 brouard 9419: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9420: {
1.235 brouard 9421: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9422: char resultsav[MAXLINE];
1.234 brouard 9423: int resultmodel[MAXLINE];
9424: int modelresult[MAXLINE];
1.230 brouard 9425: char stra[80], strb[80], strc[80], strd[80],stre[80];
9426:
1.234 brouard 9427: removefirstspace(&resultline);
1.233 brouard 9428: printf("decoderesult:%s\n",resultline);
1.230 brouard 9429:
9430: if (strstr(resultline,"v") !=0){
9431: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9432: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9433: return 1;
9434: }
9435: trimbb(resultsav, resultline);
9436: if (strlen(resultsav) >1){
9437: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9438: }
1.253 brouard 9439: if(j == 0){ /* Resultline but no = */
9440: TKresult[nres]=0; /* Combination for the nresult and the model */
9441: return (0);
9442: }
9443:
1.234 brouard 9444: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
9445: 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);
9446: 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);
9447: }
9448: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9449: if(nbocc(resultsav,'=') >1){
9450: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
9451: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
9452: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9453: }else
9454: cutl(strc,strd,resultsav,'=');
1.230 brouard 9455: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9456:
1.230 brouard 9457: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9458: Tvarsel[k]=atoi(strc);
9459: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9460: /* cptcovsel++; */
9461: if (nbocc(stra,'=') >0)
9462: strcpy(resultsav,stra); /* and analyzes it */
9463: }
1.235 brouard 9464: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9465: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9466: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9467: match=0;
1.236 brouard 9468: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9469: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9470: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9471: match=1;
9472: break;
9473: }
9474: }
9475: if(match == 0){
9476: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9477: }
9478: }
9479: }
1.235 brouard 9480: /* Checking for missing or useless values in comparison of current model needs */
9481: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9482: match=0;
1.235 brouard 9483: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9484: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9485: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9486: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9487: ++match;
9488: }
9489: }
9490: }
9491: if(match == 0){
9492: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9493: }else if(match > 1){
9494: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9495: }
9496: }
1.235 brouard 9497:
1.234 brouard 9498: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9499: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9500: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9501: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9502: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9503: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9504: /* 1 0 0 0 */
9505: /* 2 1 0 0 */
9506: /* 3 0 1 0 */
9507: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9508: /* 5 0 0 1 */
9509: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9510: /* 7 0 1 1 */
9511: /* 8 1 1 1 */
1.237 brouard 9512: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9513: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9514: /* V5*age V5 known which value for nres? */
9515: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9516: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9517: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9518: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9519: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9520: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9521: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9522: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9523: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9524: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9525: k4++;;
9526: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9527: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9528: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9529: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9530: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9531: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9532: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9533: k4q++;;
9534: }
9535: }
1.234 brouard 9536:
1.235 brouard 9537: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9538: return (0);
9539: }
1.235 brouard 9540:
1.230 brouard 9541: int decodemodel( char model[], int lastobs)
9542: /**< This routine decodes the model and returns:
1.224 brouard 9543: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9544: * - nagesqr = 1 if age*age in the model, otherwise 0.
9545: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9546: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9547: * - cptcovage number of covariates with age*products =2
9548: * - cptcovs number of simple covariates
9549: * - 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
9550: * which is a new column after the 9 (ncovcol) variables.
9551: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9552: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9553: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9554: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9555: */
1.136 brouard 9556: {
1.238 brouard 9557: int i, j, k, ks, v;
1.227 brouard 9558: int j1, k1, k2, k3, k4;
1.136 brouard 9559: char modelsav[80];
1.145 brouard 9560: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9561: char *strpt;
1.136 brouard 9562:
1.145 brouard 9563: /*removespace(model);*/
1.136 brouard 9564: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9565: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9566: if (strstr(model,"AGE") !=0){
1.192 brouard 9567: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9568: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9569: return 1;
9570: }
1.141 brouard 9571: if (strstr(model,"v") !=0){
9572: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9573: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9574: return 1;
9575: }
1.187 brouard 9576: strcpy(modelsav,model);
9577: if ((strpt=strstr(model,"age*age")) !=0){
9578: printf(" strpt=%s, model=%s\n",strpt, model);
9579: if(strpt != model){
1.234 brouard 9580: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9581: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9582: corresponding column of parameters.\n",model);
1.234 brouard 9583: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9584: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9585: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9586: return 1;
1.225 brouard 9587: }
1.187 brouard 9588: nagesqr=1;
9589: if (strstr(model,"+age*age") !=0)
1.234 brouard 9590: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9591: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9592: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9593: else
1.234 brouard 9594: substrchaine(modelsav, model, "age*age");
1.187 brouard 9595: }else
9596: nagesqr=0;
9597: if (strlen(modelsav) >1){
9598: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9599: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9600: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9601: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9602: * cst, age and age*age
9603: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9604: /* including age products which are counted in cptcovage.
9605: * but the covariates which are products must be treated
9606: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9607: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9608: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9609:
9610:
1.187 brouard 9611: /* Design
9612: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9613: * < ncovcol=8 >
9614: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9615: * k= 1 2 3 4 5 6 7 8
9616: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9617: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9618: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9619: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9620: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9621: * Tage[++cptcovage]=k
9622: * if products, new covar are created after ncovcol with k1
9623: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9624: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9625: * 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
9626: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9627: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9628: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9629: * < ncovcol=8 >
9630: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9631: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9632: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9633: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9634: * p Tprod[1]@2={ 6, 5}
9635: *p Tvard[1][1]@4= {7, 8, 5, 6}
9636: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9637: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9638: *How to reorganize?
9639: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9640: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9641: * {2, 1, 4, 8, 5, 6, 3, 7}
9642: * Struct []
9643: */
1.225 brouard 9644:
1.187 brouard 9645: /* This loop fills the array Tvar from the string 'model'.*/
9646: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9647: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9648: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9649: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9650: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9651: /* k=1 Tvar[1]=2 (from V2) */
9652: /* k=5 Tvar[5] */
9653: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9654: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9655: /* } */
1.198 brouard 9656: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9657: /*
9658: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9659: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9660: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9661: }
1.187 brouard 9662: cptcovage=0;
9663: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9664: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9665: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9666: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9667: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9668: /*scanf("%d",i);*/
9669: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9670: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9671: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9672: /* covar is not filled and then is empty */
9673: cptcovprod--;
9674: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9675: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9676: Typevar[k]=1; /* 1 for age product */
9677: cptcovage++; /* Sums the number of covariates which include age as a product */
9678: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9679: /*printf("stre=%s ", stre);*/
9680: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9681: cptcovprod--;
9682: cutl(stre,strb,strc,'V');
9683: Tvar[k]=atoi(stre);
9684: Typevar[k]=1; /* 1 for age product */
9685: cptcovage++;
9686: Tage[cptcovage]=k;
9687: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9688: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9689: cptcovn++;
9690: cptcovprodnoage++;k1++;
9691: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9692: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9693: because this model-covariate is a construction we invent a new column
9694: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9695: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9696: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9697: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9698: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9699: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9700: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9701: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9702: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9703: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9704: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9705: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9706: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9707: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9708: for (i=1; i<=lastobs;i++){
9709: /* Computes the new covariate which is a product of
9710: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9711: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9712: }
9713: } /* End age is not in the model */
9714: } /* End if model includes a product */
9715: else { /* no more sum */
9716: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9717: /* scanf("%d",i);*/
9718: cutl(strd,strc,strb,'V');
9719: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9720: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9721: Tvar[k]=atoi(strd);
9722: Typevar[k]=0; /* 0 for simple covariates */
9723: }
9724: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9725: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9726: scanf("%d",i);*/
1.187 brouard 9727: } /* end of loop + on total covariates */
9728: } /* end if strlen(modelsave == 0) age*age might exist */
9729: } /* end if strlen(model == 0) */
1.136 brouard 9730:
9731: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9732: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9733:
1.136 brouard 9734: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9735: printf("cptcovprod=%d ", cptcovprod);
9736: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9737: scanf("%d ",i);*/
9738:
9739:
1.230 brouard 9740: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9741: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9742: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9743: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9744: k = 1 2 3 4 5 6 7 8 9
9745: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9746: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9747: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9748: Dummy[k] 1 0 0 0 3 1 1 2 3
9749: Tmodelind[combination of covar]=k;
1.225 brouard 9750: */
9751: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9752: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9753: /* 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 9754: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9755: printf("Model=%s\n\
9756: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9757: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9758: 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);
9759: fprintf(ficlog,"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);
1.285 brouard 9763: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9764: 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 */
9765: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9766: Fixed[k]= 0;
9767: Dummy[k]= 0;
1.225 brouard 9768: ncoveff++;
1.232 brouard 9769: ncovf++;
1.234 brouard 9770: nsd++;
9771: modell[k].maintype= FTYPE;
9772: TvarsD[nsd]=Tvar[k];
9773: TvarsDind[nsd]=k;
9774: TvarF[ncovf]=Tvar[k];
9775: TvarFind[ncovf]=k;
9776: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9777: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9778: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
9779: Fixed[k]= 0;
9780: Dummy[k]= 0;
9781: ncoveff++;
9782: ncovf++;
9783: modell[k].maintype= FTYPE;
9784: TvarF[ncovf]=Tvar[k];
9785: TvarFind[ncovf]=k;
1.230 brouard 9786: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 9787: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 9788: }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 9789: Fixed[k]= 0;
9790: Dummy[k]= 1;
1.230 brouard 9791: nqfveff++;
1.234 brouard 9792: modell[k].maintype= FTYPE;
9793: modell[k].subtype= FQ;
9794: nsq++;
9795: TvarsQ[nsq]=Tvar[k];
9796: TvarsQind[nsq]=k;
1.232 brouard 9797: ncovf++;
1.234 brouard 9798: TvarF[ncovf]=Tvar[k];
9799: TvarFind[ncovf]=k;
1.231 brouard 9800: 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 9801: 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 9802: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 9803: Fixed[k]= 1;
9804: Dummy[k]= 0;
1.225 brouard 9805: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 9806: modell[k].maintype= VTYPE;
9807: modell[k].subtype= VD;
9808: nsd++;
9809: TvarsD[nsd]=Tvar[k];
9810: TvarsDind[nsd]=k;
9811: ncovv++; /* Only simple time varying variables */
9812: TvarV[ncovv]=Tvar[k];
1.242 brouard 9813: 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 9814: 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 */
9815: 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 9816: 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);
9817: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 9818: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 9819: Fixed[k]= 1;
9820: Dummy[k]= 1;
9821: nqtveff++;
9822: modell[k].maintype= VTYPE;
9823: modell[k].subtype= VQ;
9824: ncovv++; /* Only simple time varying variables */
9825: nsq++;
9826: TvarsQ[nsq]=Tvar[k];
9827: TvarsQind[nsq]=k;
9828: TvarV[ncovv]=Tvar[k];
1.242 brouard 9829: 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 9830: 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 */
9831: 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 9832: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9833: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9834: 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 9835: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9836: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9837: ncova++;
9838: TvarA[ncova]=Tvar[k];
9839: TvarAind[ncova]=k;
1.231 brouard 9840: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9841: Fixed[k]= 2;
9842: Dummy[k]= 2;
9843: modell[k].maintype= ATYPE;
9844: modell[k].subtype= APFD;
9845: /* ncoveff++; */
1.227 brouard 9846: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 9847: Fixed[k]= 2;
9848: Dummy[k]= 3;
9849: modell[k].maintype= ATYPE;
9850: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
9851: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 9852: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 9853: Fixed[k]= 3;
9854: Dummy[k]= 2;
9855: modell[k].maintype= ATYPE;
9856: modell[k].subtype= APVD; /* Product age * varying dummy */
9857: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 9858: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9859: Fixed[k]= 3;
9860: Dummy[k]= 3;
9861: modell[k].maintype= ATYPE;
9862: modell[k].subtype= APVQ; /* Product age * varying quantitative */
9863: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 9864: }
9865: }else if (Typevar[k] == 2) { /* product without age */
9866: k1=Tposprod[k];
9867: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 9868: if(Tvard[k1][2] <=ncovcol){
9869: Fixed[k]= 1;
9870: Dummy[k]= 0;
9871: modell[k].maintype= FTYPE;
9872: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
9873: ncovf++; /* Fixed variables without age */
9874: TvarF[ncovf]=Tvar[k];
9875: TvarFind[ncovf]=k;
9876: }else if(Tvard[k1][2] <=ncovcol+nqv){
9877: Fixed[k]= 0; /* or 2 ?*/
9878: Dummy[k]= 1;
9879: modell[k].maintype= FTYPE;
9880: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
9881: ncovf++; /* Varying variables without age */
9882: TvarF[ncovf]=Tvar[k];
9883: TvarFind[ncovf]=k;
9884: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9885: Fixed[k]= 1;
9886: Dummy[k]= 0;
9887: modell[k].maintype= VTYPE;
9888: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
9889: ncovv++; /* Varying variables without age */
9890: TvarV[ncovv]=Tvar[k];
9891: TvarVind[ncovv]=k;
9892: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9893: Fixed[k]= 1;
9894: Dummy[k]= 1;
9895: modell[k].maintype= VTYPE;
9896: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
9897: ncovv++; /* Varying variables without age */
9898: TvarV[ncovv]=Tvar[k];
9899: TvarVind[ncovv]=k;
9900: }
1.227 brouard 9901: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 9902: if(Tvard[k1][2] <=ncovcol){
9903: Fixed[k]= 0; /* or 2 ?*/
9904: Dummy[k]= 1;
9905: modell[k].maintype= FTYPE;
9906: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
9907: ncovf++; /* Fixed variables without age */
9908: TvarF[ncovf]=Tvar[k];
9909: TvarFind[ncovf]=k;
9910: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9911: Fixed[k]= 1;
9912: Dummy[k]= 1;
9913: modell[k].maintype= VTYPE;
9914: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
9915: ncovv++; /* Varying variables without age */
9916: TvarV[ncovv]=Tvar[k];
9917: TvarVind[ncovv]=k;
9918: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9919: Fixed[k]= 1;
9920: Dummy[k]= 1;
9921: modell[k].maintype= VTYPE;
9922: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
9923: ncovv++; /* Varying variables without age */
9924: TvarV[ncovv]=Tvar[k];
9925: TvarVind[ncovv]=k;
9926: ncovv++; /* Varying variables without age */
9927: TvarV[ncovv]=Tvar[k];
9928: TvarVind[ncovv]=k;
9929: }
1.227 brouard 9930: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 9931: if(Tvard[k1][2] <=ncovcol){
9932: Fixed[k]= 1;
9933: Dummy[k]= 1;
9934: modell[k].maintype= VTYPE;
9935: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
9936: ncovv++; /* Varying variables without age */
9937: TvarV[ncovv]=Tvar[k];
9938: TvarVind[ncovv]=k;
9939: }else if(Tvard[k1][2] <=ncovcol+nqv){
9940: Fixed[k]= 1;
9941: Dummy[k]= 1;
9942: modell[k].maintype= VTYPE;
9943: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
9944: ncovv++; /* Varying variables without age */
9945: TvarV[ncovv]=Tvar[k];
9946: TvarVind[ncovv]=k;
9947: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9948: Fixed[k]= 1;
9949: Dummy[k]= 0;
9950: modell[k].maintype= VTYPE;
9951: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
9952: ncovv++; /* Varying variables without age */
9953: TvarV[ncovv]=Tvar[k];
9954: TvarVind[ncovv]=k;
9955: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9956: Fixed[k]= 1;
9957: Dummy[k]= 1;
9958: modell[k].maintype= VTYPE;
9959: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
9960: ncovv++; /* Varying variables without age */
9961: TvarV[ncovv]=Tvar[k];
9962: TvarVind[ncovv]=k;
9963: }
1.227 brouard 9964: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9965: if(Tvard[k1][2] <=ncovcol){
9966: Fixed[k]= 1;
9967: Dummy[k]= 1;
9968: modell[k].maintype= VTYPE;
9969: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
9970: ncovv++; /* Varying variables without age */
9971: TvarV[ncovv]=Tvar[k];
9972: TvarVind[ncovv]=k;
9973: }else if(Tvard[k1][2] <=ncovcol+nqv){
9974: Fixed[k]= 1;
9975: Dummy[k]= 1;
9976: modell[k].maintype= VTYPE;
9977: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
9978: ncovv++; /* Varying variables without age */
9979: TvarV[ncovv]=Tvar[k];
9980: TvarVind[ncovv]=k;
9981: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9982: Fixed[k]= 1;
9983: Dummy[k]= 1;
9984: modell[k].maintype= VTYPE;
9985: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
9986: ncovv++; /* Varying variables without age */
9987: TvarV[ncovv]=Tvar[k];
9988: TvarVind[ncovv]=k;
9989: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9990: Fixed[k]= 1;
9991: Dummy[k]= 1;
9992: modell[k].maintype= VTYPE;
9993: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
9994: ncovv++; /* Varying variables without age */
9995: TvarV[ncovv]=Tvar[k];
9996: TvarVind[ncovv]=k;
9997: }
1.227 brouard 9998: }else{
1.240 brouard 9999: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10000: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
10001: } /*end k1*/
1.225 brouard 10002: }else{
1.226 brouard 10003: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10004: 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 10005: }
1.227 brouard 10006: 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 10007: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10008: 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]);
10009: }
10010: /* Searching for doublons in the model */
10011: for(k1=1; k1<= cptcovt;k1++){
10012: for(k2=1; k2 <k1;k2++){
1.285 brouard 10013: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10014: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10015: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10016: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10017: 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]);
10018: 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 10019: return(1);
10020: }
10021: }else if (Typevar[k1] ==2){
10022: k3=Tposprod[k1];
10023: k4=Tposprod[k2];
10024: 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])) ){
10025: 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]]);
10026: 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);
10027: return(1);
10028: }
10029: }
1.227 brouard 10030: }
10031: }
1.225 brouard 10032: }
10033: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10034: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10035: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10036: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10037: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10038: /*endread:*/
1.225 brouard 10039: printf("Exiting decodemodel: ");
10040: return (1);
1.136 brouard 10041: }
10042:
1.169 brouard 10043: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10044: {/* Check ages at death */
1.136 brouard 10045: int i, m;
1.218 brouard 10046: int firstone=0;
10047:
1.136 brouard 10048: for (i=1; i<=imx; i++) {
10049: for(m=2; (m<= maxwav); m++) {
10050: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10051: anint[m][i]=9999;
1.216 brouard 10052: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10053: s[m][i]=-1;
1.136 brouard 10054: }
10055: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10056: *nberr = *nberr + 1;
1.218 brouard 10057: if(firstone == 0){
10058: firstone=1;
1.260 brouard 10059: 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 10060: }
1.262 brouard 10061: 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 10062: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10063: }
10064: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10065: (*nberr)++;
1.259 brouard 10066: 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 10067: 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 10068: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10069: }
10070: }
10071: }
10072:
10073: for (i=1; i<=imx; i++) {
10074: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10075: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10076: 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 10077: if (s[m][i] >= nlstate+1) {
1.169 brouard 10078: if(agedc[i]>0){
10079: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10080: agev[m][i]=agedc[i];
1.214 brouard 10081: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10082: }else {
1.136 brouard 10083: if ((int)andc[i]!=9999){
10084: nbwarn++;
10085: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10086: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10087: agev[m][i]=-1;
10088: }
10089: }
1.169 brouard 10090: } /* agedc > 0 */
1.214 brouard 10091: } /* end if */
1.136 brouard 10092: else if(s[m][i] !=9){ /* Standard case, age in fractional
10093: years but with the precision of a month */
10094: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10095: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10096: agev[m][i]=1;
10097: else if(agev[m][i] < *agemin){
10098: *agemin=agev[m][i];
10099: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10100: }
10101: else if(agev[m][i] >*agemax){
10102: *agemax=agev[m][i];
1.156 brouard 10103: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10104: }
10105: /*agev[m][i]=anint[m][i]-annais[i];*/
10106: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10107: } /* en if 9*/
1.136 brouard 10108: else { /* =9 */
1.214 brouard 10109: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10110: agev[m][i]=1;
10111: s[m][i]=-1;
10112: }
10113: }
1.214 brouard 10114: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10115: agev[m][i]=1;
1.214 brouard 10116: else{
10117: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10118: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10119: agev[m][i]=0;
10120: }
10121: } /* End for lastpass */
10122: }
1.136 brouard 10123:
10124: for (i=1; i<=imx; i++) {
10125: for(m=firstpass; (m<=lastpass); m++){
10126: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10127: (*nberr)++;
1.136 brouard 10128: 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);
10129: 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);
10130: return 1;
10131: }
10132: }
10133: }
10134:
10135: /*for (i=1; i<=imx; i++){
10136: for (m=firstpass; (m<lastpass); m++){
10137: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10138: }
10139:
10140: }*/
10141:
10142:
1.139 brouard 10143: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10144: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10145:
10146: return (0);
1.164 brouard 10147: /* endread:*/
1.136 brouard 10148: printf("Exiting calandcheckages: ");
10149: return (1);
10150: }
10151:
1.172 brouard 10152: #if defined(_MSC_VER)
10153: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10154: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10155: //#include "stdafx.h"
10156: //#include <stdio.h>
10157: //#include <tchar.h>
10158: //#include <windows.h>
10159: //#include <iostream>
10160: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10161:
10162: LPFN_ISWOW64PROCESS fnIsWow64Process;
10163:
10164: BOOL IsWow64()
10165: {
10166: BOOL bIsWow64 = FALSE;
10167:
10168: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10169: // (HANDLE, PBOOL);
10170:
10171: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10172:
10173: HMODULE module = GetModuleHandle(_T("kernel32"));
10174: const char funcName[] = "IsWow64Process";
10175: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10176: GetProcAddress(module, funcName);
10177:
10178: if (NULL != fnIsWow64Process)
10179: {
10180: if (!fnIsWow64Process(GetCurrentProcess(),
10181: &bIsWow64))
10182: //throw std::exception("Unknown error");
10183: printf("Unknown error\n");
10184: }
10185: return bIsWow64 != FALSE;
10186: }
10187: #endif
1.177 brouard 10188:
1.191 brouard 10189: void syscompilerinfo(int logged)
1.167 brouard 10190: {
10191: /* #include "syscompilerinfo.h"*/
1.185 brouard 10192: /* command line Intel compiler 32bit windows, XP compatible:*/
10193: /* /GS /W3 /Gy
10194: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10195: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10196: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10197: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10198: */
10199: /* 64 bits */
1.185 brouard 10200: /*
10201: /GS /W3 /Gy
10202: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10203: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10204: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10205: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10206: /* Optimization are useless and O3 is slower than O2 */
10207: /*
10208: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10209: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10210: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10211: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10212: */
1.186 brouard 10213: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10214: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10215: /PDB:"visual studio
10216: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10217: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10218: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10219: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10220: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10221: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10222: uiAccess='false'"
10223: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10224: /NOLOGO /TLBID:1
10225: */
1.177 brouard 10226: #if defined __INTEL_COMPILER
1.178 brouard 10227: #if defined(__GNUC__)
10228: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10229: #endif
1.177 brouard 10230: #elif defined(__GNUC__)
1.179 brouard 10231: #ifndef __APPLE__
1.174 brouard 10232: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10233: #endif
1.177 brouard 10234: struct utsname sysInfo;
1.178 brouard 10235: int cross = CROSS;
10236: if (cross){
10237: printf("Cross-");
1.191 brouard 10238: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10239: }
1.174 brouard 10240: #endif
10241:
1.171 brouard 10242: #include <stdint.h>
1.178 brouard 10243:
1.191 brouard 10244: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10245: #if defined(__clang__)
1.191 brouard 10246: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10247: #endif
10248: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10249: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10250: #endif
10251: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10252: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10253: #endif
10254: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10255: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10256: #endif
10257: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10258: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10259: #endif
10260: #if defined(_MSC_VER)
1.191 brouard 10261: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10262: #endif
10263: #if defined(__PGI)
1.191 brouard 10264: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10265: #endif
10266: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10267: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10268: #endif
1.191 brouard 10269: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10270:
1.167 brouard 10271: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10272: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10273: // Windows (x64 and x86)
1.191 brouard 10274: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10275: #elif __unix__ // all unices, not all compilers
10276: // Unix
1.191 brouard 10277: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10278: #elif __linux__
10279: // linux
1.191 brouard 10280: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10281: #elif __APPLE__
1.174 brouard 10282: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10283: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10284: #endif
10285:
10286: /* __MINGW32__ */
10287: /* __CYGWIN__ */
10288: /* __MINGW64__ */
10289: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10290: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10291: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10292: /* _WIN64 // Defined for applications for Win64. */
10293: /* _M_X64 // Defined for compilations that target x64 processors. */
10294: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10295:
1.167 brouard 10296: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10297: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10298: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10299: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10300: #else
1.191 brouard 10301: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10302: #endif
10303:
1.169 brouard 10304: #if defined(__GNUC__)
10305: # if defined(__GNUC_PATCHLEVEL__)
10306: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10307: + __GNUC_MINOR__ * 100 \
10308: + __GNUC_PATCHLEVEL__)
10309: # else
10310: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10311: + __GNUC_MINOR__ * 100)
10312: # endif
1.174 brouard 10313: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10314: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10315:
10316: if (uname(&sysInfo) != -1) {
10317: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10318: 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 10319: }
10320: else
10321: perror("uname() error");
1.179 brouard 10322: //#ifndef __INTEL_COMPILER
10323: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10324: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10325: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10326: #endif
1.169 brouard 10327: #endif
1.172 brouard 10328:
1.286 brouard 10329: // void main ()
1.172 brouard 10330: // {
1.169 brouard 10331: #if defined(_MSC_VER)
1.174 brouard 10332: if (IsWow64()){
1.191 brouard 10333: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10334: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10335: }
10336: else{
1.191 brouard 10337: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10338: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10339: }
1.172 brouard 10340: // printf("\nPress Enter to continue...");
10341: // getchar();
10342: // }
10343:
1.169 brouard 10344: #endif
10345:
1.167 brouard 10346:
1.219 brouard 10347: }
1.136 brouard 10348:
1.219 brouard 10349: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 10350: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.235 brouard 10351: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10352: /* double ftolpl = 1.e-10; */
1.180 brouard 10353: double age, agebase, agelim;
1.203 brouard 10354: double tot;
1.180 brouard 10355:
1.202 brouard 10356: strcpy(filerespl,"PL_");
10357: strcat(filerespl,fileresu);
10358: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 10359: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10360: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 10361: }
1.288 brouard 10362: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
10363: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10364: pstamp(ficrespl);
1.288 brouard 10365: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10366: fprintf(ficrespl,"#Age ");
10367: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10368: fprintf(ficrespl,"\n");
1.180 brouard 10369:
1.219 brouard 10370: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10371:
1.219 brouard 10372: agebase=ageminpar;
10373: agelim=agemaxpar;
1.180 brouard 10374:
1.227 brouard 10375: /* i1=pow(2,ncoveff); */
1.234 brouard 10376: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10377: if (cptcovn < 1){i1=1;}
1.180 brouard 10378:
1.238 brouard 10379: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10380: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10381: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10382: continue;
1.235 brouard 10383:
1.238 brouard 10384: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10385: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10386: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10387: /* k=k+1; */
10388: /* to clean */
10389: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10390: fprintf(ficrespl,"#******");
10391: printf("#******");
10392: fprintf(ficlog,"#******");
10393: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10394: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10395: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10396: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10397: }
10398: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10399: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10400: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10401: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10402: }
10403: fprintf(ficrespl,"******\n");
10404: printf("******\n");
10405: fprintf(ficlog,"******\n");
10406: if(invalidvarcomb[k]){
10407: printf("\nCombination (%d) ignored because no case \n",k);
10408: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10409: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10410: continue;
10411: }
1.219 brouard 10412:
1.238 brouard 10413: fprintf(ficrespl,"#Age ");
10414: for(j=1;j<=cptcoveff;j++) {
10415: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10416: }
10417: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10418: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10419:
1.238 brouard 10420: for (age=agebase; age<=agelim; age++){
10421: /* for (age=agebase; age<=agebase; age++){ */
10422: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10423: fprintf(ficrespl,"%.0f ",age );
10424: for(j=1;j<=cptcoveff;j++)
10425: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10426: tot=0.;
10427: for(i=1; i<=nlstate;i++){
10428: tot += prlim[i][i];
10429: fprintf(ficrespl," %.5f", prlim[i][i]);
10430: }
10431: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10432: } /* Age */
10433: /* was end of cptcod */
10434: } /* cptcov */
10435: } /* nres */
1.219 brouard 10436: return 0;
1.180 brouard 10437: }
10438:
1.218 brouard 10439: 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 10440: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 10441:
10442: /* Computes the back prevalence limit for any combination of covariate values
10443: * at any age between ageminpar and agemaxpar
10444: */
1.235 brouard 10445: int i, j, k, i1, nres=0 ;
1.217 brouard 10446: /* double ftolpl = 1.e-10; */
10447: double age, agebase, agelim;
10448: double tot;
1.218 brouard 10449: /* double ***mobaverage; */
10450: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10451:
10452: strcpy(fileresplb,"PLB_");
10453: strcat(fileresplb,fileresu);
10454: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 10455: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
10456: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 10457: }
1.288 brouard 10458: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
10459: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 10460: pstamp(ficresplb);
1.288 brouard 10461: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 10462: fprintf(ficresplb,"#Age ");
10463: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10464: fprintf(ficresplb,"\n");
10465:
1.218 brouard 10466:
10467: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10468:
10469: agebase=ageminpar;
10470: agelim=agemaxpar;
10471:
10472:
1.227 brouard 10473: i1=pow(2,cptcoveff);
1.218 brouard 10474: if (cptcovn < 1){i1=1;}
1.227 brouard 10475:
1.238 brouard 10476: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10477: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10478: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10479: continue;
10480: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10481: fprintf(ficresplb,"#******");
10482: printf("#******");
10483: fprintf(ficlog,"#******");
10484: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10485: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10486: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10487: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10488: }
10489: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10490: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10491: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10492: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10493: }
10494: fprintf(ficresplb,"******\n");
10495: printf("******\n");
10496: fprintf(ficlog,"******\n");
10497: if(invalidvarcomb[k]){
10498: printf("\nCombination (%d) ignored because no cases \n",k);
10499: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10500: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10501: continue;
10502: }
1.218 brouard 10503:
1.238 brouard 10504: fprintf(ficresplb,"#Age ");
10505: for(j=1;j<=cptcoveff;j++) {
10506: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10507: }
10508: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10509: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10510:
10511:
1.238 brouard 10512: for (age=agebase; age<=agelim; age++){
10513: /* for (age=agebase; age<=agebase; age++){ */
10514: if(mobilavproj > 0){
10515: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10516: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10517: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10518: }else if (mobilavproj == 0){
10519: 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);
10520: 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);
10521: exit(1);
10522: }else{
10523: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10524: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10525: /* printf("TOTOT\n"); */
10526: /* exit(1); */
1.238 brouard 10527: }
10528: fprintf(ficresplb,"%.0f ",age );
10529: for(j=1;j<=cptcoveff;j++)
10530: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10531: tot=0.;
10532: for(i=1; i<=nlstate;i++){
10533: tot += bprlim[i][i];
10534: fprintf(ficresplb," %.5f", bprlim[i][i]);
10535: }
10536: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10537: } /* Age */
10538: /* was end of cptcod */
1.255 brouard 10539: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10540: } /* end of any combination */
10541: } /* end of nres */
1.218 brouard 10542: /* hBijx(p, bage, fage); */
10543: /* fclose(ficrespijb); */
10544:
10545: return 0;
1.217 brouard 10546: }
1.218 brouard 10547:
1.180 brouard 10548: int hPijx(double *p, int bage, int fage){
10549: /*------------- h Pij x at various ages ------------*/
10550:
10551: int stepsize;
10552: int agelim;
10553: int hstepm;
10554: int nhstepm;
1.235 brouard 10555: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10556:
10557: double agedeb;
10558: double ***p3mat;
10559:
1.201 brouard 10560: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10561: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10562: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10563: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10564: }
10565: printf("Computing pij: result on file '%s' \n", filerespij);
10566: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10567:
10568: stepsize=(int) (stepm+YEARM-1)/YEARM;
10569: /*if (stepm<=24) stepsize=2;*/
10570:
10571: agelim=AGESUP;
10572: hstepm=stepsize*YEARM; /* Every year of age */
10573: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10574:
1.180 brouard 10575: /* hstepm=1; aff par mois*/
10576: pstamp(ficrespij);
10577: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10578: i1= pow(2,cptcoveff);
1.218 brouard 10579: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10580: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10581: /* k=k+1; */
1.235 brouard 10582: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10583: for(k=1; k<=i1;k++){
1.253 brouard 10584: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10585: continue;
1.183 brouard 10586: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10587: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10588: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10589: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10590: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10591: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10592: }
1.183 brouard 10593: fprintf(ficrespij,"******\n");
10594:
10595: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10596: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10597: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10598:
10599: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10600:
1.183 brouard 10601: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10602: oldm=oldms;savm=savms;
1.235 brouard 10603: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10604: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10605: for(i=1; i<=nlstate;i++)
10606: for(j=1; j<=nlstate+ndeath;j++)
10607: fprintf(ficrespij," %1d-%1d",i,j);
10608: fprintf(ficrespij,"\n");
10609: for (h=0; h<=nhstepm; h++){
10610: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10611: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10612: for(i=1; i<=nlstate;i++)
10613: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10614: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10615: fprintf(ficrespij,"\n");
10616: }
1.183 brouard 10617: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10618: fprintf(ficrespij,"\n");
10619: }
1.180 brouard 10620: /*}*/
10621: }
1.218 brouard 10622: return 0;
1.180 brouard 10623: }
1.218 brouard 10624:
10625: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10626: /*------------- h Bij x at various ages ------------*/
10627:
10628: int stepsize;
1.218 brouard 10629: /* int agelim; */
10630: int ageminl;
1.217 brouard 10631: int hstepm;
10632: int nhstepm;
1.238 brouard 10633: int h, i, i1, j, k, nres;
1.218 brouard 10634:
1.217 brouard 10635: double agedeb;
10636: double ***p3mat;
1.218 brouard 10637:
10638: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10639: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10640: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10641: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10642: }
10643: printf("Computing pij back: result on file '%s' \n", filerespijb);
10644: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10645:
10646: stepsize=(int) (stepm+YEARM-1)/YEARM;
10647: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10648:
1.218 brouard 10649: /* agelim=AGESUP; */
1.289 ! brouard 10650: ageminl=AGEINF; /* was 30 */
1.218 brouard 10651: hstepm=stepsize*YEARM; /* Every year of age */
10652: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10653:
10654: /* hstepm=1; aff par mois*/
10655: pstamp(ficrespijb);
1.255 brouard 10656: 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 10657: i1= pow(2,cptcoveff);
1.218 brouard 10658: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10659: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10660: /* k=k+1; */
1.238 brouard 10661: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10662: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10663: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10664: continue;
10665: fprintf(ficrespijb,"\n#****** ");
10666: for(j=1;j<=cptcoveff;j++)
10667: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10668: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10669: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10670: }
10671: fprintf(ficrespijb,"******\n");
1.264 brouard 10672: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10673: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10674: continue;
10675: }
10676:
10677: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10678: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10679: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
10680: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10681: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
10682:
10683: /* nhstepm=nhstepm*YEARM; aff par mois*/
10684:
1.266 brouard 10685: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10686: /* and memory limitations if stepm is small */
10687:
1.238 brouard 10688: /* oldm=oldms;savm=savms; */
10689: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10690: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10691: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10692: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10693: for(i=1; i<=nlstate;i++)
10694: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10695: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10696: fprintf(ficrespijb,"\n");
1.238 brouard 10697: for (h=0; h<=nhstepm; h++){
10698: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10699: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10700: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10701: for(i=1; i<=nlstate;i++)
10702: for(j=1; j<=nlstate+ndeath;j++)
10703: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10704: fprintf(ficrespijb,"\n");
10705: }
10706: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10707: fprintf(ficrespijb,"\n");
10708: } /* end age deb */
10709: } /* end combination */
10710: } /* end nres */
1.218 brouard 10711: return 0;
10712: } /* hBijx */
1.217 brouard 10713:
1.180 brouard 10714:
1.136 brouard 10715: /***********************************************/
10716: /**************** Main Program *****************/
10717: /***********************************************/
10718:
10719: int main(int argc, char *argv[])
10720: {
10721: #ifdef GSL
10722: const gsl_multimin_fminimizer_type *T;
10723: size_t iteri = 0, it;
10724: int rval = GSL_CONTINUE;
10725: int status = GSL_SUCCESS;
10726: double ssval;
10727: #endif
10728: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.164 brouard 10729: int i,j, k, n=MAXN,iter=0,m,size=100, cptcod;
1.209 brouard 10730: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10731: int jj, ll, li, lj, lk;
1.136 brouard 10732: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10733: int num_filled;
1.136 brouard 10734: int itimes;
10735: int NDIM=2;
10736: int vpopbased=0;
1.235 brouard 10737: int nres=0;
1.258 brouard 10738: int endishere=0;
1.277 brouard 10739: int noffset=0;
1.274 brouard 10740: int ncurrv=0; /* Temporary variable */
10741:
1.164 brouard 10742: char ca[32], cb[32];
1.136 brouard 10743: /* FILE *fichtm; *//* Html File */
10744: /* FILE *ficgp;*/ /*Gnuplot File */
10745: struct stat info;
1.191 brouard 10746: double agedeb=0.;
1.194 brouard 10747:
10748: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10749: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10750:
1.165 brouard 10751: double fret;
1.191 brouard 10752: double dum=0.; /* Dummy variable */
1.136 brouard 10753: double ***p3mat;
1.218 brouard 10754: /* double ***mobaverage; */
1.164 brouard 10755:
10756: char line[MAXLINE];
1.197 brouard 10757: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10758:
1.234 brouard 10759: char modeltemp[MAXLINE];
1.230 brouard 10760: char resultline[MAXLINE];
10761:
1.136 brouard 10762: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10763: char *tok, *val; /* pathtot */
1.136 brouard 10764: int firstobs=1, lastobs=10;
1.195 brouard 10765: int c, h , cpt, c2;
1.191 brouard 10766: int jl=0;
10767: int i1, j1, jk, stepsize=0;
1.194 brouard 10768: int count=0;
10769:
1.164 brouard 10770: int *tab;
1.136 brouard 10771: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.217 brouard 10772: int backcast=0;
1.136 brouard 10773: int mobilav=0,popforecast=0;
1.191 brouard 10774: int hstepm=0, nhstepm=0;
1.136 brouard 10775: int agemortsup;
10776: float sumlpop=0.;
10777: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
10778: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
10779:
1.191 brouard 10780: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 10781: double ftolpl=FTOL;
10782: double **prlim;
1.217 brouard 10783: double **bprlim;
1.136 brouard 10784: double ***param; /* Matrix of parameters */
1.251 brouard 10785: double ***paramstart; /* Matrix of starting parameter values */
10786: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 10787: double **matcov; /* Matrix of covariance */
1.203 brouard 10788: double **hess; /* Hessian matrix */
1.136 brouard 10789: double ***delti3; /* Scale */
10790: double *delti; /* Scale */
10791: double ***eij, ***vareij;
10792: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 10793:
1.136 brouard 10794: double *epj, vepp;
1.164 brouard 10795:
1.273 brouard 10796: double dateprev1, dateprev2;
10797: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0;
10798: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0;
1.217 brouard 10799:
1.136 brouard 10800: double **ximort;
1.145 brouard 10801: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 10802: int *dcwave;
10803:
1.164 brouard 10804: char z[1]="c";
1.136 brouard 10805:
10806: /*char *strt;*/
10807: char strtend[80];
1.126 brouard 10808:
1.164 brouard 10809:
1.126 brouard 10810: /* setlocale (LC_ALL, ""); */
10811: /* bindtextdomain (PACKAGE, LOCALEDIR); */
10812: /* textdomain (PACKAGE); */
10813: /* setlocale (LC_CTYPE, ""); */
10814: /* setlocale (LC_MESSAGES, ""); */
10815:
10816: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 10817: rstart_time = time(NULL);
10818: /* (void) gettimeofday(&start_time,&tzp);*/
10819: start_time = *localtime(&rstart_time);
1.126 brouard 10820: curr_time=start_time;
1.157 brouard 10821: /*tml = *localtime(&start_time.tm_sec);*/
10822: /* strcpy(strstart,asctime(&tml)); */
10823: strcpy(strstart,asctime(&start_time));
1.126 brouard 10824:
10825: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 10826: /* tp.tm_sec = tp.tm_sec +86400; */
10827: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 10828: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
10829: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
10830: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 10831: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 10832: /* strt=asctime(&tmg); */
10833: /* printf("Time(after) =%s",strstart); */
10834: /* (void) time (&time_value);
10835: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
10836: * tm = *localtime(&time_value);
10837: * strstart=asctime(&tm);
10838: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
10839: */
10840:
10841: nberr=0; /* Number of errors and warnings */
10842: nbwarn=0;
1.184 brouard 10843: #ifdef WIN32
10844: _getcwd(pathcd, size);
10845: #else
1.126 brouard 10846: getcwd(pathcd, size);
1.184 brouard 10847: #endif
1.191 brouard 10848: syscompilerinfo(0);
1.196 brouard 10849: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 10850: if(argc <=1){
10851: printf("\nEnter the parameter file name: ");
1.205 brouard 10852: if(!fgets(pathr,FILENAMELENGTH,stdin)){
10853: printf("ERROR Empty parameter file name\n");
10854: goto end;
10855: }
1.126 brouard 10856: i=strlen(pathr);
10857: if(pathr[i-1]=='\n')
10858: pathr[i-1]='\0';
1.156 brouard 10859: i=strlen(pathr);
1.205 brouard 10860: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 10861: pathr[i-1]='\0';
1.205 brouard 10862: }
10863: i=strlen(pathr);
10864: if( i==0 ){
10865: printf("ERROR Empty parameter file name\n");
10866: goto end;
10867: }
10868: for (tok = pathr; tok != NULL; ){
1.126 brouard 10869: printf("Pathr |%s|\n",pathr);
10870: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
10871: printf("val= |%s| pathr=%s\n",val,pathr);
10872: strcpy (pathtot, val);
10873: if(pathr[0] == '\0') break; /* Dirty */
10874: }
10875: }
1.281 brouard 10876: else if (argc<=2){
10877: strcpy(pathtot,argv[1]);
10878: }
1.126 brouard 10879: else{
10880: strcpy(pathtot,argv[1]);
1.281 brouard 10881: strcpy(z,argv[2]);
10882: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 10883: }
10884: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
10885: /*cygwin_split_path(pathtot,path,optionfile);
10886: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
10887: /* cutv(path,optionfile,pathtot,'\\');*/
10888:
10889: /* Split argv[0], imach program to get pathimach */
10890: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
10891: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10892: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10893: /* strcpy(pathimach,argv[0]); */
10894: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
10895: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
10896: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 10897: #ifdef WIN32
10898: _chdir(path); /* Can be a relative path */
10899: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
10900: #else
1.126 brouard 10901: chdir(path); /* Can be a relative path */
1.184 brouard 10902: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
10903: #endif
10904: printf("Current directory %s!\n",pathcd);
1.126 brouard 10905: strcpy(command,"mkdir ");
10906: strcat(command,optionfilefiname);
10907: if((outcmd=system(command)) != 0){
1.169 brouard 10908: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 10909: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
10910: /* fclose(ficlog); */
10911: /* exit(1); */
10912: }
10913: /* if((imk=mkdir(optionfilefiname))<0){ */
10914: /* perror("mkdir"); */
10915: /* } */
10916:
10917: /*-------- arguments in the command line --------*/
10918:
1.186 brouard 10919: /* Main Log file */
1.126 brouard 10920: strcat(filelog, optionfilefiname);
10921: strcat(filelog,".log"); /* */
10922: if((ficlog=fopen(filelog,"w"))==NULL) {
10923: printf("Problem with logfile %s\n",filelog);
10924: goto end;
10925: }
10926: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 10927: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 10928: fprintf(ficlog,"\nEnter the parameter file name: \n");
10929: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
10930: path=%s \n\
10931: optionfile=%s\n\
10932: optionfilext=%s\n\
1.156 brouard 10933: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 10934:
1.197 brouard 10935: syscompilerinfo(1);
1.167 brouard 10936:
1.126 brouard 10937: printf("Local time (at start):%s",strstart);
10938: fprintf(ficlog,"Local time (at start): %s",strstart);
10939: fflush(ficlog);
10940: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 10941: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 10942:
10943: /* */
10944: strcpy(fileres,"r");
10945: strcat(fileres, optionfilefiname);
1.201 brouard 10946: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 10947: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 10948: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 10949:
1.186 brouard 10950: /* Main ---------arguments file --------*/
1.126 brouard 10951:
10952: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 10953: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
10954: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 10955: fflush(ficlog);
1.149 brouard 10956: /* goto end; */
10957: exit(70);
1.126 brouard 10958: }
10959:
10960: strcpy(filereso,"o");
1.201 brouard 10961: strcat(filereso,fileresu);
1.126 brouard 10962: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
10963: printf("Problem with Output resultfile: %s\n", filereso);
10964: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
10965: fflush(ficlog);
10966: goto end;
10967: }
1.278 brouard 10968: /*-------- Rewriting parameter file ----------*/
10969: strcpy(rfileres,"r"); /* "Rparameterfile */
10970: strcat(rfileres,optionfilefiname); /* Parameter file first name */
10971: strcat(rfileres,"."); /* */
10972: strcat(rfileres,optionfilext); /* Other files have txt extension */
10973: if((ficres =fopen(rfileres,"w"))==NULL) {
10974: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
10975: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
10976: fflush(ficlog);
10977: goto end;
10978: }
10979: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 10980:
1.278 brouard 10981:
1.126 brouard 10982: /* Reads comments: lines beginning with '#' */
10983: numlinepar=0;
1.277 brouard 10984: /* Is it a BOM UTF-8 Windows file? */
10985: /* First parameter line */
1.197 brouard 10986: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 10987: noffset=0;
10988: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10989: {
10990: noffset=noffset+3;
10991: printf("# File is an UTF8 Bom.\n"); // 0xBF
10992: }
10993: else if( line[0] == (char)0xFE && line[1] == (char)0xFF)
10994: {
10995: noffset=noffset+2;
10996: printf("# File is an UTF16BE BOM file\n");
10997: }
10998: else if( line[0] == 0 && line[1] == 0)
10999: {
11000: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
11001: noffset=noffset+4;
11002: printf("# File is an UTF16BE BOM file\n");
11003: }
11004: } else{
11005: ;/*printf(" Not a BOM file\n");*/
11006: }
11007:
1.197 brouard 11008: /* If line starts with a # it is a comment */
1.277 brouard 11009: if (line[noffset] == '#') {
1.197 brouard 11010: numlinepar++;
11011: fputs(line,stdout);
11012: fputs(line,ficparo);
1.278 brouard 11013: fputs(line,ficres);
1.197 brouard 11014: fputs(line,ficlog);
11015: continue;
11016: }else
11017: break;
11018: }
11019: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11020: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11021: if (num_filled != 5) {
11022: printf("Should be 5 parameters\n");
1.283 brouard 11023: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11024: }
1.126 brouard 11025: numlinepar++;
1.197 brouard 11026: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11027: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11028: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11029: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11030: }
11031: /* Second parameter line */
11032: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11033: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11034: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11035: if (line[0] == '#') {
11036: numlinepar++;
1.283 brouard 11037: printf("%s",line);
11038: fprintf(ficres,"%s",line);
11039: fprintf(ficparo,"%s",line);
11040: fprintf(ficlog,"%s",line);
1.197 brouard 11041: continue;
11042: }else
11043: break;
11044: }
1.223 brouard 11045: 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", \
11046: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11047: if (num_filled != 11) {
11048: 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 11049: printf("but line=%s\n",line);
1.283 brouard 11050: 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");
11051: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11052: }
1.286 brouard 11053: if( lastpass > maxwav){
11054: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11055: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11056: fflush(ficlog);
11057: goto end;
11058: }
11059: 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 11060: 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 11061: 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 11062: 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 11063: }
1.203 brouard 11064: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11065: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11066: /* Third parameter line */
11067: while(fgets(line, MAXLINE, ficpar)) {
11068: /* If line starts with a # it is a comment */
11069: if (line[0] == '#') {
11070: numlinepar++;
1.283 brouard 11071: printf("%s",line);
11072: fprintf(ficres,"%s",line);
11073: fprintf(ficparo,"%s",line);
11074: fprintf(ficlog,"%s",line);
1.197 brouard 11075: continue;
11076: }else
11077: break;
11078: }
1.201 brouard 11079: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11080: if (num_filled != 1){
11081: printf("ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
11082: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
1.197 brouard 11083: model[0]='\0';
11084: goto end;
11085: }
11086: else{
11087: if (model[0]=='+'){
11088: for(i=1; i<=strlen(model);i++)
11089: modeltemp[i-1]=model[i];
1.201 brouard 11090: strcpy(model,modeltemp);
1.197 brouard 11091: }
11092: }
1.199 brouard 11093: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11094: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11095: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11096: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11097: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11098: }
11099: /* 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); */
11100: /* numlinepar=numlinepar+3; /\* In general *\/ */
11101: /* 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 11102: /* 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); */
11103: /* 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 11104: fflush(ficlog);
1.190 brouard 11105: /* if(model[0]=='#'|| model[0]== '\0'){ */
11106: if(model[0]=='#'){
1.279 brouard 11107: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11108: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11109: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11110: if(mle != -1){
1.279 brouard 11111: 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 11112: exit(1);
11113: }
11114: }
1.126 brouard 11115: while((c=getc(ficpar))=='#' && c!= EOF){
11116: ungetc(c,ficpar);
11117: fgets(line, MAXLINE, ficpar);
11118: numlinepar++;
1.195 brouard 11119: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11120: z[0]=line[1];
11121: }
11122: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11123: fputs(line, stdout);
11124: //puts(line);
1.126 brouard 11125: fputs(line,ficparo);
11126: fputs(line,ficlog);
11127: }
11128: ungetc(c,ficpar);
11129:
11130:
1.145 brouard 11131: covar=matrix(0,NCOVMAX,1,n); /**< used in readdata */
1.268 brouard 11132: if(nqv>=1)coqvar=matrix(1,nqv,1,n); /**< Fixed quantitative covariate */
11133: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,1,n); /**< Time varying quantitative covariate */
11134: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,1,n); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11135: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11136: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11137: v1+v2*age+v2*v3 makes cptcovn = 3
11138: */
11139: if (strlen(model)>1)
1.187 brouard 11140: 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 11141: else
1.187 brouard 11142: ncovmodel=2; /* Constant and age */
1.133 brouard 11143: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11144: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11145: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11146: 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);
11147: 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);
11148: fflush(stdout);
11149: fclose (ficlog);
11150: goto end;
11151: }
1.126 brouard 11152: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11153: delti=delti3[1][1];
11154: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11155: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11156: /* We could also provide initial parameters values giving by simple logistic regression
11157: * only one way, that is without matrix product. We will have nlstate maximizations */
11158: /* for(i=1;i<nlstate;i++){ */
11159: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11160: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11161: /* } */
1.126 brouard 11162: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11163: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11164: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11165: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11166: fclose (ficparo);
11167: fclose (ficlog);
11168: goto end;
11169: exit(0);
1.220 brouard 11170: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11171: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11172: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11173: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11174: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11175: matcov=matrix(1,npar,1,npar);
1.203 brouard 11176: hess=matrix(1,npar,1,npar);
1.220 brouard 11177: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11178: /* Read guessed parameters */
1.126 brouard 11179: /* Reads comments: lines beginning with '#' */
11180: while((c=getc(ficpar))=='#' && c!= EOF){
11181: ungetc(c,ficpar);
11182: fgets(line, MAXLINE, ficpar);
11183: numlinepar++;
1.141 brouard 11184: fputs(line,stdout);
1.126 brouard 11185: fputs(line,ficparo);
11186: fputs(line,ficlog);
11187: }
11188: ungetc(c,ficpar);
11189:
11190: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11191: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11192: for(i=1; i <=nlstate; i++){
1.234 brouard 11193: j=0;
1.126 brouard 11194: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11195: if(jj==i) continue;
11196: j++;
11197: fscanf(ficpar,"%1d%1d",&i1,&j1);
11198: if ((i1 != i) || (j1 != jj)){
11199: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11200: It might be a problem of design; if ncovcol and the model are correct\n \
11201: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11202: exit(1);
11203: }
11204: fprintf(ficparo,"%1d%1d",i1,j1);
11205: if(mle==1)
11206: printf("%1d%1d",i,jj);
11207: fprintf(ficlog,"%1d%1d",i,jj);
11208: for(k=1; k<=ncovmodel;k++){
11209: fscanf(ficpar," %lf",¶m[i][j][k]);
11210: if(mle==1){
11211: printf(" %lf",param[i][j][k]);
11212: fprintf(ficlog," %lf",param[i][j][k]);
11213: }
11214: else
11215: fprintf(ficlog," %lf",param[i][j][k]);
11216: fprintf(ficparo," %lf",param[i][j][k]);
11217: }
11218: fscanf(ficpar,"\n");
11219: numlinepar++;
11220: if(mle==1)
11221: printf("\n");
11222: fprintf(ficlog,"\n");
11223: fprintf(ficparo,"\n");
1.126 brouard 11224: }
11225: }
11226: fflush(ficlog);
1.234 brouard 11227:
1.251 brouard 11228: /* Reads parameters values */
1.126 brouard 11229: p=param[1][1];
1.251 brouard 11230: pstart=paramstart[1][1];
1.126 brouard 11231:
11232: /* Reads comments: lines beginning with '#' */
11233: while((c=getc(ficpar))=='#' && c!= EOF){
11234: ungetc(c,ficpar);
11235: fgets(line, MAXLINE, ficpar);
11236: numlinepar++;
1.141 brouard 11237: fputs(line,stdout);
1.126 brouard 11238: fputs(line,ficparo);
11239: fputs(line,ficlog);
11240: }
11241: ungetc(c,ficpar);
11242:
11243: for(i=1; i <=nlstate; i++){
11244: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11245: fscanf(ficpar,"%1d%1d",&i1,&j1);
11246: if ( (i1-i) * (j1-j) != 0){
11247: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11248: exit(1);
11249: }
11250: printf("%1d%1d",i,j);
11251: fprintf(ficparo,"%1d%1d",i1,j1);
11252: fprintf(ficlog,"%1d%1d",i1,j1);
11253: for(k=1; k<=ncovmodel;k++){
11254: fscanf(ficpar,"%le",&delti3[i][j][k]);
11255: printf(" %le",delti3[i][j][k]);
11256: fprintf(ficparo," %le",delti3[i][j][k]);
11257: fprintf(ficlog," %le",delti3[i][j][k]);
11258: }
11259: fscanf(ficpar,"\n");
11260: numlinepar++;
11261: printf("\n");
11262: fprintf(ficparo,"\n");
11263: fprintf(ficlog,"\n");
1.126 brouard 11264: }
11265: }
11266: fflush(ficlog);
1.234 brouard 11267:
1.145 brouard 11268: /* Reads covariance matrix */
1.126 brouard 11269: delti=delti3[1][1];
1.220 brouard 11270:
11271:
1.126 brouard 11272: /* 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 11273:
1.126 brouard 11274: /* Reads comments: lines beginning with '#' */
11275: while((c=getc(ficpar))=='#' && c!= EOF){
11276: ungetc(c,ficpar);
11277: fgets(line, MAXLINE, ficpar);
11278: numlinepar++;
1.141 brouard 11279: fputs(line,stdout);
1.126 brouard 11280: fputs(line,ficparo);
11281: fputs(line,ficlog);
11282: }
11283: ungetc(c,ficpar);
1.220 brouard 11284:
1.126 brouard 11285: matcov=matrix(1,npar,1,npar);
1.203 brouard 11286: hess=matrix(1,npar,1,npar);
1.131 brouard 11287: for(i=1; i <=npar; i++)
11288: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11289:
1.194 brouard 11290: /* Scans npar lines */
1.126 brouard 11291: for(i=1; i <=npar; i++){
1.226 brouard 11292: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11293: if(count != 3){
1.226 brouard 11294: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11295: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11296: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11297: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11298: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11299: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11300: exit(1);
1.220 brouard 11301: }else{
1.226 brouard 11302: if(mle==1)
11303: printf("%1d%1d%d",i1,j1,jk);
11304: }
11305: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11306: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11307: for(j=1; j <=i; j++){
1.226 brouard 11308: fscanf(ficpar," %le",&matcov[i][j]);
11309: if(mle==1){
11310: printf(" %.5le",matcov[i][j]);
11311: }
11312: fprintf(ficlog," %.5le",matcov[i][j]);
11313: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11314: }
11315: fscanf(ficpar,"\n");
11316: numlinepar++;
11317: if(mle==1)
1.220 brouard 11318: printf("\n");
1.126 brouard 11319: fprintf(ficlog,"\n");
11320: fprintf(ficparo,"\n");
11321: }
1.194 brouard 11322: /* End of read covariance matrix npar lines */
1.126 brouard 11323: for(i=1; i <=npar; i++)
11324: for(j=i+1;j<=npar;j++)
1.226 brouard 11325: matcov[i][j]=matcov[j][i];
1.126 brouard 11326:
11327: if(mle==1)
11328: printf("\n");
11329: fprintf(ficlog,"\n");
11330:
11331: fflush(ficlog);
11332:
11333: } /* End of mle != -3 */
1.218 brouard 11334:
1.186 brouard 11335: /* Main data
11336: */
1.126 brouard 11337: n= lastobs;
11338: num=lvector(1,n);
11339: moisnais=vector(1,n);
11340: annais=vector(1,n);
11341: moisdc=vector(1,n);
11342: andc=vector(1,n);
1.220 brouard 11343: weight=vector(1,n);
1.126 brouard 11344: agedc=vector(1,n);
11345: cod=ivector(1,n);
1.220 brouard 11346: for(i=1;i<=n;i++){
1.234 brouard 11347: num[i]=0;
11348: moisnais[i]=0;
11349: annais[i]=0;
11350: moisdc[i]=0;
11351: andc[i]=0;
11352: agedc[i]=0;
11353: cod[i]=0;
11354: weight[i]=1.0; /* Equal weights, 1 by default */
11355: }
1.126 brouard 11356: mint=matrix(1,maxwav,1,n);
11357: anint=matrix(1,maxwav,1,n);
1.131 brouard 11358: s=imatrix(1,maxwav+1,1,n); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11359: tab=ivector(1,NCOVMAX);
1.144 brouard 11360: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11361: 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 11362:
1.136 brouard 11363: /* Reads data from file datafile */
11364: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11365: goto end;
11366:
11367: /* Calculation of the number of parameters from char model */
1.234 brouard 11368: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11369: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11370: k=3 V4 Tvar[k=3]= 4 (from V4)
11371: k=2 V1 Tvar[k=2]= 1 (from V1)
11372: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11373: */
11374:
11375: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11376: TvarsDind=ivector(1,NCOVMAX); /* */
11377: TvarsD=ivector(1,NCOVMAX); /* */
11378: TvarsQind=ivector(1,NCOVMAX); /* */
11379: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11380: TvarF=ivector(1,NCOVMAX); /* */
11381: TvarFind=ivector(1,NCOVMAX); /* */
11382: TvarV=ivector(1,NCOVMAX); /* */
11383: TvarVind=ivector(1,NCOVMAX); /* */
11384: TvarA=ivector(1,NCOVMAX); /* */
11385: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11386: TvarFD=ivector(1,NCOVMAX); /* */
11387: TvarFDind=ivector(1,NCOVMAX); /* */
11388: TvarFQ=ivector(1,NCOVMAX); /* */
11389: TvarFQind=ivector(1,NCOVMAX); /* */
11390: TvarVD=ivector(1,NCOVMAX); /* */
11391: TvarVDind=ivector(1,NCOVMAX); /* */
11392: TvarVQ=ivector(1,NCOVMAX); /* */
11393: TvarVQind=ivector(1,NCOVMAX); /* */
11394:
1.230 brouard 11395: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11396: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11397: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11398: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11399: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11400: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11401: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11402: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11403: */
11404: /* For model-covariate k tells which data-covariate to use but
11405: because this model-covariate is a construction we invent a new column
11406: ncovcol + k1
11407: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11408: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11409: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11410: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11411: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11412: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11413: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11414: */
1.145 brouard 11415: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11416: 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 11417: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11418: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11419: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11420: 4 covariates (3 plus signs)
11421: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11422: */
1.230 brouard 11423: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11424: * individual dummy, fixed or varying:
11425: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11426: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11427: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11428: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11429: * Tmodelind[1]@9={9,0,3,2,}*/
11430: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11431: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11432: * individual quantitative, fixed or varying:
11433: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11434: * 3, 1, 0, 0, 0, 0, 0, 0},
11435: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11436: /* Main decodemodel */
11437:
1.187 brouard 11438:
1.223 brouard 11439: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11440: goto end;
11441:
1.137 brouard 11442: if((double)(lastobs-imx)/(double)imx > 1.10){
11443: nbwarn++;
11444: 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);
11445: 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);
11446: }
1.136 brouard 11447: /* if(mle==1){*/
1.137 brouard 11448: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11449: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11450: }
11451:
11452: /*-calculation of age at interview from date of interview and age at death -*/
11453: agev=matrix(1,maxwav,1,imx);
11454:
11455: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11456: goto end;
11457:
1.126 brouard 11458:
1.136 brouard 11459: agegomp=(int)agemin;
11460: free_vector(moisnais,1,n);
11461: free_vector(annais,1,n);
1.126 brouard 11462: /* free_matrix(mint,1,maxwav,1,n);
11463: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11464: /* free_vector(moisdc,1,n); */
11465: /* free_vector(andc,1,n); */
1.145 brouard 11466: /* */
11467:
1.126 brouard 11468: wav=ivector(1,imx);
1.214 brouard 11469: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11470: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11471: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11472: 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.*/
11473: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11474: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11475:
11476: /* Concatenates waves */
1.214 brouard 11477: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11478: Death is a valid wave (if date is known).
11479: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11480: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11481: and mw[mi+1][i]. dh depends on stepm.
11482: */
11483:
1.126 brouard 11484: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11485: /* Concatenates waves */
1.145 brouard 11486:
1.215 brouard 11487: free_vector(moisdc,1,n);
11488: free_vector(andc,1,n);
11489:
1.126 brouard 11490: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11491: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11492: ncodemax[1]=1;
1.145 brouard 11493: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11494: cptcoveff=0;
1.220 brouard 11495: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11496: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11497: }
11498:
11499: ncovcombmax=pow(2,cptcoveff);
11500: invalidvarcomb=ivector(1, ncovcombmax);
11501: for(i=1;i<ncovcombmax;i++)
11502: invalidvarcomb[i]=0;
11503:
1.211 brouard 11504: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11505: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11506: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11507:
1.200 brouard 11508: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11509: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11510: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11511: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11512: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11513: * (currently 0 or 1) in the data.
11514: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11515: * corresponding modality (h,j).
11516: */
11517:
1.145 brouard 11518: h=0;
11519: /*if (cptcovn > 0) */
1.126 brouard 11520: m=pow(2,cptcoveff);
11521:
1.144 brouard 11522: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11523: * For k=4 covariates, h goes from 1 to m=2**k
11524: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11525: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11526: * h\k 1 2 3 4
1.143 brouard 11527: *______________________________
11528: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11529: * 2 2 1 1 1
11530: * 3 i=2 1 2 1 1
11531: * 4 2 2 1 1
11532: * 5 i=3 1 i=2 1 2 1
11533: * 6 2 1 2 1
11534: * 7 i=4 1 2 2 1
11535: * 8 2 2 2 1
1.197 brouard 11536: * 9 i=5 1 i=3 1 i=2 1 2
11537: * 10 2 1 1 2
11538: * 11 i=6 1 2 1 2
11539: * 12 2 2 1 2
11540: * 13 i=7 1 i=4 1 2 2
11541: * 14 2 1 2 2
11542: * 15 i=8 1 2 2 2
11543: * 16 2 2 2 2
1.143 brouard 11544: */
1.212 brouard 11545: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11546: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11547: * and the value of each covariate?
11548: * V1=1, V2=1, V3=2, V4=1 ?
11549: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11550: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11551: * In order to get the real value in the data, we use nbcode
11552: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11553: * We are keeping this crazy system in order to be able (in the future?)
11554: * to have more than 2 values (0 or 1) for a covariate.
11555: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11556: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11557: * bbbbbbbb
11558: * 76543210
11559: * h-1 00000101 (6-1=5)
1.219 brouard 11560: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11561: * &
11562: * 1 00000001 (1)
1.219 brouard 11563: * 00000000 = 1 & ((h-1) >> (k-1))
11564: * +1= 00000001 =1
1.211 brouard 11565: *
11566: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11567: * h' 1101 =2^3+2^2+0x2^1+2^0
11568: * >>k' 11
11569: * & 00000001
11570: * = 00000001
11571: * +1 = 00000010=2 = codtabm(14,3)
11572: * Reverse h=6 and m=16?
11573: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11574: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11575: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11576: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11577: * V3=decodtabm(14,3,2**4)=2
11578: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11579: *(h-1) >> (j-1) 0011 =13 >> 2
11580: * &1 000000001
11581: * = 000000001
11582: * +1= 000000010 =2
11583: * 2211
11584: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11585: * V3=2
1.220 brouard 11586: * codtabm and decodtabm are identical
1.211 brouard 11587: */
11588:
1.145 brouard 11589:
11590: free_ivector(Ndum,-1,NCOVMAX);
11591:
11592:
1.126 brouard 11593:
1.186 brouard 11594: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11595: strcpy(optionfilegnuplot,optionfilefiname);
11596: if(mle==-3)
1.201 brouard 11597: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11598: strcat(optionfilegnuplot,".gp");
11599:
11600: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11601: printf("Problem with file %s",optionfilegnuplot);
11602: }
11603: else{
1.204 brouard 11604: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11605: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11606: //fprintf(ficgp,"set missing 'NaNq'\n");
11607: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11608: }
11609: /* fclose(ficgp);*/
1.186 brouard 11610:
11611:
11612: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11613:
11614: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11615: if(mle==-3)
1.201 brouard 11616: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11617: strcat(optionfilehtm,".htm");
11618: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11619: printf("Problem with %s \n",optionfilehtm);
11620: exit(0);
1.126 brouard 11621: }
11622:
11623: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11624: strcat(optionfilehtmcov,"-cov.htm");
11625: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11626: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11627: }
11628: else{
11629: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11630: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11631: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11632: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11633: }
11634:
1.213 brouard 11635: 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 11636: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11637: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11638: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11639: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11640: \n\
11641: <hr size=\"2\" color=\"#EC5E5E\">\
11642: <ul><li><h4>Parameter files</h4>\n\
11643: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11644: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11645: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11646: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11647: - Date and time at start: %s</ul>\n",\
11648: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11649: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11650: fileres,fileres,\
11651: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11652: fflush(fichtm);
11653:
11654: strcpy(pathr,path);
11655: strcat(pathr,optionfilefiname);
1.184 brouard 11656: #ifdef WIN32
11657: _chdir(optionfilefiname); /* Move to directory named optionfile */
11658: #else
1.126 brouard 11659: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11660: #endif
11661:
1.126 brouard 11662:
1.220 brouard 11663: /* Calculates basic frequencies. Computes observed prevalence at single age
11664: and for any valid combination of covariates
1.126 brouard 11665: and prints on file fileres'p'. */
1.251 brouard 11666: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11667: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11668:
11669: fprintf(fichtm,"\n");
1.286 brouard 11670: 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 11671: ftol, stepm);
11672: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
11673: ncurrv=1;
11674: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
11675: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
11676: ncurrv=i;
11677: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
11678: fprintf(fichtm,"\n<li> Number of time varying (wave varying) covariates: ntv=%d ", ntv);
11679: ncurrv=i;
11680: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
11681: fprintf(fichtm,"\n<li>Number of quantitative time varying covariates: nqtv=%d ", nqtv);
11682: ncurrv=i;
11683: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
11684: 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", \
11685: nlstate, ndeath, maxwav, mle, weightopt);
11686:
11687: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
11688: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
11689:
11690:
11691: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Total number of observations=%d <br>\n\
1.126 brouard 11692: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11693: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 11694: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 11695: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 11696: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11697: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11698: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11699: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11700:
1.126 brouard 11701: /* For Powell, parameters are in a vector p[] starting at p[1]
11702: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11703: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11704:
11705: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11706: /* For mortality only */
1.126 brouard 11707: if (mle==-3){
1.136 brouard 11708: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11709: for(i=1;i<=NDIM;i++)
11710: for(j=1;j<=NDIM;j++)
11711: ximort[i][j]=0.;
1.186 brouard 11712: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.126 brouard 11713: cens=ivector(1,n);
11714: ageexmed=vector(1,n);
11715: agecens=vector(1,n);
11716: dcwave=ivector(1,n);
1.223 brouard 11717:
1.126 brouard 11718: for (i=1; i<=imx; i++){
11719: dcwave[i]=-1;
11720: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11721: if (s[m][i]>nlstate) {
11722: dcwave[i]=m;
11723: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11724: break;
11725: }
1.126 brouard 11726: }
1.226 brouard 11727:
1.126 brouard 11728: for (i=1; i<=imx; i++) {
11729: if (wav[i]>0){
1.226 brouard 11730: ageexmed[i]=agev[mw[1][i]][i];
11731: j=wav[i];
11732: agecens[i]=1.;
11733:
11734: if (ageexmed[i]> 1 && wav[i] > 0){
11735: agecens[i]=agev[mw[j][i]][i];
11736: cens[i]= 1;
11737: }else if (ageexmed[i]< 1)
11738: cens[i]= -1;
11739: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11740: cens[i]=0 ;
1.126 brouard 11741: }
11742: else cens[i]=-1;
11743: }
11744:
11745: for (i=1;i<=NDIM;i++) {
11746: for (j=1;j<=NDIM;j++)
1.226 brouard 11747: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 11748: }
11749:
1.145 brouard 11750: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 11751: /*printf("%lf %lf", p[1], p[2]);*/
11752:
11753:
1.136 brouard 11754: #ifdef GSL
11755: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 11756: #else
1.126 brouard 11757: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 11758: #endif
1.201 brouard 11759: strcpy(filerespow,"POW-MORT_");
11760: strcat(filerespow,fileresu);
1.126 brouard 11761: if((ficrespow=fopen(filerespow,"w"))==NULL) {
11762: printf("Problem with resultfile: %s\n", filerespow);
11763: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
11764: }
1.136 brouard 11765: #ifdef GSL
11766: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 11767: #else
1.126 brouard 11768: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 11769: #endif
1.126 brouard 11770: /* for (i=1;i<=nlstate;i++)
11771: for(j=1;j<=nlstate+ndeath;j++)
11772: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
11773: */
11774: fprintf(ficrespow,"\n");
1.136 brouard 11775: #ifdef GSL
11776: /* gsl starts here */
11777: T = gsl_multimin_fminimizer_nmsimplex;
11778: gsl_multimin_fminimizer *sfm = NULL;
11779: gsl_vector *ss, *x;
11780: gsl_multimin_function minex_func;
11781:
11782: /* Initial vertex size vector */
11783: ss = gsl_vector_alloc (NDIM);
11784:
11785: if (ss == NULL){
11786: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
11787: }
11788: /* Set all step sizes to 1 */
11789: gsl_vector_set_all (ss, 0.001);
11790:
11791: /* Starting point */
1.126 brouard 11792:
1.136 brouard 11793: x = gsl_vector_alloc (NDIM);
11794:
11795: if (x == NULL){
11796: gsl_vector_free(ss);
11797: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
11798: }
11799:
11800: /* Initialize method and iterate */
11801: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 11802: /* gsl_vector_set(x, 0, 0.0268); */
11803: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 11804: gsl_vector_set(x, 0, p[1]);
11805: gsl_vector_set(x, 1, p[2]);
11806:
11807: minex_func.f = &gompertz_f;
11808: minex_func.n = NDIM;
11809: minex_func.params = (void *)&p; /* ??? */
11810:
11811: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
11812: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
11813:
11814: printf("Iterations beginning .....\n\n");
11815: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
11816:
11817: iteri=0;
11818: while (rval == GSL_CONTINUE){
11819: iteri++;
11820: status = gsl_multimin_fminimizer_iterate(sfm);
11821:
11822: if (status) printf("error: %s\n", gsl_strerror (status));
11823: fflush(0);
11824:
11825: if (status)
11826: break;
11827:
11828: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
11829: ssval = gsl_multimin_fminimizer_size (sfm);
11830:
11831: if (rval == GSL_SUCCESS)
11832: printf ("converged to a local maximum at\n");
11833:
11834: printf("%5d ", iteri);
11835: for (it = 0; it < NDIM; it++){
11836: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
11837: }
11838: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
11839: }
11840:
11841: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
11842:
11843: gsl_vector_free(x); /* initial values */
11844: gsl_vector_free(ss); /* inital step size */
11845: for (it=0; it<NDIM; it++){
11846: p[it+1]=gsl_vector_get(sfm->x,it);
11847: fprintf(ficrespow," %.12lf", p[it]);
11848: }
11849: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
11850: #endif
11851: #ifdef POWELL
11852: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
11853: #endif
1.126 brouard 11854: fclose(ficrespow);
11855:
1.203 brouard 11856: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 11857:
11858: for(i=1; i <=NDIM; i++)
11859: for(j=i+1;j<=NDIM;j++)
1.220 brouard 11860: matcov[i][j]=matcov[j][i];
1.126 brouard 11861:
11862: printf("\nCovariance matrix\n ");
1.203 brouard 11863: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 11864: for(i=1; i <=NDIM; i++) {
11865: for(j=1;j<=NDIM;j++){
1.220 brouard 11866: printf("%f ",matcov[i][j]);
11867: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 11868: }
1.203 brouard 11869: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 11870: }
11871:
11872: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 11873: for (i=1;i<=NDIM;i++) {
1.126 brouard 11874: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 11875: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
11876: }
1.126 brouard 11877: lsurv=vector(1,AGESUP);
11878: lpop=vector(1,AGESUP);
11879: tpop=vector(1,AGESUP);
11880: lsurv[agegomp]=100000;
11881:
11882: for (k=agegomp;k<=AGESUP;k++) {
11883: agemortsup=k;
11884: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
11885: }
11886:
11887: for (k=agegomp;k<agemortsup;k++)
11888: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
11889:
11890: for (k=agegomp;k<agemortsup;k++){
11891: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
11892: sumlpop=sumlpop+lpop[k];
11893: }
11894:
11895: tpop[agegomp]=sumlpop;
11896: for (k=agegomp;k<(agemortsup-3);k++){
11897: /* tpop[k+1]=2;*/
11898: tpop[k+1]=tpop[k]-lpop[k];
11899: }
11900:
11901:
11902: printf("\nAge lx qx dx Lx Tx e(x)\n");
11903: for (k=agegomp;k<(agemortsup-2);k++)
11904: 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]);
11905:
11906:
11907: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 11908: ageminpar=50;
11909: agemaxpar=100;
1.194 brouard 11910: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
11911: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11912: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11913: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
11914: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11915: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11916: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 11917: }else{
11918: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
11919: 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 11920: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 11921: }
1.201 brouard 11922: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 11923: stepm, weightopt,\
11924: model,imx,p,matcov,agemortsup);
11925:
11926: free_vector(lsurv,1,AGESUP);
11927: free_vector(lpop,1,AGESUP);
11928: free_vector(tpop,1,AGESUP);
1.220 brouard 11929: free_matrix(ximort,1,NDIM,1,NDIM);
1.136 brouard 11930: free_ivector(cens,1,n);
11931: free_vector(agecens,1,n);
11932: free_ivector(dcwave,1,n);
1.220 brouard 11933: #ifdef GSL
1.136 brouard 11934: #endif
1.186 brouard 11935: } /* Endof if mle==-3 mortality only */
1.205 brouard 11936: /* Standard */
11937: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
11938: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11939: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 11940: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 11941: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11942: for (k=1; k<=npar;k++)
11943: printf(" %d %8.5f",k,p[k]);
11944: printf("\n");
1.205 brouard 11945: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
11946: /* mlikeli uses func not funcone */
1.247 brouard 11947: /* for(i=1;i<nlstate;i++){ */
11948: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11949: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11950: /* } */
1.205 brouard 11951: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
11952: }
11953: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
11954: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11955: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
11956: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11957: }
11958: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 11959: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11960: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11961: for (k=1; k<=npar;k++)
11962: printf(" %d %8.5f",k,p[k]);
11963: printf("\n");
11964:
11965: /*--------- results files --------------*/
1.283 brouard 11966: /* 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 11967:
11968:
11969: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11970: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11971: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11972: for(i=1,jk=1; i <=nlstate; i++){
11973: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 11974: if (k != i) {
11975: printf("%d%d ",i,k);
11976: fprintf(ficlog,"%d%d ",i,k);
11977: fprintf(ficres,"%1d%1d ",i,k);
11978: for(j=1; j <=ncovmodel; j++){
11979: printf("%12.7f ",p[jk]);
11980: fprintf(ficlog,"%12.7f ",p[jk]);
11981: fprintf(ficres,"%12.7f ",p[jk]);
11982: jk++;
11983: }
11984: printf("\n");
11985: fprintf(ficlog,"\n");
11986: fprintf(ficres,"\n");
11987: }
1.126 brouard 11988: }
11989: }
1.203 brouard 11990: if(mle != 0){
11991: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 11992: ftolhess=ftol; /* Usually correct */
1.203 brouard 11993: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
11994: 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");
11995: 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");
11996: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 11997: for(k=1; k <=(nlstate+ndeath); k++){
11998: if (k != i) {
11999: printf("%d%d ",i,k);
12000: fprintf(ficlog,"%d%d ",i,k);
12001: for(j=1; j <=ncovmodel; j++){
12002: 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]));
12003: 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]));
12004: jk++;
12005: }
12006: printf("\n");
12007: fprintf(ficlog,"\n");
12008: }
12009: }
1.193 brouard 12010: }
1.203 brouard 12011: } /* end of hesscov and Wald tests */
1.225 brouard 12012:
1.203 brouard 12013: /* */
1.126 brouard 12014: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
12015: printf("# Scales (for hessian or gradient estimation)\n");
12016: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
12017: for(i=1,jk=1; i <=nlstate; i++){
12018: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 12019: if (j!=i) {
12020: fprintf(ficres,"%1d%1d",i,j);
12021: printf("%1d%1d",i,j);
12022: fprintf(ficlog,"%1d%1d",i,j);
12023: for(k=1; k<=ncovmodel;k++){
12024: printf(" %.5e",delti[jk]);
12025: fprintf(ficlog," %.5e",delti[jk]);
12026: fprintf(ficres," %.5e",delti[jk]);
12027: jk++;
12028: }
12029: printf("\n");
12030: fprintf(ficlog,"\n");
12031: fprintf(ficres,"\n");
12032: }
1.126 brouard 12033: }
12034: }
12035:
12036: 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 12037: if(mle >= 1) /* To big for the screen */
1.126 brouard 12038: 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");
12039: 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");
12040: /* # 121 Var(a12)\n\ */
12041: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12042: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12043: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12044: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12045: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12046: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12047: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12048:
12049:
12050: /* Just to have a covariance matrix which will be more understandable
12051: even is we still don't want to manage dictionary of variables
12052: */
12053: for(itimes=1;itimes<=2;itimes++){
12054: jj=0;
12055: for(i=1; i <=nlstate; i++){
1.225 brouard 12056: for(j=1; j <=nlstate+ndeath; j++){
12057: if(j==i) continue;
12058: for(k=1; k<=ncovmodel;k++){
12059: jj++;
12060: ca[0]= k+'a'-1;ca[1]='\0';
12061: if(itimes==1){
12062: if(mle>=1)
12063: printf("#%1d%1d%d",i,j,k);
12064: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12065: fprintf(ficres,"#%1d%1d%d",i,j,k);
12066: }else{
12067: if(mle>=1)
12068: printf("%1d%1d%d",i,j,k);
12069: fprintf(ficlog,"%1d%1d%d",i,j,k);
12070: fprintf(ficres,"%1d%1d%d",i,j,k);
12071: }
12072: ll=0;
12073: for(li=1;li <=nlstate; li++){
12074: for(lj=1;lj <=nlstate+ndeath; lj++){
12075: if(lj==li) continue;
12076: for(lk=1;lk<=ncovmodel;lk++){
12077: ll++;
12078: if(ll<=jj){
12079: cb[0]= lk +'a'-1;cb[1]='\0';
12080: if(ll<jj){
12081: if(itimes==1){
12082: if(mle>=1)
12083: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12084: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12085: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12086: }else{
12087: if(mle>=1)
12088: printf(" %.5e",matcov[jj][ll]);
12089: fprintf(ficlog," %.5e",matcov[jj][ll]);
12090: fprintf(ficres," %.5e",matcov[jj][ll]);
12091: }
12092: }else{
12093: if(itimes==1){
12094: if(mle>=1)
12095: printf(" Var(%s%1d%1d)",ca,i,j);
12096: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12097: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12098: }else{
12099: if(mle>=1)
12100: printf(" %.7e",matcov[jj][ll]);
12101: fprintf(ficlog," %.7e",matcov[jj][ll]);
12102: fprintf(ficres," %.7e",matcov[jj][ll]);
12103: }
12104: }
12105: }
12106: } /* end lk */
12107: } /* end lj */
12108: } /* end li */
12109: if(mle>=1)
12110: printf("\n");
12111: fprintf(ficlog,"\n");
12112: fprintf(ficres,"\n");
12113: numlinepar++;
12114: } /* end k*/
12115: } /*end j */
1.126 brouard 12116: } /* end i */
12117: } /* end itimes */
12118:
12119: fflush(ficlog);
12120: fflush(ficres);
1.225 brouard 12121: while(fgets(line, MAXLINE, ficpar)) {
12122: /* If line starts with a # it is a comment */
12123: if (line[0] == '#') {
12124: numlinepar++;
12125: fputs(line,stdout);
12126: fputs(line,ficparo);
12127: fputs(line,ficlog);
12128: continue;
12129: }else
12130: break;
12131: }
12132:
1.209 brouard 12133: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12134: /* ungetc(c,ficpar); */
12135: /* fgets(line, MAXLINE, ficpar); */
12136: /* fputs(line,stdout); */
12137: /* fputs(line,ficparo); */
12138: /* } */
12139: /* ungetc(c,ficpar); */
1.126 brouard 12140:
12141: estepm=0;
1.209 brouard 12142: 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 12143:
12144: if (num_filled != 6) {
12145: 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);
12146: 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);
12147: goto end;
12148: }
12149: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12150: }
12151: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12152: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12153:
1.209 brouard 12154: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12155: if (estepm==0 || estepm < stepm) estepm=stepm;
12156: if (fage <= 2) {
12157: bage = ageminpar;
12158: fage = agemaxpar;
12159: }
12160:
12161: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12162: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12163: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12164:
1.186 brouard 12165: /* Other stuffs, more or less useful */
1.254 brouard 12166: while(fgets(line, MAXLINE, ficpar)) {
12167: /* If line starts with a # it is a comment */
12168: if (line[0] == '#') {
12169: numlinepar++;
12170: fputs(line,stdout);
12171: fputs(line,ficparo);
12172: fputs(line,ficlog);
12173: continue;
12174: }else
12175: break;
12176: }
12177:
12178: 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){
12179:
12180: if (num_filled != 7) {
12181: 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);
12182: 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);
12183: goto end;
12184: }
12185: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12186: 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);
12187: 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);
12188: 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 12189: }
1.254 brouard 12190:
12191: while(fgets(line, MAXLINE, ficpar)) {
12192: /* If line starts with a # it is a comment */
12193: if (line[0] == '#') {
12194: numlinepar++;
12195: fputs(line,stdout);
12196: fputs(line,ficparo);
12197: fputs(line,ficlog);
12198: continue;
12199: }else
12200: break;
1.126 brouard 12201: }
12202:
12203:
12204: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12205: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12206:
1.254 brouard 12207: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12208: if (num_filled != 1) {
12209: 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);
12210: 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);
12211: goto end;
12212: }
12213: printf("pop_based=%d\n",popbased);
12214: fprintf(ficlog,"pop_based=%d\n",popbased);
12215: fprintf(ficparo,"pop_based=%d\n",popbased);
12216: fprintf(ficres,"pop_based=%d\n",popbased);
12217: }
12218:
1.258 brouard 12219: /* Results */
12220: nresult=0;
12221: do{
12222: if(!fgets(line, MAXLINE, ficpar)){
12223: endishere=1;
12224: parameterline=14;
12225: }else if (line[0] == '#') {
12226: /* If line starts with a # it is a comment */
1.254 brouard 12227: numlinepar++;
12228: fputs(line,stdout);
12229: fputs(line,ficparo);
12230: fputs(line,ficlog);
12231: continue;
1.258 brouard 12232: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12233: parameterline=11;
12234: else if(sscanf(line,"backcast=%[^\n]\n",modeltemp))
12235: parameterline=12;
12236: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
12237: parameterline=13;
12238: else{
12239: parameterline=14;
1.254 brouard 12240: }
1.258 brouard 12241: switch (parameterline){
12242: case 11:
12243: 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){
12244: if (num_filled != 8) {
12245: 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);
12246: 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);
12247: goto end;
12248: }
12249: 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);
12250: 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);
12251: 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);
12252: 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);
12253: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12254: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12255: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
12256:
1.258 brouard 12257: }
1.254 brouard 12258: break;
1.258 brouard 12259: case 12:
12260: /*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);*/
12261: 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){
12262: if (num_filled != 8) {
1.262 brouard 12263: 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);
12264: 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 12265: goto end;
12266: }
12267: 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);
12268: 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);
12269: 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);
12270: 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);
12271: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12272: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12273: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.258 brouard 12274: }
1.230 brouard 12275: break;
1.258 brouard 12276: case 13:
12277: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
12278: if (num_filled == 0){
12279: resultline[0]='\0';
12280: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12281: 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);
12282: break;
12283: } else if (num_filled != 1){
12284: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12285: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12286: }
12287: nresult++; /* Sum of resultlines */
12288: printf("Result %d: result=%s\n",nresult, resultline);
12289: if(nresult > MAXRESULTLINES){
12290: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12291: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12292: goto end;
12293: }
12294: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
12295: fprintf(ficparo,"result: %s\n",resultline);
12296: fprintf(ficres,"result: %s\n",resultline);
12297: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 12298: break;
1.258 brouard 12299: case 14:
1.259 brouard 12300: if(ncovmodel >2 && nresult==0 ){
12301: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12302: goto end;
12303: }
1.259 brouard 12304: break;
1.258 brouard 12305: default:
12306: nresult=1;
12307: decoderesult(".",nresult ); /* No covariate */
12308: }
12309: } /* End switch parameterline */
12310: }while(endishere==0); /* End do */
1.126 brouard 12311:
1.230 brouard 12312: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12313: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12314:
12315: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12316: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12317: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12318: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12319: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12320: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12321: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12322: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12323: }else{
1.270 brouard 12324: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
12325: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, backcast, pathc,p, (int)anproj1-bage, (int)anback1-fage);
1.220 brouard 12326: }
12327: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.258 brouard 12328: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,backcast, estepm, \
1.273 brouard 12329: jprev1,mprev1,anprev1,dateprev1, dateproj1, dateback1,jprev2,mprev2,anprev2,dateprev2,dateproj2, dateback2);
1.220 brouard 12330:
1.225 brouard 12331: /*------------ free_vector -------------*/
12332: /* chdir(path); */
1.220 brouard 12333:
1.215 brouard 12334: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12335: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12336: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12337: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.126 brouard 12338: free_lvector(num,1,n);
12339: free_vector(agedc,1,n);
12340: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12341: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12342: fclose(ficparo);
12343: fclose(ficres);
1.220 brouard 12344:
12345:
1.186 brouard 12346: /* Other results (useful)*/
1.220 brouard 12347:
12348:
1.126 brouard 12349: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12350: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12351: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12352: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12353: fclose(ficrespl);
12354:
12355: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12356: /*#include "hpijx.h"*/
12357: hPijx(p, bage, fage);
1.145 brouard 12358: fclose(ficrespij);
1.227 brouard 12359:
1.220 brouard 12360: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12361: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12362: k=1;
1.126 brouard 12363: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12364:
1.269 brouard 12365: /* Prevalence for each covariate combination in probs[age][status][cov] */
12366: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12367: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12368: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12369: for(k=1;k<=ncovcombmax;k++)
12370: probs[i][j][k]=0.;
1.269 brouard 12371: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
12372: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12373: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 12374: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12375: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12376: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12377: for(k=1;k<=ncovcombmax;k++)
12378: mobaverages[i][j][k]=0.;
1.219 brouard 12379: mobaverage=mobaverages;
12380: if (mobilav!=0) {
1.235 brouard 12381: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12382: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12383: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12384: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12385: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12386: }
1.269 brouard 12387: } else if (mobilavproj !=0) {
1.235 brouard 12388: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12389: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12390: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12391: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12392: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12393: }
1.269 brouard 12394: }else{
12395: printf("Internal error moving average\n");
12396: fflush(stdout);
12397: exit(1);
1.219 brouard 12398: }
12399: }/* end if moving average */
1.227 brouard 12400:
1.126 brouard 12401: /*---------- Forecasting ------------------*/
12402: if(prevfcast==1){
12403: /* if(stepm ==1){*/
1.269 brouard 12404: prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
1.126 brouard 12405: }
1.269 brouard 12406:
12407: /* Backcasting */
1.217 brouard 12408: if(backcast==1){
1.219 brouard 12409: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12410: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12411: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12412:
12413: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12414:
12415: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 12416:
1.219 brouard 12417: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12418: fclose(ficresplb);
12419:
1.222 brouard 12420: hBijx(p, bage, fage, mobaverage);
12421: fclose(ficrespijb);
1.219 brouard 12422:
1.269 brouard 12423: prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2,
12424: mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff);
12425: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12426:
12427:
1.269 brouard 12428: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12429: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12430: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12431: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.269 brouard 12432: } /* end Backcasting */
1.268 brouard 12433:
1.186 brouard 12434:
12435: /* ------ Other prevalence ratios------------ */
1.126 brouard 12436:
1.215 brouard 12437: free_ivector(wav,1,imx);
12438: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12439: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12440: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12441:
12442:
1.127 brouard 12443: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12444:
1.201 brouard 12445: strcpy(filerese,"E_");
12446: strcat(filerese,fileresu);
1.126 brouard 12447: if((ficreseij=fopen(filerese,"w"))==NULL) {
12448: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12449: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12450: }
1.208 brouard 12451: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12452: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12453:
12454: pstamp(ficreseij);
1.219 brouard 12455:
1.235 brouard 12456: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12457: if (cptcovn < 1){i1=1;}
12458:
12459: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12460: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12461: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12462: continue;
1.219 brouard 12463: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12464: printf("\n#****** ");
1.225 brouard 12465: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12466: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12467: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12468: }
12469: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12470: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12471: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12472: }
12473: fprintf(ficreseij,"******\n");
1.235 brouard 12474: printf("******\n");
1.219 brouard 12475:
12476: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12477: oldm=oldms;savm=savms;
1.235 brouard 12478: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12479:
1.219 brouard 12480: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12481: }
12482: fclose(ficreseij);
1.208 brouard 12483: printf("done evsij\n");fflush(stdout);
12484: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 12485:
1.218 brouard 12486:
1.227 brouard 12487: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12488:
1.201 brouard 12489: strcpy(filerest,"T_");
12490: strcat(filerest,fileresu);
1.127 brouard 12491: if((ficrest=fopen(filerest,"w"))==NULL) {
12492: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12493: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12494: }
1.208 brouard 12495: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12496: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12497: strcpy(fileresstde,"STDE_");
12498: strcat(fileresstde,fileresu);
1.126 brouard 12499: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12500: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12501: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12502: }
1.227 brouard 12503: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12504: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12505:
1.201 brouard 12506: strcpy(filerescve,"CVE_");
12507: strcat(filerescve,fileresu);
1.126 brouard 12508: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12509: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12510: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12511: }
1.227 brouard 12512: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12513: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12514:
1.201 brouard 12515: strcpy(fileresv,"V_");
12516: strcat(fileresv,fileresu);
1.126 brouard 12517: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12518: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12519: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12520: }
1.227 brouard 12521: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12522: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12523:
1.235 brouard 12524: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12525: if (cptcovn < 1){i1=1;}
12526:
12527: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12528: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12529: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12530: continue;
1.242 brouard 12531: printf("\n#****** Result for:");
12532: fprintf(ficrest,"\n#****** Result for:");
12533: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12534: for(j=1;j<=cptcoveff;j++){
12535: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12536: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12537: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12538: }
1.235 brouard 12539: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12540: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12541: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12542: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12543: }
1.208 brouard 12544: fprintf(ficrest,"******\n");
1.227 brouard 12545: fprintf(ficlog,"******\n");
12546: printf("******\n");
1.208 brouard 12547:
12548: fprintf(ficresstdeij,"\n#****** ");
12549: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12550: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12551: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12552: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12553: }
1.235 brouard 12554: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12555: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12556: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12557: }
1.208 brouard 12558: fprintf(ficresstdeij,"******\n");
12559: fprintf(ficrescveij,"******\n");
12560:
12561: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12562: /* pstamp(ficresvij); */
1.225 brouard 12563: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12564: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12565: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12566: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12567: }
1.208 brouard 12568: fprintf(ficresvij,"******\n");
12569:
12570: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12571: oldm=oldms;savm=savms;
1.235 brouard 12572: printf(" cvevsij ");
12573: fprintf(ficlog, " cvevsij ");
12574: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12575: printf(" end cvevsij \n ");
12576: fprintf(ficlog, " end cvevsij \n ");
12577:
12578: /*
12579: */
12580: /* goto endfree; */
12581:
12582: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12583: pstamp(ficrest);
12584:
1.269 brouard 12585: epj=vector(1,nlstate+1);
1.208 brouard 12586: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12587: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12588: cptcod= 0; /* To be deleted */
12589: printf("varevsij vpopbased=%d \n",vpopbased);
12590: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12591: 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 12592: 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 ");
12593: if(vpopbased==1)
12594: 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);
12595: else
1.288 brouard 12596: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12597: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12598: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12599: fprintf(ficrest,"\n");
12600: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 12601: printf("Computing age specific forward period (stable) prevalences in each health state \n");
12602: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12603: for(age=bage; age <=fage ;age++){
1.235 brouard 12604: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12605: if (vpopbased==1) {
12606: if(mobilav ==0){
12607: for(i=1; i<=nlstate;i++)
12608: prlim[i][i]=probs[(int)age][i][k];
12609: }else{ /* mobilav */
12610: for(i=1; i<=nlstate;i++)
12611: prlim[i][i]=mobaverage[(int)age][i][k];
12612: }
12613: }
1.219 brouard 12614:
1.227 brouard 12615: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12616: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12617: /* printf(" age %4.0f ",age); */
12618: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12619: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12620: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12621: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12622: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12623: }
12624: epj[nlstate+1] +=epj[j];
12625: }
12626: /* printf(" age %4.0f \n",age); */
1.219 brouard 12627:
1.227 brouard 12628: for(i=1, vepp=0.;i <=nlstate;i++)
12629: for(j=1;j <=nlstate;j++)
12630: vepp += vareij[i][j][(int)age];
12631: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12632: for(j=1;j <=nlstate;j++){
12633: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12634: }
12635: fprintf(ficrest,"\n");
12636: }
1.208 brouard 12637: } /* End vpopbased */
1.269 brouard 12638: free_vector(epj,1,nlstate+1);
1.208 brouard 12639: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12640: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 12641: printf("done selection\n");fflush(stdout);
12642: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12643:
1.235 brouard 12644: } /* End k selection */
1.227 brouard 12645:
12646: printf("done State-specific expectancies\n");fflush(stdout);
12647: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12648:
1.288 brouard 12649: /* variance-covariance of forward period prevalence*/
1.269 brouard 12650: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12651:
1.227 brouard 12652:
12653: free_vector(weight,1,n);
12654: free_imatrix(Tvard,1,NCOVMAX,1,2);
12655: free_imatrix(s,1,maxwav+1,1,n);
12656: free_matrix(anint,1,maxwav,1,n);
12657: free_matrix(mint,1,maxwav,1,n);
12658: free_ivector(cod,1,n);
12659: free_ivector(tab,1,NCOVMAX);
12660: fclose(ficresstdeij);
12661: fclose(ficrescveij);
12662: fclose(ficresvij);
12663: fclose(ficrest);
12664: fclose(ficpar);
12665:
12666:
1.126 brouard 12667: /*---------- End : free ----------------*/
1.219 brouard 12668: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 12669: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
12670: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12671: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12672: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12673: } /* mle==-3 arrives here for freeing */
1.227 brouard 12674: /* endfree:*/
12675: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12676: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12677: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.268 brouard 12678: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,1,n);
12679: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,1,n);
12680: if(nqv>=1)free_matrix(coqvar,1,nqv,1,n);
1.227 brouard 12681: free_matrix(covar,0,NCOVMAX,1,n);
12682: free_matrix(matcov,1,npar,1,npar);
12683: free_matrix(hess,1,npar,1,npar);
12684: /*free_vector(delti,1,npar);*/
12685: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12686: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 12687: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 12688: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12689:
12690: free_ivector(ncodemax,1,NCOVMAX);
12691: free_ivector(ncodemaxwundef,1,NCOVMAX);
12692: free_ivector(Dummy,-1,NCOVMAX);
12693: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 12694: free_ivector(DummyV,1,NCOVMAX);
12695: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 12696: free_ivector(Typevar,-1,NCOVMAX);
12697: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 12698: free_ivector(TvarsQ,1,NCOVMAX);
12699: free_ivector(TvarsQind,1,NCOVMAX);
12700: free_ivector(TvarsD,1,NCOVMAX);
12701: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 12702: free_ivector(TvarFD,1,NCOVMAX);
12703: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 12704: free_ivector(TvarF,1,NCOVMAX);
12705: free_ivector(TvarFind,1,NCOVMAX);
12706: free_ivector(TvarV,1,NCOVMAX);
12707: free_ivector(TvarVind,1,NCOVMAX);
12708: free_ivector(TvarA,1,NCOVMAX);
12709: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 12710: free_ivector(TvarFQ,1,NCOVMAX);
12711: free_ivector(TvarFQind,1,NCOVMAX);
12712: free_ivector(TvarVD,1,NCOVMAX);
12713: free_ivector(TvarVDind,1,NCOVMAX);
12714: free_ivector(TvarVQ,1,NCOVMAX);
12715: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 12716: free_ivector(Tvarsel,1,NCOVMAX);
12717: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 12718: free_ivector(Tposprod,1,NCOVMAX);
12719: free_ivector(Tprod,1,NCOVMAX);
12720: free_ivector(Tvaraff,1,NCOVMAX);
12721: free_ivector(invalidvarcomb,1,ncovcombmax);
12722: free_ivector(Tage,1,NCOVMAX);
12723: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 12724: free_ivector(TmodelInvind,1,NCOVMAX);
12725: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 12726:
12727: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
12728: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 12729: fflush(fichtm);
12730: fflush(ficgp);
12731:
1.227 brouard 12732:
1.126 brouard 12733: if((nberr >0) || (nbwarn>0)){
1.216 brouard 12734: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
12735: 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 12736: }else{
12737: printf("End of Imach\n");
12738: fprintf(ficlog,"End of Imach\n");
12739: }
12740: printf("See log file on %s\n",filelog);
12741: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 12742: /*(void) gettimeofday(&end_time,&tzp);*/
12743: rend_time = time(NULL);
12744: end_time = *localtime(&rend_time);
12745: /* tml = *localtime(&end_time.tm_sec); */
12746: strcpy(strtend,asctime(&end_time));
1.126 brouard 12747: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
12748: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 12749: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 12750:
1.157 brouard 12751: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
12752: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
12753: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 12754: /* printf("Total time was %d uSec.\n", total_usecs);*/
12755: /* if(fileappend(fichtm,optionfilehtm)){ */
12756: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12757: fclose(fichtm);
12758: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12759: fclose(fichtmcov);
12760: fclose(ficgp);
12761: fclose(ficlog);
12762: /*------ End -----------*/
1.227 brouard 12763:
1.281 brouard 12764:
12765: /* Executes gnuplot */
1.227 brouard 12766:
12767: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 12768: #ifdef WIN32
1.227 brouard 12769: if (_chdir(pathcd) != 0)
12770: printf("Can't move to directory %s!\n",path);
12771: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 12772: #else
1.227 brouard 12773: if(chdir(pathcd) != 0)
12774: printf("Can't move to directory %s!\n", path);
12775: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 12776: #endif
1.126 brouard 12777: printf("Current directory %s!\n",pathcd);
12778: /*strcat(plotcmd,CHARSEPARATOR);*/
12779: sprintf(plotcmd,"gnuplot");
1.157 brouard 12780: #ifdef _WIN32
1.126 brouard 12781: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
12782: #endif
12783: if(!stat(plotcmd,&info)){
1.158 brouard 12784: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12785: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 12786: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 12787: }else
12788: strcpy(pplotcmd,plotcmd);
1.157 brouard 12789: #ifdef __unix
1.126 brouard 12790: strcpy(plotcmd,GNUPLOTPROGRAM);
12791: if(!stat(plotcmd,&info)){
1.158 brouard 12792: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12793: }else
12794: strcpy(pplotcmd,plotcmd);
12795: #endif
12796: }else
12797: strcpy(pplotcmd,plotcmd);
12798:
12799: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 12800: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.227 brouard 12801:
1.126 brouard 12802: if((outcmd=system(plotcmd)) != 0){
1.158 brouard 12803: printf("gnuplot command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 12804: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 12805: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.150 brouard 12806: if((outcmd=system(plotcmd)) != 0)
1.153 brouard 12807: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.126 brouard 12808: }
1.158 brouard 12809: printf(" Successful, please wait...");
1.126 brouard 12810: while (z[0] != 'q') {
12811: /* chdir(path); */
1.154 brouard 12812: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 12813: scanf("%s",z);
12814: /* if (z[0] == 'c') system("./imach"); */
12815: if (z[0] == 'e') {
1.158 brouard 12816: #ifdef __APPLE__
1.152 brouard 12817: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 12818: #elif __linux
12819: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 12820: #else
1.152 brouard 12821: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 12822: #endif
12823: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
12824: system(pplotcmd);
1.126 brouard 12825: }
12826: else if (z[0] == 'g') system(plotcmd);
12827: else if (z[0] == 'q') exit(0);
12828: }
1.227 brouard 12829: end:
1.126 brouard 12830: while (z[0] != 'q') {
1.195 brouard 12831: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 12832: scanf("%s",z);
12833: }
1.283 brouard 12834: printf("End\n");
1.282 brouard 12835: exit(0);
1.126 brouard 12836: }
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