Annotation of imach/src/imach.c, revision 1.284
1.284 ! brouard 1: /* $Id: imach.c,v 1.283 2018/04/19 14:49:16 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.284 ! brouard 4: Revision 1.283 2018/04/19 14:49:16 brouard
! 5: Summary: Some minor bugs fixed
! 6:
1.283 brouard 7: Revision 1.282 2018/02/27 22:50:02 brouard
8: *** empty log message ***
9:
1.282 brouard 10: Revision 1.281 2018/02/27 19:25:23 brouard
11: Summary: Adding second argument for quitting
12:
1.281 brouard 13: Revision 1.280 2018/02/21 07:58:13 brouard
14: Summary: 0.99r15
15:
16: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
17:
1.280 brouard 18: Revision 1.279 2017/07/20 13:35:01 brouard
19: Summary: temporary working
20:
1.279 brouard 21: Revision 1.278 2017/07/19 14:09:02 brouard
22: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
23:
1.278 brouard 24: Revision 1.277 2017/07/17 08:53:49 brouard
25: Summary: BOM files can be read now
26:
1.277 brouard 27: Revision 1.276 2017/06/30 15:48:31 brouard
28: Summary: Graphs improvements
29:
1.276 brouard 30: Revision 1.275 2017/06/30 13:39:33 brouard
31: Summary: Saito's color
32:
1.275 brouard 33: Revision 1.274 2017/06/29 09:47:08 brouard
34: Summary: Version 0.99r14
35:
1.274 brouard 36: Revision 1.273 2017/06/27 11:06:02 brouard
37: Summary: More documentation on projections
38:
1.273 brouard 39: Revision 1.272 2017/06/27 10:22:40 brouard
40: Summary: Color of backprojection changed from 6 to 5(yellow)
41:
1.272 brouard 42: Revision 1.271 2017/06/27 10:17:50 brouard
43: Summary: Some bug with rint
44:
1.271 brouard 45: Revision 1.270 2017/05/24 05:45:29 brouard
46: *** empty log message ***
47:
1.270 brouard 48: Revision 1.269 2017/05/23 08:39:25 brouard
49: Summary: Code into subroutine, cleanings
50:
1.269 brouard 51: Revision 1.268 2017/05/18 20:09:32 brouard
52: Summary: backprojection and confidence intervals of backprevalence
53:
1.268 brouard 54: Revision 1.267 2017/05/13 10:25:05 brouard
55: Summary: temporary save for backprojection
56:
1.267 brouard 57: Revision 1.266 2017/05/13 07:26:12 brouard
58: Summary: Version 0.99r13 (improvements and bugs fixed)
59:
1.266 brouard 60: Revision 1.265 2017/04/26 16:22:11 brouard
61: Summary: imach 0.99r13 Some bugs fixed
62:
1.265 brouard 63: Revision 1.264 2017/04/26 06:01:29 brouard
64: Summary: Labels in graphs
65:
1.264 brouard 66: Revision 1.263 2017/04/24 15:23:15 brouard
67: Summary: to save
68:
1.263 brouard 69: Revision 1.262 2017/04/18 16:48:12 brouard
70: *** empty log message ***
71:
1.262 brouard 72: Revision 1.261 2017/04/05 10:14:09 brouard
73: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
74:
1.261 brouard 75: Revision 1.260 2017/04/04 17:46:59 brouard
76: Summary: Gnuplot indexations fixed (humm)
77:
1.260 brouard 78: Revision 1.259 2017/04/04 13:01:16 brouard
79: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
80:
1.259 brouard 81: Revision 1.258 2017/04/03 10:17:47 brouard
82: Summary: Version 0.99r12
83:
84: Some cleanings, conformed with updated documentation.
85:
1.258 brouard 86: Revision 1.257 2017/03/29 16:53:30 brouard
87: Summary: Temp
88:
1.257 brouard 89: Revision 1.256 2017/03/27 05:50:23 brouard
90: Summary: Temporary
91:
1.256 brouard 92: Revision 1.255 2017/03/08 16:02:28 brouard
93: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
94:
1.255 brouard 95: Revision 1.254 2017/03/08 07:13:00 brouard
96: Summary: Fixing data parameter line
97:
1.254 brouard 98: Revision 1.253 2016/12/15 11:59:41 brouard
99: Summary: 0.99 in progress
100:
1.253 brouard 101: Revision 1.252 2016/09/15 21:15:37 brouard
102: *** empty log message ***
103:
1.252 brouard 104: Revision 1.251 2016/09/15 15:01:13 brouard
105: Summary: not working
106:
1.251 brouard 107: Revision 1.250 2016/09/08 16:07:27 brouard
108: Summary: continue
109:
1.250 brouard 110: Revision 1.249 2016/09/07 17:14:18 brouard
111: Summary: Starting values from frequencies
112:
1.249 brouard 113: Revision 1.248 2016/09/07 14:10:18 brouard
114: *** empty log message ***
115:
1.248 brouard 116: Revision 1.247 2016/09/02 11:11:21 brouard
117: *** empty log message ***
118:
1.247 brouard 119: Revision 1.246 2016/09/02 08:49:22 brouard
120: *** empty log message ***
121:
1.246 brouard 122: Revision 1.245 2016/09/02 07:25:01 brouard
123: *** empty log message ***
124:
1.245 brouard 125: Revision 1.244 2016/09/02 07:17:34 brouard
126: *** empty log message ***
127:
1.244 brouard 128: Revision 1.243 2016/09/02 06:45:35 brouard
129: *** empty log message ***
130:
1.243 brouard 131: Revision 1.242 2016/08/30 15:01:20 brouard
132: Summary: Fixing a lots
133:
1.242 brouard 134: Revision 1.241 2016/08/29 17:17:25 brouard
135: Summary: gnuplot problem in Back projection to fix
136:
1.241 brouard 137: Revision 1.240 2016/08/29 07:53:18 brouard
138: Summary: Better
139:
1.240 brouard 140: Revision 1.239 2016/08/26 15:51:03 brouard
141: Summary: Improvement in Powell output in order to copy and paste
142:
143: Author:
144:
1.239 brouard 145: Revision 1.238 2016/08/26 14:23:35 brouard
146: Summary: Starting tests of 0.99
147:
1.238 brouard 148: Revision 1.237 2016/08/26 09:20:19 brouard
149: Summary: to valgrind
150:
1.237 brouard 151: Revision 1.236 2016/08/25 10:50:18 brouard
152: *** empty log message ***
153:
1.236 brouard 154: Revision 1.235 2016/08/25 06:59:23 brouard
155: *** empty log message ***
156:
1.235 brouard 157: Revision 1.234 2016/08/23 16:51:20 brouard
158: *** empty log message ***
159:
1.234 brouard 160: Revision 1.233 2016/08/23 07:40:50 brouard
161: Summary: not working
162:
1.233 brouard 163: Revision 1.232 2016/08/22 14:20:21 brouard
164: Summary: not working
165:
1.232 brouard 166: Revision 1.231 2016/08/22 07:17:15 brouard
167: Summary: not working
168:
1.231 brouard 169: Revision 1.230 2016/08/22 06:55:53 brouard
170: Summary: Not working
171:
1.230 brouard 172: Revision 1.229 2016/07/23 09:45:53 brouard
173: Summary: Completing for func too
174:
1.229 brouard 175: Revision 1.228 2016/07/22 17:45:30 brouard
176: Summary: Fixing some arrays, still debugging
177:
1.227 brouard 178: Revision 1.226 2016/07/12 18:42:34 brouard
179: Summary: temp
180:
1.226 brouard 181: Revision 1.225 2016/07/12 08:40:03 brouard
182: Summary: saving but not running
183:
1.225 brouard 184: Revision 1.224 2016/07/01 13:16:01 brouard
185: Summary: Fixes
186:
1.224 brouard 187: Revision 1.223 2016/02/19 09:23:35 brouard
188: Summary: temporary
189:
1.223 brouard 190: Revision 1.222 2016/02/17 08:14:50 brouard
191: Summary: Probably last 0.98 stable version 0.98r6
192:
1.222 brouard 193: Revision 1.221 2016/02/15 23:35:36 brouard
194: Summary: minor bug
195:
1.220 brouard 196: Revision 1.219 2016/02/15 00:48:12 brouard
197: *** empty log message ***
198:
1.219 brouard 199: Revision 1.218 2016/02/12 11:29:23 brouard
200: Summary: 0.99 Back projections
201:
1.218 brouard 202: Revision 1.217 2015/12/23 17:18:31 brouard
203: Summary: Experimental backcast
204:
1.217 brouard 205: Revision 1.216 2015/12/18 17:32:11 brouard
206: Summary: 0.98r4 Warning and status=-2
207:
208: Version 0.98r4 is now:
209: - displaying an error when status is -1, date of interview unknown and date of death known;
210: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
211: Older changes concerning s=-2, dating from 2005 have been supersed.
212:
1.216 brouard 213: Revision 1.215 2015/12/16 08:52:24 brouard
214: Summary: 0.98r4 working
215:
1.215 brouard 216: Revision 1.214 2015/12/16 06:57:54 brouard
217: Summary: temporary not working
218:
1.214 brouard 219: Revision 1.213 2015/12/11 18:22:17 brouard
220: Summary: 0.98r4
221:
1.213 brouard 222: Revision 1.212 2015/11/21 12:47:24 brouard
223: Summary: minor typo
224:
1.212 brouard 225: Revision 1.211 2015/11/21 12:41:11 brouard
226: Summary: 0.98r3 with some graph of projected cross-sectional
227:
228: Author: Nicolas Brouard
229:
1.211 brouard 230: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 231: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 232: Summary: Adding ftolpl parameter
233: Author: N Brouard
234:
235: We had difficulties to get smoothed confidence intervals. It was due
236: to the period prevalence which wasn't computed accurately. The inner
237: parameter ftolpl is now an outer parameter of the .imach parameter
238: file after estepm. If ftolpl is small 1.e-4 and estepm too,
239: computation are long.
240:
1.209 brouard 241: Revision 1.208 2015/11/17 14:31:57 brouard
242: Summary: temporary
243:
1.208 brouard 244: Revision 1.207 2015/10/27 17:36:57 brouard
245: *** empty log message ***
246:
1.207 brouard 247: Revision 1.206 2015/10/24 07:14:11 brouard
248: *** empty log message ***
249:
1.206 brouard 250: Revision 1.205 2015/10/23 15:50:53 brouard
251: Summary: 0.98r3 some clarification for graphs on likelihood contributions
252:
1.205 brouard 253: Revision 1.204 2015/10/01 16:20:26 brouard
254: Summary: Some new graphs of contribution to likelihood
255:
1.204 brouard 256: Revision 1.203 2015/09/30 17:45:14 brouard
257: Summary: looking at better estimation of the hessian
258:
259: Also a better criteria for convergence to the period prevalence And
260: therefore adding the number of years needed to converge. (The
261: prevalence in any alive state shold sum to one
262:
1.203 brouard 263: Revision 1.202 2015/09/22 19:45:16 brouard
264: Summary: Adding some overall graph on contribution to likelihood. Might change
265:
1.202 brouard 266: Revision 1.201 2015/09/15 17:34:58 brouard
267: Summary: 0.98r0
268:
269: - Some new graphs like suvival functions
270: - Some bugs fixed like model=1+age+V2.
271:
1.201 brouard 272: Revision 1.200 2015/09/09 16:53:55 brouard
273: Summary: Big bug thanks to Flavia
274:
275: Even model=1+age+V2. did not work anymore
276:
1.200 brouard 277: Revision 1.199 2015/09/07 14:09:23 brouard
278: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
279:
1.199 brouard 280: Revision 1.198 2015/09/03 07:14:39 brouard
281: Summary: 0.98q5 Flavia
282:
1.198 brouard 283: Revision 1.197 2015/09/01 18:24:39 brouard
284: *** empty log message ***
285:
1.197 brouard 286: Revision 1.196 2015/08/18 23:17:52 brouard
287: Summary: 0.98q5
288:
1.196 brouard 289: Revision 1.195 2015/08/18 16:28:39 brouard
290: Summary: Adding a hack for testing purpose
291:
292: After reading the title, ftol and model lines, if the comment line has
293: a q, starting with #q, the answer at the end of the run is quit. It
294: permits to run test files in batch with ctest. The former workaround was
295: $ echo q | imach foo.imach
296:
1.195 brouard 297: Revision 1.194 2015/08/18 13:32:00 brouard
298: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
299:
1.194 brouard 300: Revision 1.193 2015/08/04 07:17:42 brouard
301: Summary: 0.98q4
302:
1.193 brouard 303: Revision 1.192 2015/07/16 16:49:02 brouard
304: Summary: Fixing some outputs
305:
1.192 brouard 306: Revision 1.191 2015/07/14 10:00:33 brouard
307: Summary: Some fixes
308:
1.191 brouard 309: Revision 1.190 2015/05/05 08:51:13 brouard
310: Summary: Adding digits in output parameters (7 digits instead of 6)
311:
312: Fix 1+age+.
313:
1.190 brouard 314: Revision 1.189 2015/04/30 14:45:16 brouard
315: Summary: 0.98q2
316:
1.189 brouard 317: Revision 1.188 2015/04/30 08:27:53 brouard
318: *** empty log message ***
319:
1.188 brouard 320: Revision 1.187 2015/04/29 09:11:15 brouard
321: *** empty log message ***
322:
1.187 brouard 323: Revision 1.186 2015/04/23 12:01:52 brouard
324: Summary: V1*age is working now, version 0.98q1
325:
326: Some codes had been disabled in order to simplify and Vn*age was
327: working in the optimization phase, ie, giving correct MLE parameters,
328: but, as usual, outputs were not correct and program core dumped.
329:
1.186 brouard 330: Revision 1.185 2015/03/11 13:26:42 brouard
331: Summary: Inclusion of compile and links command line for Intel Compiler
332:
1.185 brouard 333: Revision 1.184 2015/03/11 11:52:39 brouard
334: Summary: Back from Windows 8. Intel Compiler
335:
1.184 brouard 336: Revision 1.183 2015/03/10 20:34:32 brouard
337: Summary: 0.98q0, trying with directest, mnbrak fixed
338:
339: We use directest instead of original Powell test; probably no
340: incidence on the results, but better justifications;
341: We fixed Numerical Recipes mnbrak routine which was wrong and gave
342: wrong results.
343:
1.183 brouard 344: Revision 1.182 2015/02/12 08:19:57 brouard
345: Summary: Trying to keep directest which seems simpler and more general
346: Author: Nicolas Brouard
347:
1.182 brouard 348: Revision 1.181 2015/02/11 23:22:24 brouard
349: Summary: Comments on Powell added
350:
351: Author:
352:
1.181 brouard 353: Revision 1.180 2015/02/11 17:33:45 brouard
354: Summary: Finishing move from main to function (hpijx and prevalence_limit)
355:
1.180 brouard 356: Revision 1.179 2015/01/04 09:57:06 brouard
357: Summary: back to OS/X
358:
1.179 brouard 359: Revision 1.178 2015/01/04 09:35:48 brouard
360: *** empty log message ***
361:
1.178 brouard 362: Revision 1.177 2015/01/03 18:40:56 brouard
363: Summary: Still testing ilc32 on OSX
364:
1.177 brouard 365: Revision 1.176 2015/01/03 16:45:04 brouard
366: *** empty log message ***
367:
1.176 brouard 368: Revision 1.175 2015/01/03 16:33:42 brouard
369: *** empty log message ***
370:
1.175 brouard 371: Revision 1.174 2015/01/03 16:15:49 brouard
372: Summary: Still in cross-compilation
373:
1.174 brouard 374: Revision 1.173 2015/01/03 12:06:26 brouard
375: Summary: trying to detect cross-compilation
376:
1.173 brouard 377: Revision 1.172 2014/12/27 12:07:47 brouard
378: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
379:
1.172 brouard 380: Revision 1.171 2014/12/23 13:26:59 brouard
381: Summary: Back from Visual C
382:
383: Still problem with utsname.h on Windows
384:
1.171 brouard 385: Revision 1.170 2014/12/23 11:17:12 brouard
386: Summary: Cleaning some \%% back to %%
387:
388: The escape was mandatory for a specific compiler (which one?), but too many warnings.
389:
1.170 brouard 390: Revision 1.169 2014/12/22 23:08:31 brouard
391: Summary: 0.98p
392:
393: Outputs some informations on compiler used, OS etc. Testing on different platforms.
394:
1.169 brouard 395: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 396: Summary: update
1.169 brouard 397:
1.168 brouard 398: Revision 1.167 2014/12/22 13:50:56 brouard
399: Summary: Testing uname and compiler version and if compiled 32 or 64
400:
401: Testing on Linux 64
402:
1.167 brouard 403: Revision 1.166 2014/12/22 11:40:47 brouard
404: *** empty log message ***
405:
1.166 brouard 406: Revision 1.165 2014/12/16 11:20:36 brouard
407: Summary: After compiling on Visual C
408:
409: * imach.c (Module): Merging 1.61 to 1.162
410:
1.165 brouard 411: Revision 1.164 2014/12/16 10:52:11 brouard
412: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
413:
414: * imach.c (Module): Merging 1.61 to 1.162
415:
1.164 brouard 416: Revision 1.163 2014/12/16 10:30:11 brouard
417: * imach.c (Module): Merging 1.61 to 1.162
418:
1.163 brouard 419: Revision 1.162 2014/09/25 11:43:39 brouard
420: Summary: temporary backup 0.99!
421:
1.162 brouard 422: Revision 1.1 2014/09/16 11:06:58 brouard
423: Summary: With some code (wrong) for nlopt
424:
425: Author:
426:
427: Revision 1.161 2014/09/15 20:41:41 brouard
428: Summary: Problem with macro SQR on Intel compiler
429:
1.161 brouard 430: Revision 1.160 2014/09/02 09:24:05 brouard
431: *** empty log message ***
432:
1.160 brouard 433: Revision 1.159 2014/09/01 10:34:10 brouard
434: Summary: WIN32
435: Author: Brouard
436:
1.159 brouard 437: Revision 1.158 2014/08/27 17:11:51 brouard
438: *** empty log message ***
439:
1.158 brouard 440: Revision 1.157 2014/08/27 16:26:55 brouard
441: Summary: Preparing windows Visual studio version
442: Author: Brouard
443:
444: In order to compile on Visual studio, time.h is now correct and time_t
445: and tm struct should be used. difftime should be used but sometimes I
446: just make the differences in raw time format (time(&now).
447: Trying to suppress #ifdef LINUX
448: Add xdg-open for __linux in order to open default browser.
449:
1.157 brouard 450: Revision 1.156 2014/08/25 20:10:10 brouard
451: *** empty log message ***
452:
1.156 brouard 453: Revision 1.155 2014/08/25 18:32:34 brouard
454: Summary: New compile, minor changes
455: Author: Brouard
456:
1.155 brouard 457: Revision 1.154 2014/06/20 17:32:08 brouard
458: Summary: Outputs now all graphs of convergence to period prevalence
459:
1.154 brouard 460: Revision 1.153 2014/06/20 16:45:46 brouard
461: Summary: If 3 live state, convergence to period prevalence on same graph
462: Author: Brouard
463:
1.153 brouard 464: Revision 1.152 2014/06/18 17:54:09 brouard
465: Summary: open browser, use gnuplot on same dir than imach if not found in the path
466:
1.152 brouard 467: Revision 1.151 2014/06/18 16:43:30 brouard
468: *** empty log message ***
469:
1.151 brouard 470: Revision 1.150 2014/06/18 16:42:35 brouard
471: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
472: Author: brouard
473:
1.150 brouard 474: Revision 1.149 2014/06/18 15:51:14 brouard
475: Summary: Some fixes in parameter files errors
476: Author: Nicolas Brouard
477:
1.149 brouard 478: Revision 1.148 2014/06/17 17:38:48 brouard
479: Summary: Nothing new
480: Author: Brouard
481:
482: Just a new packaging for OS/X version 0.98nS
483:
1.148 brouard 484: Revision 1.147 2014/06/16 10:33:11 brouard
485: *** empty log message ***
486:
1.147 brouard 487: Revision 1.146 2014/06/16 10:20:28 brouard
488: Summary: Merge
489: Author: Brouard
490:
491: Merge, before building revised version.
492:
1.146 brouard 493: Revision 1.145 2014/06/10 21:23:15 brouard
494: Summary: Debugging with valgrind
495: Author: Nicolas Brouard
496:
497: Lot of changes in order to output the results with some covariates
498: After the Edimburgh REVES conference 2014, it seems mandatory to
499: improve the code.
500: No more memory valgrind error but a lot has to be done in order to
501: continue the work of splitting the code into subroutines.
502: Also, decodemodel has been improved. Tricode is still not
503: optimal. nbcode should be improved. Documentation has been added in
504: the source code.
505:
1.144 brouard 506: Revision 1.143 2014/01/26 09:45:38 brouard
507: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
508:
509: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
510: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
511:
1.143 brouard 512: Revision 1.142 2014/01/26 03:57:36 brouard
513: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
514:
515: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
516:
1.142 brouard 517: Revision 1.141 2014/01/26 02:42:01 brouard
518: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
519:
1.141 brouard 520: Revision 1.140 2011/09/02 10:37:54 brouard
521: Summary: times.h is ok with mingw32 now.
522:
1.140 brouard 523: Revision 1.139 2010/06/14 07:50:17 brouard
524: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
525: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
526:
1.139 brouard 527: Revision 1.138 2010/04/30 18:19:40 brouard
528: *** empty log message ***
529:
1.138 brouard 530: Revision 1.137 2010/04/29 18:11:38 brouard
531: (Module): Checking covariates for more complex models
532: than V1+V2. A lot of change to be done. Unstable.
533:
1.137 brouard 534: Revision 1.136 2010/04/26 20:30:53 brouard
535: (Module): merging some libgsl code. Fixing computation
536: of likelione (using inter/intrapolation if mle = 0) in order to
537: get same likelihood as if mle=1.
538: Some cleaning of code and comments added.
539:
1.136 brouard 540: Revision 1.135 2009/10/29 15:33:14 brouard
541: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
542:
1.135 brouard 543: Revision 1.134 2009/10/29 13:18:53 brouard
544: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
545:
1.134 brouard 546: Revision 1.133 2009/07/06 10:21:25 brouard
547: just nforces
548:
1.133 brouard 549: Revision 1.132 2009/07/06 08:22:05 brouard
550: Many tings
551:
1.132 brouard 552: Revision 1.131 2009/06/20 16:22:47 brouard
553: Some dimensions resccaled
554:
1.131 brouard 555: Revision 1.130 2009/05/26 06:44:34 brouard
556: (Module): Max Covariate is now set to 20 instead of 8. A
557: lot of cleaning with variables initialized to 0. Trying to make
558: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
559:
1.130 brouard 560: Revision 1.129 2007/08/31 13:49:27 lievre
561: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
562:
1.129 lievre 563: Revision 1.128 2006/06/30 13:02:05 brouard
564: (Module): Clarifications on computing e.j
565:
1.128 brouard 566: Revision 1.127 2006/04/28 18:11:50 brouard
567: (Module): Yes the sum of survivors was wrong since
568: imach-114 because nhstepm was no more computed in the age
569: loop. Now we define nhstepma in the age loop.
570: (Module): In order to speed up (in case of numerous covariates) we
571: compute health expectancies (without variances) in a first step
572: and then all the health expectancies with variances or standard
573: deviation (needs data from the Hessian matrices) which slows the
574: computation.
575: In the future we should be able to stop the program is only health
576: expectancies and graph are needed without standard deviations.
577:
1.127 brouard 578: Revision 1.126 2006/04/28 17:23:28 brouard
579: (Module): Yes the sum of survivors was wrong since
580: imach-114 because nhstepm was no more computed in the age
581: loop. Now we define nhstepma in the age loop.
582: Version 0.98h
583:
1.126 brouard 584: Revision 1.125 2006/04/04 15:20:31 lievre
585: Errors in calculation of health expectancies. Age was not initialized.
586: Forecasting file added.
587:
588: Revision 1.124 2006/03/22 17:13:53 lievre
589: Parameters are printed with %lf instead of %f (more numbers after the comma).
590: The log-likelihood is printed in the log file
591:
592: Revision 1.123 2006/03/20 10:52:43 brouard
593: * imach.c (Module): <title> changed, corresponds to .htm file
594: name. <head> headers where missing.
595:
596: * imach.c (Module): Weights can have a decimal point as for
597: English (a comma might work with a correct LC_NUMERIC environment,
598: otherwise the weight is truncated).
599: Modification of warning when the covariates values are not 0 or
600: 1.
601: Version 0.98g
602:
603: Revision 1.122 2006/03/20 09:45:41 brouard
604: (Module): Weights can have a decimal point as for
605: English (a comma might work with a correct LC_NUMERIC environment,
606: otherwise the weight is truncated).
607: Modification of warning when the covariates values are not 0 or
608: 1.
609: Version 0.98g
610:
611: Revision 1.121 2006/03/16 17:45:01 lievre
612: * imach.c (Module): Comments concerning covariates added
613:
614: * imach.c (Module): refinements in the computation of lli if
615: status=-2 in order to have more reliable computation if stepm is
616: not 1 month. Version 0.98f
617:
618: Revision 1.120 2006/03/16 15:10:38 lievre
619: (Module): refinements in the computation of lli if
620: status=-2 in order to have more reliable computation if stepm is
621: not 1 month. Version 0.98f
622:
623: Revision 1.119 2006/03/15 17:42:26 brouard
624: (Module): Bug if status = -2, the loglikelihood was
625: computed as likelihood omitting the logarithm. Version O.98e
626:
627: Revision 1.118 2006/03/14 18:20:07 brouard
628: (Module): varevsij Comments added explaining the second
629: table of variances if popbased=1 .
630: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
631: (Module): Function pstamp added
632: (Module): Version 0.98d
633:
634: Revision 1.117 2006/03/14 17:16:22 brouard
635: (Module): varevsij Comments added explaining the second
636: table of variances if popbased=1 .
637: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
638: (Module): Function pstamp added
639: (Module): Version 0.98d
640:
641: Revision 1.116 2006/03/06 10:29:27 brouard
642: (Module): Variance-covariance wrong links and
643: varian-covariance of ej. is needed (Saito).
644:
645: Revision 1.115 2006/02/27 12:17:45 brouard
646: (Module): One freematrix added in mlikeli! 0.98c
647:
648: Revision 1.114 2006/02/26 12:57:58 brouard
649: (Module): Some improvements in processing parameter
650: filename with strsep.
651:
652: Revision 1.113 2006/02/24 14:20:24 brouard
653: (Module): Memory leaks checks with valgrind and:
654: datafile was not closed, some imatrix were not freed and on matrix
655: allocation too.
656:
657: Revision 1.112 2006/01/30 09:55:26 brouard
658: (Module): Back to gnuplot.exe instead of wgnuplot.exe
659:
660: Revision 1.111 2006/01/25 20:38:18 brouard
661: (Module): Lots of cleaning and bugs added (Gompertz)
662: (Module): Comments can be added in data file. Missing date values
663: can be a simple dot '.'.
664:
665: Revision 1.110 2006/01/25 00:51:50 brouard
666: (Module): Lots of cleaning and bugs added (Gompertz)
667:
668: Revision 1.109 2006/01/24 19:37:15 brouard
669: (Module): Comments (lines starting with a #) are allowed in data.
670:
671: Revision 1.108 2006/01/19 18:05:42 lievre
672: Gnuplot problem appeared...
673: To be fixed
674:
675: Revision 1.107 2006/01/19 16:20:37 brouard
676: Test existence of gnuplot in imach path
677:
678: Revision 1.106 2006/01/19 13:24:36 brouard
679: Some cleaning and links added in html output
680:
681: Revision 1.105 2006/01/05 20:23:19 lievre
682: *** empty log message ***
683:
684: Revision 1.104 2005/09/30 16:11:43 lievre
685: (Module): sump fixed, loop imx fixed, and simplifications.
686: (Module): If the status is missing at the last wave but we know
687: that the person is alive, then we can code his/her status as -2
688: (instead of missing=-1 in earlier versions) and his/her
689: contributions to the likelihood is 1 - Prob of dying from last
690: health status (= 1-p13= p11+p12 in the easiest case of somebody in
691: the healthy state at last known wave). Version is 0.98
692:
693: Revision 1.103 2005/09/30 15:54:49 lievre
694: (Module): sump fixed, loop imx fixed, and simplifications.
695:
696: Revision 1.102 2004/09/15 17:31:30 brouard
697: Add the possibility to read data file including tab characters.
698:
699: Revision 1.101 2004/09/15 10:38:38 brouard
700: Fix on curr_time
701:
702: Revision 1.100 2004/07/12 18:29:06 brouard
703: Add version for Mac OS X. Just define UNIX in Makefile
704:
705: Revision 1.99 2004/06/05 08:57:40 brouard
706: *** empty log message ***
707:
708: Revision 1.98 2004/05/16 15:05:56 brouard
709: New version 0.97 . First attempt to estimate force of mortality
710: directly from the data i.e. without the need of knowing the health
711: state at each age, but using a Gompertz model: log u =a + b*age .
712: This is the basic analysis of mortality and should be done before any
713: other analysis, in order to test if the mortality estimated from the
714: cross-longitudinal survey is different from the mortality estimated
715: from other sources like vital statistic data.
716:
717: The same imach parameter file can be used but the option for mle should be -3.
718:
1.133 brouard 719: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 720: former routines in order to include the new code within the former code.
721:
722: The output is very simple: only an estimate of the intercept and of
723: the slope with 95% confident intervals.
724:
725: Current limitations:
726: A) Even if you enter covariates, i.e. with the
727: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
728: B) There is no computation of Life Expectancy nor Life Table.
729:
730: Revision 1.97 2004/02/20 13:25:42 lievre
731: Version 0.96d. Population forecasting command line is (temporarily)
732: suppressed.
733:
734: Revision 1.96 2003/07/15 15:38:55 brouard
735: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
736: rewritten within the same printf. Workaround: many printfs.
737:
738: Revision 1.95 2003/07/08 07:54:34 brouard
739: * imach.c (Repository):
740: (Repository): Using imachwizard code to output a more meaningful covariance
741: matrix (cov(a12,c31) instead of numbers.
742:
743: Revision 1.94 2003/06/27 13:00:02 brouard
744: Just cleaning
745:
746: Revision 1.93 2003/06/25 16:33:55 brouard
747: (Module): On windows (cygwin) function asctime_r doesn't
748: exist so I changed back to asctime which exists.
749: (Module): Version 0.96b
750:
751: Revision 1.92 2003/06/25 16:30:45 brouard
752: (Module): On windows (cygwin) function asctime_r doesn't
753: exist so I changed back to asctime which exists.
754:
755: Revision 1.91 2003/06/25 15:30:29 brouard
756: * imach.c (Repository): Duplicated warning errors corrected.
757: (Repository): Elapsed time after each iteration is now output. It
758: helps to forecast when convergence will be reached. Elapsed time
759: is stamped in powell. We created a new html file for the graphs
760: concerning matrix of covariance. It has extension -cov.htm.
761:
762: Revision 1.90 2003/06/24 12:34:15 brouard
763: (Module): Some bugs corrected for windows. Also, when
764: mle=-1 a template is output in file "or"mypar.txt with the design
765: of the covariance matrix to be input.
766:
767: Revision 1.89 2003/06/24 12:30:52 brouard
768: (Module): Some bugs corrected for windows. Also, when
769: mle=-1 a template is output in file "or"mypar.txt with the design
770: of the covariance matrix to be input.
771:
772: Revision 1.88 2003/06/23 17:54:56 brouard
773: * 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.
774:
775: Revision 1.87 2003/06/18 12:26:01 brouard
776: Version 0.96
777:
778: Revision 1.86 2003/06/17 20:04:08 brouard
779: (Module): Change position of html and gnuplot routines and added
780: routine fileappend.
781:
782: Revision 1.85 2003/06/17 13:12:43 brouard
783: * imach.c (Repository): Check when date of death was earlier that
784: current date of interview. It may happen when the death was just
785: prior to the death. In this case, dh was negative and likelihood
786: was wrong (infinity). We still send an "Error" but patch by
787: assuming that the date of death was just one stepm after the
788: interview.
789: (Repository): Because some people have very long ID (first column)
790: we changed int to long in num[] and we added a new lvector for
791: memory allocation. But we also truncated to 8 characters (left
792: truncation)
793: (Repository): No more line truncation errors.
794:
795: Revision 1.84 2003/06/13 21:44:43 brouard
796: * imach.c (Repository): Replace "freqsummary" at a correct
797: place. It differs from routine "prevalence" which may be called
798: many times. Probs is memory consuming and must be used with
799: parcimony.
800: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
801:
802: Revision 1.83 2003/06/10 13:39:11 lievre
803: *** empty log message ***
804:
805: Revision 1.82 2003/06/05 15:57:20 brouard
806: Add log in imach.c and fullversion number is now printed.
807:
808: */
809: /*
810: Interpolated Markov Chain
811:
812: Short summary of the programme:
813:
1.227 brouard 814: This program computes Healthy Life Expectancies or State-specific
815: (if states aren't health statuses) Expectancies from
816: cross-longitudinal data. Cross-longitudinal data consist in:
817:
818: -1- a first survey ("cross") where individuals from different ages
819: are interviewed on their health status or degree of disability (in
820: the case of a health survey which is our main interest)
821:
822: -2- at least a second wave of interviews ("longitudinal") which
823: measure each change (if any) in individual health status. Health
824: expectancies are computed from the time spent in each health state
825: according to a model. More health states you consider, more time is
826: necessary to reach the Maximum Likelihood of the parameters involved
827: in the model. The simplest model is the multinomial logistic model
828: where pij is the probability to be observed in state j at the second
829: wave conditional to be observed in state i at the first
830: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
831: etc , where 'age' is age and 'sex' is a covariate. If you want to
832: have a more complex model than "constant and age", you should modify
833: the program where the markup *Covariates have to be included here
834: again* invites you to do it. More covariates you add, slower the
1.126 brouard 835: convergence.
836:
837: The advantage of this computer programme, compared to a simple
838: multinomial logistic model, is clear when the delay between waves is not
839: identical for each individual. Also, if a individual missed an
840: intermediate interview, the information is lost, but taken into
841: account using an interpolation or extrapolation.
842:
843: hPijx is the probability to be observed in state i at age x+h
844: conditional to the observed state i at age x. The delay 'h' can be
845: split into an exact number (nh*stepm) of unobserved intermediate
846: states. This elementary transition (by month, quarter,
847: semester or year) is modelled as a multinomial logistic. The hPx
848: matrix is simply the matrix product of nh*stepm elementary matrices
849: and the contribution of each individual to the likelihood is simply
850: hPijx.
851:
852: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 853: of the life expectancies. It also computes the period (stable) prevalence.
854:
855: Back prevalence and projections:
1.227 brouard 856:
857: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
858: double agemaxpar, double ftolpl, int *ncvyearp, double
859: dateprev1,double dateprev2, int firstpass, int lastpass, int
860: mobilavproj)
861:
862: Computes the back prevalence limit for any combination of
863: covariate values k at any age between ageminpar and agemaxpar and
864: returns it in **bprlim. In the loops,
865:
866: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
867: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
868:
869: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 870: Computes for any combination of covariates k and any age between bage and fage
871: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
872: oldm=oldms;savm=savms;
1.227 brouard 873:
1.267 brouard 874: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 875: Computes the transition matrix starting at age 'age' over
876: 'nhstepm*hstepm*stepm' months (i.e. until
877: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 878: nhstepm*hstepm matrices.
879:
880: Returns p3mat[i][j][h] after calling
881: p3mat[i][j][h]=matprod2(newm,
882: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
883: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
884: oldm);
1.226 brouard 885:
886: Important routines
887:
888: - func (or funcone), computes logit (pij) distinguishing
889: o fixed variables (single or product dummies or quantitative);
890: o varying variables by:
891: (1) wave (single, product dummies, quantitative),
892: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
893: % fixed dummy (treated) or quantitative (not done because time-consuming);
894: % varying dummy (not done) or quantitative (not done);
895: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
896: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
897: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
898: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
899: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 900:
1.226 brouard 901:
902:
1.133 brouard 903: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
904: Institut national d'études démographiques, Paris.
1.126 brouard 905: This software have been partly granted by Euro-REVES, a concerted action
906: from the European Union.
907: It is copyrighted identically to a GNU software product, ie programme and
908: software can be distributed freely for non commercial use. Latest version
909: can be accessed at http://euroreves.ined.fr/imach .
910:
911: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
912: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
913:
914: **********************************************************************/
915: /*
916: main
917: read parameterfile
918: read datafile
919: concatwav
920: freqsummary
921: if (mle >= 1)
922: mlikeli
923: print results files
924: if mle==1
925: computes hessian
926: read end of parameter file: agemin, agemax, bage, fage, estepm
927: begin-prev-date,...
928: open gnuplot file
929: open html file
1.145 brouard 930: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
931: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
932: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
933: freexexit2 possible for memory heap.
934:
935: h Pij x | pij_nom ficrestpij
936: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
937: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
938: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
939:
940: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
941: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
942: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
943: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
944: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
945:
1.126 brouard 946: forecasting if prevfcast==1 prevforecast call prevalence()
947: health expectancies
948: Variance-covariance of DFLE
949: prevalence()
950: movingaverage()
951: varevsij()
952: if popbased==1 varevsij(,popbased)
953: total life expectancies
954: Variance of period (stable) prevalence
955: end
956: */
957:
1.187 brouard 958: /* #define DEBUG */
959: /* #define DEBUGBRENT */
1.203 brouard 960: /* #define DEBUGLINMIN */
961: /* #define DEBUGHESS */
962: #define DEBUGHESSIJ
1.224 brouard 963: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 964: #define POWELL /* Instead of NLOPT */
1.224 brouard 965: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 966: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
967: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 968:
969: #include <math.h>
970: #include <stdio.h>
971: #include <stdlib.h>
972: #include <string.h>
1.226 brouard 973: #include <ctype.h>
1.159 brouard 974:
975: #ifdef _WIN32
976: #include <io.h>
1.172 brouard 977: #include <windows.h>
978: #include <tchar.h>
1.159 brouard 979: #else
1.126 brouard 980: #include <unistd.h>
1.159 brouard 981: #endif
1.126 brouard 982:
983: #include <limits.h>
984: #include <sys/types.h>
1.171 brouard 985:
986: #if defined(__GNUC__)
987: #include <sys/utsname.h> /* Doesn't work on Windows */
988: #endif
989:
1.126 brouard 990: #include <sys/stat.h>
991: #include <errno.h>
1.159 brouard 992: /* extern int errno; */
1.126 brouard 993:
1.157 brouard 994: /* #ifdef LINUX */
995: /* #include <time.h> */
996: /* #include "timeval.h" */
997: /* #else */
998: /* #include <sys/time.h> */
999: /* #endif */
1000:
1.126 brouard 1001: #include <time.h>
1002:
1.136 brouard 1003: #ifdef GSL
1004: #include <gsl/gsl_errno.h>
1005: #include <gsl/gsl_multimin.h>
1006: #endif
1007:
1.167 brouard 1008:
1.162 brouard 1009: #ifdef NLOPT
1010: #include <nlopt.h>
1011: typedef struct {
1012: double (* function)(double [] );
1013: } myfunc_data ;
1014: #endif
1015:
1.126 brouard 1016: /* #include <libintl.h> */
1017: /* #define _(String) gettext (String) */
1018:
1.251 brouard 1019: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1020:
1021: #define GNUPLOTPROGRAM "gnuplot"
1022: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1023: #define FILENAMELENGTH 132
1024:
1025: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1026: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1027:
1.144 brouard 1028: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1029: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1030:
1031: #define NINTERVMAX 8
1.144 brouard 1032: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1033: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1034: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 1035: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1036: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1037: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.126 brouard 1038: #define MAXN 20000
1.144 brouard 1039: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1040: /* #define AGESUP 130 */
1041: #define AGESUP 150
1.268 brouard 1042: #define AGEINF 0
1.218 brouard 1043: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1044: #define AGEBASE 40
1.194 brouard 1045: #define AGEOVERFLOW 1.e20
1.164 brouard 1046: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1047: #ifdef _WIN32
1048: #define DIRSEPARATOR '\\'
1049: #define CHARSEPARATOR "\\"
1050: #define ODIRSEPARATOR '/'
1051: #else
1.126 brouard 1052: #define DIRSEPARATOR '/'
1053: #define CHARSEPARATOR "/"
1054: #define ODIRSEPARATOR '\\'
1055: #endif
1056:
1.284 ! brouard 1057: /* $Id: imach.c,v 1.283 2018/04/19 14:49:16 brouard Exp $ */
1.126 brouard 1058: /* $State: Exp $ */
1.196 brouard 1059: #include "version.h"
1060: char version[]=__IMACH_VERSION__;
1.283 brouard 1061: 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";
1.284 ! brouard 1062: char fullversion[]="$Revision: 1.283 $ $Date: 2018/04/19 14:49:16 $";
1.126 brouard 1063: char strstart[80];
1064: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1065: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1066: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1067: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1068: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1069: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1070: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1071: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1072: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1073: int cptcovprodnoage=0; /**< Number of covariate products without age */
1074: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1075: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1076: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1077: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1078: int nsd=0; /**< Total number of single dummy variables (output) */
1079: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1080: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1081: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1082: int ntveff=0; /**< ntveff number of effective time varying variables */
1083: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1084: int cptcov=0; /* Working variable */
1.218 brouard 1085: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 1086: int npar=NPARMAX;
1087: int nlstate=2; /* Number of live states */
1088: int ndeath=1; /* Number of dead states */
1.130 brouard 1089: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1090: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1091: int popbased=0;
1092:
1093: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1094: int maxwav=0; /* Maxim number of waves */
1095: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1096: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1097: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1098: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1099: int mle=1, weightopt=0;
1.126 brouard 1100: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1101: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1102: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1103: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1104: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1105: int selected(int kvar); /* Is covariate kvar selected for printing results */
1106:
1.130 brouard 1107: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1108: double **matprod2(); /* test */
1.126 brouard 1109: double **oldm, **newm, **savm; /* Working pointers to matrices */
1110: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1111: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1112:
1.136 brouard 1113: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1114: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1115: FILE *ficlog, *ficrespow;
1.130 brouard 1116: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1117: double fretone; /* Only one call to likelihood */
1.130 brouard 1118: long ipmx=0; /* Number of contributions */
1.126 brouard 1119: double sw; /* Sum of weights */
1120: char filerespow[FILENAMELENGTH];
1121: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1122: FILE *ficresilk;
1123: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1124: FILE *ficresprobmorprev;
1125: FILE *fichtm, *fichtmcov; /* Html File */
1126: FILE *ficreseij;
1127: char filerese[FILENAMELENGTH];
1128: FILE *ficresstdeij;
1129: char fileresstde[FILENAMELENGTH];
1130: FILE *ficrescveij;
1131: char filerescve[FILENAMELENGTH];
1132: FILE *ficresvij;
1133: char fileresv[FILENAMELENGTH];
1.269 brouard 1134:
1.126 brouard 1135: char title[MAXLINE];
1.234 brouard 1136: char model[MAXLINE]; /**< The model line */
1.217 brouard 1137: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1138: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1139: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1140: char command[FILENAMELENGTH];
1141: int outcmd=0;
1142:
1.217 brouard 1143: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1144: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1145: char filelog[FILENAMELENGTH]; /* Log file */
1146: char filerest[FILENAMELENGTH];
1147: char fileregp[FILENAMELENGTH];
1148: char popfile[FILENAMELENGTH];
1149:
1150: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1151:
1.157 brouard 1152: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1153: /* struct timezone tzp; */
1154: /* extern int gettimeofday(); */
1155: struct tm tml, *gmtime(), *localtime();
1156:
1157: extern time_t time();
1158:
1159: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1160: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1161: struct tm tm;
1162:
1.126 brouard 1163: char strcurr[80], strfor[80];
1164:
1165: char *endptr;
1166: long lval;
1167: double dval;
1168:
1169: #define NR_END 1
1170: #define FREE_ARG char*
1171: #define FTOL 1.0e-10
1172:
1173: #define NRANSI
1.240 brouard 1174: #define ITMAX 200
1175: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1176:
1177: #define TOL 2.0e-4
1178:
1179: #define CGOLD 0.3819660
1180: #define ZEPS 1.0e-10
1181: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1182:
1183: #define GOLD 1.618034
1184: #define GLIMIT 100.0
1185: #define TINY 1.0e-20
1186:
1187: static double maxarg1,maxarg2;
1188: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1189: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1190:
1191: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1192: #define rint(a) floor(a+0.5)
1.166 brouard 1193: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1194: #define mytinydouble 1.0e-16
1.166 brouard 1195: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1196: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1197: /* static double dsqrarg; */
1198: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1199: static double sqrarg;
1200: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1201: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1202: int agegomp= AGEGOMP;
1203:
1204: int imx;
1205: int stepm=1;
1206: /* Stepm, step in month: minimum step interpolation*/
1207:
1208: int estepm;
1209: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1210:
1211: int m,nb;
1212: long *num;
1.197 brouard 1213: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1214: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1215: covariate for which somebody answered excluding
1216: undefined. Usually 2: 0 and 1. */
1217: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1218: covariate for which somebody answered including
1219: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1220: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1221: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1222: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1223: double *ageexmed,*agecens;
1224: double dateintmean=0;
1225:
1226: double *weight;
1227: int **s; /* Status */
1.141 brouard 1228: double *agedc;
1.145 brouard 1229: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1230: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1231: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1232: double **coqvar; /* Fixed quantitative covariate nqv */
1233: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1234: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1235: double idx;
1236: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1237: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1238: /*k 1 2 3 4 5 6 7 8 9 */
1239: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1240: /* Tndvar[k] 1 2 3 4 5 */
1241: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1242: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1243: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1244: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1245: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1246: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1247: /* Tprod[i]=k 4 7 */
1248: /* Tage[i]=k 5 8 */
1249: /* */
1250: /* Type */
1251: /* V 1 2 3 4 5 */
1252: /* F F V V V */
1253: /* D Q D D Q */
1254: /* */
1255: int *TvarsD;
1256: int *TvarsDind;
1257: int *TvarsQ;
1258: int *TvarsQind;
1259:
1.235 brouard 1260: #define MAXRESULTLINES 10
1261: int nresult=0;
1.258 brouard 1262: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1263: int TKresult[MAXRESULTLINES];
1.237 brouard 1264: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1265: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1266: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1267: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1268: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1269: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1270:
1.234 brouard 1271: /* 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 1272: 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 */
1273: 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 */
1274: 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 */
1275: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1276: 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 */
1277: 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 1278: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1279: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1280: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1281: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1282: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1283: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1284: 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 */
1285: 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 */
1286:
1.230 brouard 1287: int *Tvarsel; /**< Selected covariates for output */
1288: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1289: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1290: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1291: 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 1292: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1293: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1294: int *Tage;
1.227 brouard 1295: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1296: 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 1297: 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*/
1298: 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 1299: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1300: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1301: int **Tvard;
1302: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1303: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1304: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1305: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1306: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1307: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1308: double *lsurv, *lpop, *tpop;
1309:
1.231 brouard 1310: #define FD 1; /* Fixed dummy covariate */
1311: #define FQ 2; /* Fixed quantitative covariate */
1312: #define FP 3; /* Fixed product covariate */
1313: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1314: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1315: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1316: #define VD 10; /* Varying dummy covariate */
1317: #define VQ 11; /* Varying quantitative covariate */
1318: #define VP 12; /* Varying product covariate */
1319: #define VPDD 13; /* Varying product dummy*dummy covariate */
1320: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1321: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1322: #define APFD 16; /* Age product * fixed dummy covariate */
1323: #define APFQ 17; /* Age product * fixed quantitative covariate */
1324: #define APVD 18; /* Age product * varying dummy covariate */
1325: #define APVQ 19; /* Age product * varying quantitative covariate */
1326:
1327: #define FTYPE 1; /* Fixed covariate */
1328: #define VTYPE 2; /* Varying covariate (loop in wave) */
1329: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1330:
1331: struct kmodel{
1332: int maintype; /* main type */
1333: int subtype; /* subtype */
1334: };
1335: struct kmodel modell[NCOVMAX];
1336:
1.143 brouard 1337: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1338: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1339:
1340: /**************** split *************************/
1341: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1342: {
1343: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1344: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1345: */
1346: char *ss; /* pointer */
1.186 brouard 1347: int l1=0, l2=0; /* length counters */
1.126 brouard 1348:
1349: l1 = strlen(path ); /* length of path */
1350: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1351: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1352: if ( ss == NULL ) { /* no directory, so determine current directory */
1353: strcpy( name, path ); /* we got the fullname name because no directory */
1354: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1355: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1356: /* get current working directory */
1357: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1358: #ifdef WIN32
1359: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1360: #else
1361: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1362: #endif
1.126 brouard 1363: return( GLOCK_ERROR_GETCWD );
1364: }
1365: /* got dirc from getcwd*/
1366: printf(" DIRC = %s \n",dirc);
1.205 brouard 1367: } else { /* strip directory from path */
1.126 brouard 1368: ss++; /* after this, the filename */
1369: l2 = strlen( ss ); /* length of filename */
1370: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1371: strcpy( name, ss ); /* save file name */
1372: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1373: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1374: printf(" DIRC2 = %s \n",dirc);
1375: }
1376: /* We add a separator at the end of dirc if not exists */
1377: l1 = strlen( dirc ); /* length of directory */
1378: if( dirc[l1-1] != DIRSEPARATOR ){
1379: dirc[l1] = DIRSEPARATOR;
1380: dirc[l1+1] = 0;
1381: printf(" DIRC3 = %s \n",dirc);
1382: }
1383: ss = strrchr( name, '.' ); /* find last / */
1384: if (ss >0){
1385: ss++;
1386: strcpy(ext,ss); /* save extension */
1387: l1= strlen( name);
1388: l2= strlen(ss)+1;
1389: strncpy( finame, name, l1-l2);
1390: finame[l1-l2]= 0;
1391: }
1392:
1393: return( 0 ); /* we're done */
1394: }
1395:
1396:
1397: /******************************************/
1398:
1399: void replace_back_to_slash(char *s, char*t)
1400: {
1401: int i;
1402: int lg=0;
1403: i=0;
1404: lg=strlen(t);
1405: for(i=0; i<= lg; i++) {
1406: (s[i] = t[i]);
1407: if (t[i]== '\\') s[i]='/';
1408: }
1409: }
1410:
1.132 brouard 1411: char *trimbb(char *out, char *in)
1.137 brouard 1412: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1413: char *s;
1414: s=out;
1415: while (*in != '\0'){
1.137 brouard 1416: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1417: in++;
1418: }
1419: *out++ = *in++;
1420: }
1421: *out='\0';
1422: return s;
1423: }
1424:
1.187 brouard 1425: /* char *substrchaine(char *out, char *in, char *chain) */
1426: /* { */
1427: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1428: /* char *s, *t; */
1429: /* t=in;s=out; */
1430: /* while ((*in != *chain) && (*in != '\0')){ */
1431: /* *out++ = *in++; */
1432: /* } */
1433:
1434: /* /\* *in matches *chain *\/ */
1435: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1436: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1437: /* } */
1438: /* in--; chain--; */
1439: /* while ( (*in != '\0')){ */
1440: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1441: /* *out++ = *in++; */
1442: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1443: /* } */
1444: /* *out='\0'; */
1445: /* out=s; */
1446: /* return out; */
1447: /* } */
1448: char *substrchaine(char *out, char *in, char *chain)
1449: {
1450: /* Substract chain 'chain' from 'in', return and output 'out' */
1451: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1452:
1453: char *strloc;
1454:
1455: strcpy (out, in);
1456: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1457: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1458: if(strloc != NULL){
1459: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1460: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1461: /* strcpy (strloc, strloc +strlen(chain));*/
1462: }
1463: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1464: return out;
1465: }
1466:
1467:
1.145 brouard 1468: char *cutl(char *blocc, char *alocc, char *in, char occ)
1469: {
1.187 brouard 1470: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1471: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1472: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1473: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1474: */
1.160 brouard 1475: char *s, *t;
1.145 brouard 1476: t=in;s=in;
1477: while ((*in != occ) && (*in != '\0')){
1478: *alocc++ = *in++;
1479: }
1480: if( *in == occ){
1481: *(alocc)='\0';
1482: s=++in;
1483: }
1484:
1485: if (s == t) {/* occ not found */
1486: *(alocc-(in-s))='\0';
1487: in=s;
1488: }
1489: while ( *in != '\0'){
1490: *blocc++ = *in++;
1491: }
1492:
1493: *blocc='\0';
1494: return t;
1495: }
1.137 brouard 1496: char *cutv(char *blocc, char *alocc, char *in, char occ)
1497: {
1.187 brouard 1498: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1499: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1500: gives blocc="abcdef2ghi" and alocc="j".
1501: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1502: */
1503: char *s, *t;
1504: t=in;s=in;
1505: while (*in != '\0'){
1506: while( *in == occ){
1507: *blocc++ = *in++;
1508: s=in;
1509: }
1510: *blocc++ = *in++;
1511: }
1512: if (s == t) /* occ not found */
1513: *(blocc-(in-s))='\0';
1514: else
1515: *(blocc-(in-s)-1)='\0';
1516: in=s;
1517: while ( *in != '\0'){
1518: *alocc++ = *in++;
1519: }
1520:
1521: *alocc='\0';
1522: return s;
1523: }
1524:
1.126 brouard 1525: int nbocc(char *s, char occ)
1526: {
1527: int i,j=0;
1528: int lg=20;
1529: i=0;
1530: lg=strlen(s);
1531: for(i=0; i<= lg; i++) {
1.234 brouard 1532: if (s[i] == occ ) j++;
1.126 brouard 1533: }
1534: return j;
1535: }
1536:
1.137 brouard 1537: /* void cutv(char *u,char *v, char*t, char occ) */
1538: /* { */
1539: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1540: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1541: /* gives u="abcdef2ghi" and v="j" *\/ */
1542: /* int i,lg,j,p=0; */
1543: /* i=0; */
1544: /* lg=strlen(t); */
1545: /* for(j=0; j<=lg-1; j++) { */
1546: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1547: /* } */
1.126 brouard 1548:
1.137 brouard 1549: /* for(j=0; j<p; j++) { */
1550: /* (u[j] = t[j]); */
1551: /* } */
1552: /* u[p]='\0'; */
1.126 brouard 1553:
1.137 brouard 1554: /* for(j=0; j<= lg; j++) { */
1555: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1556: /* } */
1557: /* } */
1.126 brouard 1558:
1.160 brouard 1559: #ifdef _WIN32
1560: char * strsep(char **pp, const char *delim)
1561: {
1562: char *p, *q;
1563:
1564: if ((p = *pp) == NULL)
1565: return 0;
1566: if ((q = strpbrk (p, delim)) != NULL)
1567: {
1568: *pp = q + 1;
1569: *q = '\0';
1570: }
1571: else
1572: *pp = 0;
1573: return p;
1574: }
1575: #endif
1576:
1.126 brouard 1577: /********************** nrerror ********************/
1578:
1579: void nrerror(char error_text[])
1580: {
1581: fprintf(stderr,"ERREUR ...\n");
1582: fprintf(stderr,"%s\n",error_text);
1583: exit(EXIT_FAILURE);
1584: }
1585: /*********************** vector *******************/
1586: double *vector(int nl, int nh)
1587: {
1588: double *v;
1589: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1590: if (!v) nrerror("allocation failure in vector");
1591: return v-nl+NR_END;
1592: }
1593:
1594: /************************ free vector ******************/
1595: void free_vector(double*v, int nl, int nh)
1596: {
1597: free((FREE_ARG)(v+nl-NR_END));
1598: }
1599:
1600: /************************ivector *******************************/
1601: int *ivector(long nl,long nh)
1602: {
1603: int *v;
1604: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1605: if (!v) nrerror("allocation failure in ivector");
1606: return v-nl+NR_END;
1607: }
1608:
1609: /******************free ivector **************************/
1610: void free_ivector(int *v, long nl, long nh)
1611: {
1612: free((FREE_ARG)(v+nl-NR_END));
1613: }
1614:
1615: /************************lvector *******************************/
1616: long *lvector(long nl,long nh)
1617: {
1618: long *v;
1619: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1620: if (!v) nrerror("allocation failure in ivector");
1621: return v-nl+NR_END;
1622: }
1623:
1624: /******************free lvector **************************/
1625: void free_lvector(long *v, long nl, long nh)
1626: {
1627: free((FREE_ARG)(v+nl-NR_END));
1628: }
1629:
1630: /******************* imatrix *******************************/
1631: int **imatrix(long nrl, long nrh, long ncl, long nch)
1632: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1633: {
1634: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1635: int **m;
1636:
1637: /* allocate pointers to rows */
1638: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1639: if (!m) nrerror("allocation failure 1 in matrix()");
1640: m += NR_END;
1641: m -= nrl;
1642:
1643:
1644: /* allocate rows and set pointers to them */
1645: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1646: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1647: m[nrl] += NR_END;
1648: m[nrl] -= ncl;
1649:
1650: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1651:
1652: /* return pointer to array of pointers to rows */
1653: return m;
1654: }
1655:
1656: /****************** free_imatrix *************************/
1657: void free_imatrix(m,nrl,nrh,ncl,nch)
1658: int **m;
1659: long nch,ncl,nrh,nrl;
1660: /* free an int matrix allocated by imatrix() */
1661: {
1662: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1663: free((FREE_ARG) (m+nrl-NR_END));
1664: }
1665:
1666: /******************* matrix *******************************/
1667: double **matrix(long nrl, long nrh, long ncl, long nch)
1668: {
1669: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1670: double **m;
1671:
1672: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1673: if (!m) nrerror("allocation failure 1 in matrix()");
1674: m += NR_END;
1675: m -= nrl;
1676:
1677: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1678: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1679: m[nrl] += NR_END;
1680: m[nrl] -= ncl;
1681:
1682: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1683: return m;
1.145 brouard 1684: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1685: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1686: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1687: */
1688: }
1689:
1690: /*************************free matrix ************************/
1691: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1692: {
1693: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1694: free((FREE_ARG)(m+nrl-NR_END));
1695: }
1696:
1697: /******************* ma3x *******************************/
1698: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1699: {
1700: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1701: double ***m;
1702:
1703: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1704: if (!m) nrerror("allocation failure 1 in matrix()");
1705: m += NR_END;
1706: m -= nrl;
1707:
1708: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1709: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1710: m[nrl] += NR_END;
1711: m[nrl] -= ncl;
1712:
1713: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1714:
1715: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1716: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1717: m[nrl][ncl] += NR_END;
1718: m[nrl][ncl] -= nll;
1719: for (j=ncl+1; j<=nch; j++)
1720: m[nrl][j]=m[nrl][j-1]+nlay;
1721:
1722: for (i=nrl+1; i<=nrh; i++) {
1723: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1724: for (j=ncl+1; j<=nch; j++)
1725: m[i][j]=m[i][j-1]+nlay;
1726: }
1727: return m;
1728: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1729: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1730: */
1731: }
1732:
1733: /*************************free ma3x ************************/
1734: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1735: {
1736: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1737: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1738: free((FREE_ARG)(m+nrl-NR_END));
1739: }
1740:
1741: /*************** function subdirf ***********/
1742: char *subdirf(char fileres[])
1743: {
1744: /* Caution optionfilefiname is hidden */
1745: strcpy(tmpout,optionfilefiname);
1746: strcat(tmpout,"/"); /* Add to the right */
1747: strcat(tmpout,fileres);
1748: return tmpout;
1749: }
1750:
1751: /*************** function subdirf2 ***********/
1752: char *subdirf2(char fileres[], char *preop)
1753: {
1754:
1755: /* Caution optionfilefiname is hidden */
1756: strcpy(tmpout,optionfilefiname);
1757: strcat(tmpout,"/");
1758: strcat(tmpout,preop);
1759: strcat(tmpout,fileres);
1760: return tmpout;
1761: }
1762:
1763: /*************** function subdirf3 ***********/
1764: char *subdirf3(char fileres[], char *preop, char *preop2)
1765: {
1766:
1767: /* Caution optionfilefiname is hidden */
1768: strcpy(tmpout,optionfilefiname);
1769: strcat(tmpout,"/");
1770: strcat(tmpout,preop);
1771: strcat(tmpout,preop2);
1772: strcat(tmpout,fileres);
1773: return tmpout;
1774: }
1.213 brouard 1775:
1776: /*************** function subdirfext ***********/
1777: char *subdirfext(char fileres[], char *preop, char *postop)
1778: {
1779:
1780: strcpy(tmpout,preop);
1781: strcat(tmpout,fileres);
1782: strcat(tmpout,postop);
1783: return tmpout;
1784: }
1.126 brouard 1785:
1.213 brouard 1786: /*************** function subdirfext3 ***********/
1787: char *subdirfext3(char fileres[], char *preop, char *postop)
1788: {
1789:
1790: /* Caution optionfilefiname is hidden */
1791: strcpy(tmpout,optionfilefiname);
1792: strcat(tmpout,"/");
1793: strcat(tmpout,preop);
1794: strcat(tmpout,fileres);
1795: strcat(tmpout,postop);
1796: return tmpout;
1797: }
1798:
1.162 brouard 1799: char *asc_diff_time(long time_sec, char ascdiff[])
1800: {
1801: long sec_left, days, hours, minutes;
1802: days = (time_sec) / (60*60*24);
1803: sec_left = (time_sec) % (60*60*24);
1804: hours = (sec_left) / (60*60) ;
1805: sec_left = (sec_left) %(60*60);
1806: minutes = (sec_left) /60;
1807: sec_left = (sec_left) % (60);
1808: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1809: return ascdiff;
1810: }
1811:
1.126 brouard 1812: /***************** f1dim *************************/
1813: extern int ncom;
1814: extern double *pcom,*xicom;
1815: extern double (*nrfunc)(double []);
1816:
1817: double f1dim(double x)
1818: {
1819: int j;
1820: double f;
1821: double *xt;
1822:
1823: xt=vector(1,ncom);
1824: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1825: f=(*nrfunc)(xt);
1826: free_vector(xt,1,ncom);
1827: return f;
1828: }
1829:
1830: /*****************brent *************************/
1831: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1832: {
1833: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1834: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1835: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1836: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1837: * returned function value.
1838: */
1.126 brouard 1839: int iter;
1840: double a,b,d,etemp;
1.159 brouard 1841: double fu=0,fv,fw,fx;
1.164 brouard 1842: double ftemp=0.;
1.126 brouard 1843: double p,q,r,tol1,tol2,u,v,w,x,xm;
1844: double e=0.0;
1845:
1846: a=(ax < cx ? ax : cx);
1847: b=(ax > cx ? ax : cx);
1848: x=w=v=bx;
1849: fw=fv=fx=(*f)(x);
1850: for (iter=1;iter<=ITMAX;iter++) {
1851: xm=0.5*(a+b);
1852: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1853: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1854: printf(".");fflush(stdout);
1855: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1856: #ifdef DEBUGBRENT
1.126 brouard 1857: 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);
1858: 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);
1859: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1860: #endif
1861: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1862: *xmin=x;
1863: return fx;
1864: }
1865: ftemp=fu;
1866: if (fabs(e) > tol1) {
1867: r=(x-w)*(fx-fv);
1868: q=(x-v)*(fx-fw);
1869: p=(x-v)*q-(x-w)*r;
1870: q=2.0*(q-r);
1871: if (q > 0.0) p = -p;
1872: q=fabs(q);
1873: etemp=e;
1874: e=d;
1875: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1876: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1877: else {
1.224 brouard 1878: d=p/q;
1879: u=x+d;
1880: if (u-a < tol2 || b-u < tol2)
1881: d=SIGN(tol1,xm-x);
1.126 brouard 1882: }
1883: } else {
1884: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1885: }
1886: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1887: fu=(*f)(u);
1888: if (fu <= fx) {
1889: if (u >= x) a=x; else b=x;
1890: SHFT(v,w,x,u)
1.183 brouard 1891: SHFT(fv,fw,fx,fu)
1892: } else {
1893: if (u < x) a=u; else b=u;
1894: if (fu <= fw || w == x) {
1.224 brouard 1895: v=w;
1896: w=u;
1897: fv=fw;
1898: fw=fu;
1.183 brouard 1899: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1900: v=u;
1901: fv=fu;
1.183 brouard 1902: }
1903: }
1.126 brouard 1904: }
1905: nrerror("Too many iterations in brent");
1906: *xmin=x;
1907: return fx;
1908: }
1909:
1910: /****************** mnbrak ***********************/
1911:
1912: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1913: double (*func)(double))
1.183 brouard 1914: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1915: the downhill direction (defined by the function as evaluated at the initial points) and returns
1916: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1917: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1918: */
1.126 brouard 1919: double ulim,u,r,q, dum;
1920: double fu;
1.187 brouard 1921:
1922: double scale=10.;
1923: int iterscale=0;
1924:
1925: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1926: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1927:
1928:
1929: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1930: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1931: /* *bx = *ax - (*ax - *bx)/scale; */
1932: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1933: /* } */
1934:
1.126 brouard 1935: if (*fb > *fa) {
1936: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1937: SHFT(dum,*fb,*fa,dum)
1938: }
1.126 brouard 1939: *cx=(*bx)+GOLD*(*bx-*ax);
1940: *fc=(*func)(*cx);
1.183 brouard 1941: #ifdef DEBUG
1.224 brouard 1942: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1943: 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 1944: #endif
1.224 brouard 1945: 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 1946: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1947: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1948: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1949: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1950: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1951: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1952: fu=(*func)(u);
1.163 brouard 1953: #ifdef DEBUG
1954: /* f(x)=A(x-u)**2+f(u) */
1955: double A, fparabu;
1956: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1957: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 1958: 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);
1959: 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 1960: /* And thus,it can be that fu > *fc even if fparabu < *fc */
1961: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
1962: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
1963: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 1964: #endif
1.184 brouard 1965: #ifdef MNBRAKORIGINAL
1.183 brouard 1966: #else
1.191 brouard 1967: /* if (fu > *fc) { */
1968: /* #ifdef DEBUG */
1969: /* printf("mnbrak4 fu > fc \n"); */
1970: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
1971: /* #endif */
1972: /* /\* 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 *\\/ *\/ */
1973: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
1974: /* dum=u; /\* Shifting c and u *\/ */
1975: /* u = *cx; */
1976: /* *cx = dum; */
1977: /* dum = fu; */
1978: /* fu = *fc; */
1979: /* *fc =dum; */
1980: /* } else { /\* end *\/ */
1981: /* #ifdef DEBUG */
1982: /* printf("mnbrak3 fu < fc \n"); */
1983: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
1984: /* #endif */
1985: /* dum=u; /\* Shifting c and u *\/ */
1986: /* u = *cx; */
1987: /* *cx = dum; */
1988: /* dum = fu; */
1989: /* fu = *fc; */
1990: /* *fc =dum; */
1991: /* } */
1.224 brouard 1992: #ifdef DEBUGMNBRAK
1993: double A, fparabu;
1994: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1995: fparabu= *fa - A*(*ax-u)*(*ax-u);
1996: 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);
1997: 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 1998: #endif
1.191 brouard 1999: dum=u; /* Shifting c and u */
2000: u = *cx;
2001: *cx = dum;
2002: dum = fu;
2003: fu = *fc;
2004: *fc =dum;
1.183 brouard 2005: #endif
1.162 brouard 2006: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2007: #ifdef DEBUG
1.224 brouard 2008: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2009: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2010: #endif
1.126 brouard 2011: fu=(*func)(u);
2012: if (fu < *fc) {
1.183 brouard 2013: #ifdef DEBUG
1.224 brouard 2014: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2015: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2016: #endif
2017: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2018: SHFT(*fb,*fc,fu,(*func)(u))
2019: #ifdef DEBUG
2020: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2021: #endif
2022: }
1.162 brouard 2023: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2024: #ifdef DEBUG
1.224 brouard 2025: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2026: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2027: #endif
1.126 brouard 2028: u=ulim;
2029: fu=(*func)(u);
1.183 brouard 2030: } else { /* u could be left to b (if r > q parabola has a maximum) */
2031: #ifdef DEBUG
1.224 brouard 2032: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2033: 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 2034: #endif
1.126 brouard 2035: u=(*cx)+GOLD*(*cx-*bx);
2036: fu=(*func)(u);
1.224 brouard 2037: #ifdef DEBUG
2038: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2039: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2040: #endif
1.183 brouard 2041: } /* end tests */
1.126 brouard 2042: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2043: SHFT(*fa,*fb,*fc,fu)
2044: #ifdef DEBUG
1.224 brouard 2045: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2046: 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 2047: #endif
2048: } /* 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 2049: }
2050:
2051: /*************** linmin ************************/
1.162 brouard 2052: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2053: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2054: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2055: the value of func at the returned location p . This is actually all accomplished by calling the
2056: routines mnbrak and brent .*/
1.126 brouard 2057: int ncom;
2058: double *pcom,*xicom;
2059: double (*nrfunc)(double []);
2060:
1.224 brouard 2061: #ifdef LINMINORIGINAL
1.126 brouard 2062: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2063: #else
2064: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2065: #endif
1.126 brouard 2066: {
2067: double brent(double ax, double bx, double cx,
2068: double (*f)(double), double tol, double *xmin);
2069: double f1dim(double x);
2070: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2071: double *fc, double (*func)(double));
2072: int j;
2073: double xx,xmin,bx,ax;
2074: double fx,fb,fa;
1.187 brouard 2075:
1.203 brouard 2076: #ifdef LINMINORIGINAL
2077: #else
2078: double scale=10., axs, xxs; /* Scale added for infinity */
2079: #endif
2080:
1.126 brouard 2081: ncom=n;
2082: pcom=vector(1,n);
2083: xicom=vector(1,n);
2084: nrfunc=func;
2085: for (j=1;j<=n;j++) {
2086: pcom[j]=p[j];
1.202 brouard 2087: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2088: }
1.187 brouard 2089:
1.203 brouard 2090: #ifdef LINMINORIGINAL
2091: xx=1.;
2092: #else
2093: axs=0.0;
2094: xxs=1.;
2095: do{
2096: xx= xxs;
2097: #endif
1.187 brouard 2098: ax=0.;
2099: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2100: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2101: /* 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)) */
2102: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2103: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2104: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2105: /* 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 2106: #ifdef LINMINORIGINAL
2107: #else
2108: if (fx != fx){
1.224 brouard 2109: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2110: printf("|");
2111: fprintf(ficlog,"|");
1.203 brouard 2112: #ifdef DEBUGLINMIN
1.224 brouard 2113: 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 2114: #endif
2115: }
1.224 brouard 2116: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2117: #endif
2118:
1.191 brouard 2119: #ifdef DEBUGLINMIN
2120: 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 2121: 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 2122: #endif
1.224 brouard 2123: #ifdef LINMINORIGINAL
2124: #else
2125: if(fb == fx){ /* Flat function in the direction */
2126: xmin=xx;
2127: *flat=1;
2128: }else{
2129: *flat=0;
2130: #endif
2131: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2132: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2133: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2134: /* fmin = f(p[j] + xmin * xi[j]) */
2135: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2136: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2137: #ifdef DEBUG
1.224 brouard 2138: 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);
2139: 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);
2140: #endif
2141: #ifdef LINMINORIGINAL
2142: #else
2143: }
1.126 brouard 2144: #endif
1.191 brouard 2145: #ifdef DEBUGLINMIN
2146: printf("linmin end ");
1.202 brouard 2147: fprintf(ficlog,"linmin end ");
1.191 brouard 2148: #endif
1.126 brouard 2149: for (j=1;j<=n;j++) {
1.203 brouard 2150: #ifdef LINMINORIGINAL
2151: xi[j] *= xmin;
2152: #else
2153: #ifdef DEBUGLINMIN
2154: if(xxs <1.0)
2155: printf(" before xi[%d]=%12.8f", j,xi[j]);
2156: #endif
2157: 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) */
2158: #ifdef DEBUGLINMIN
2159: if(xxs <1.0)
2160: 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 );
2161: #endif
2162: #endif
1.187 brouard 2163: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2164: }
1.191 brouard 2165: #ifdef DEBUGLINMIN
1.203 brouard 2166: printf("\n");
1.191 brouard 2167: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2168: 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 2169: for (j=1;j<=n;j++) {
1.202 brouard 2170: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2171: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2172: if(j % ncovmodel == 0){
1.191 brouard 2173: printf("\n");
1.202 brouard 2174: fprintf(ficlog,"\n");
2175: }
1.191 brouard 2176: }
1.203 brouard 2177: #else
1.191 brouard 2178: #endif
1.126 brouard 2179: free_vector(xicom,1,n);
2180: free_vector(pcom,1,n);
2181: }
2182:
2183:
2184: /*************** powell ************************/
1.162 brouard 2185: /*
2186: Minimization of a function func of n variables. Input consists of an initial starting point
2187: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2188: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2189: such that failure to decrease by more than this amount on one iteration signals doneness. On
2190: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2191: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2192: */
1.224 brouard 2193: #ifdef LINMINORIGINAL
2194: #else
2195: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2196: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2197: #endif
1.126 brouard 2198: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2199: double (*func)(double []))
2200: {
1.224 brouard 2201: #ifdef LINMINORIGINAL
2202: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2203: double (*func)(double []));
1.224 brouard 2204: #else
1.241 brouard 2205: void linmin(double p[], double xi[], int n, double *fret,
2206: double (*func)(double []),int *flat);
1.224 brouard 2207: #endif
1.239 brouard 2208: int i,ibig,j,jk,k;
1.126 brouard 2209: double del,t,*pt,*ptt,*xit;
1.181 brouard 2210: double directest;
1.126 brouard 2211: double fp,fptt;
2212: double *xits;
2213: int niterf, itmp;
1.224 brouard 2214: #ifdef LINMINORIGINAL
2215: #else
2216:
2217: flatdir=ivector(1,n);
2218: for (j=1;j<=n;j++) flatdir[j]=0;
2219: #endif
1.126 brouard 2220:
2221: pt=vector(1,n);
2222: ptt=vector(1,n);
2223: xit=vector(1,n);
2224: xits=vector(1,n);
2225: *fret=(*func)(p);
2226: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2227: rcurr_time = time(NULL);
1.126 brouard 2228: for (*iter=1;;++(*iter)) {
1.187 brouard 2229: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2230: ibig=0;
2231: del=0.0;
1.157 brouard 2232: rlast_time=rcurr_time;
2233: /* (void) gettimeofday(&curr_time,&tzp); */
2234: rcurr_time = time(NULL);
2235: curr_time = *localtime(&rcurr_time);
2236: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2237: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2238: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2239: for (i=1;i<=n;i++) {
1.126 brouard 2240: fprintf(ficrespow," %.12lf", p[i]);
2241: }
1.239 brouard 2242: fprintf(ficrespow,"\n");fflush(ficrespow);
2243: printf("\n#model= 1 + age ");
2244: fprintf(ficlog,"\n#model= 1 + age ");
2245: if(nagesqr==1){
1.241 brouard 2246: printf(" + age*age ");
2247: fprintf(ficlog," + age*age ");
1.239 brouard 2248: }
2249: for(j=1;j <=ncovmodel-2;j++){
2250: if(Typevar[j]==0) {
2251: printf(" + V%d ",Tvar[j]);
2252: fprintf(ficlog," + V%d ",Tvar[j]);
2253: }else if(Typevar[j]==1) {
2254: printf(" + V%d*age ",Tvar[j]);
2255: fprintf(ficlog," + V%d*age ",Tvar[j]);
2256: }else if(Typevar[j]==2) {
2257: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2258: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2259: }
2260: }
1.126 brouard 2261: printf("\n");
1.239 brouard 2262: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2263: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2264: fprintf(ficlog,"\n");
1.239 brouard 2265: for(i=1,jk=1; i <=nlstate; i++){
2266: for(k=1; k <=(nlstate+ndeath); k++){
2267: if (k != i) {
2268: printf("%d%d ",i,k);
2269: fprintf(ficlog,"%d%d ",i,k);
2270: for(j=1; j <=ncovmodel; j++){
2271: printf("%12.7f ",p[jk]);
2272: fprintf(ficlog,"%12.7f ",p[jk]);
2273: jk++;
2274: }
2275: printf("\n");
2276: fprintf(ficlog,"\n");
2277: }
2278: }
2279: }
1.241 brouard 2280: if(*iter <=3 && *iter >1){
1.157 brouard 2281: tml = *localtime(&rcurr_time);
2282: strcpy(strcurr,asctime(&tml));
2283: rforecast_time=rcurr_time;
1.126 brouard 2284: itmp = strlen(strcurr);
2285: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2286: strcurr[itmp-1]='\0';
1.162 brouard 2287: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2288: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2289: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2290: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2291: forecast_time = *localtime(&rforecast_time);
2292: strcpy(strfor,asctime(&forecast_time));
2293: itmp = strlen(strfor);
2294: if(strfor[itmp-1]=='\n')
2295: strfor[itmp-1]='\0';
2296: 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);
2297: 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 2298: }
2299: }
1.187 brouard 2300: for (i=1;i<=n;i++) { /* For each direction i */
2301: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2302: fptt=(*fret);
2303: #ifdef DEBUG
1.203 brouard 2304: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2305: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2306: #endif
1.203 brouard 2307: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2308: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2309: #ifdef LINMINORIGINAL
1.188 brouard 2310: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2311: #else
2312: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2313: flatdir[i]=flat; /* Function is vanishing in that direction i */
2314: #endif
2315: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2316: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2317: /* because that direction will be replaced unless the gain del is small */
2318: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2319: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2320: /* with the new direction. */
2321: del=fabs(fptt-(*fret));
2322: ibig=i;
1.126 brouard 2323: }
2324: #ifdef DEBUG
2325: printf("%d %.12e",i,(*fret));
2326: fprintf(ficlog,"%d %.12e",i,(*fret));
2327: for (j=1;j<=n;j++) {
1.224 brouard 2328: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2329: printf(" x(%d)=%.12e",j,xit[j]);
2330: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2331: }
2332: for(j=1;j<=n;j++) {
1.225 brouard 2333: printf(" p(%d)=%.12e",j,p[j]);
2334: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2335: }
2336: printf("\n");
2337: fprintf(ficlog,"\n");
2338: #endif
1.187 brouard 2339: } /* end loop on each direction i */
2340: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2341: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2342: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2343: for(j=1;j<=n;j++) {
1.225 brouard 2344: if(flatdir[j] >0){
2345: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2346: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2347: }
2348: /* printf("\n"); */
2349: /* fprintf(ficlog,"\n"); */
2350: }
1.243 brouard 2351: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2352: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2353: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2354: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2355: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2356: /* decreased of more than 3.84 */
2357: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2358: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2359: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2360:
1.188 brouard 2361: /* Starting the program with initial values given by a former maximization will simply change */
2362: /* the scales of the directions and the directions, because the are reset to canonical directions */
2363: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2364: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2365: #ifdef DEBUG
2366: int k[2],l;
2367: k[0]=1;
2368: k[1]=-1;
2369: printf("Max: %.12e",(*func)(p));
2370: fprintf(ficlog,"Max: %.12e",(*func)(p));
2371: for (j=1;j<=n;j++) {
2372: printf(" %.12e",p[j]);
2373: fprintf(ficlog," %.12e",p[j]);
2374: }
2375: printf("\n");
2376: fprintf(ficlog,"\n");
2377: for(l=0;l<=1;l++) {
2378: for (j=1;j<=n;j++) {
2379: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2380: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2381: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2382: }
2383: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2384: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2385: }
2386: #endif
2387:
1.224 brouard 2388: #ifdef LINMINORIGINAL
2389: #else
2390: free_ivector(flatdir,1,n);
2391: #endif
1.126 brouard 2392: free_vector(xit,1,n);
2393: free_vector(xits,1,n);
2394: free_vector(ptt,1,n);
2395: free_vector(pt,1,n);
2396: return;
1.192 brouard 2397: } /* enough precision */
1.240 brouard 2398: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2399: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2400: ptt[j]=2.0*p[j]-pt[j];
2401: xit[j]=p[j]-pt[j];
2402: pt[j]=p[j];
2403: }
1.181 brouard 2404: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2405: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2406: if (*iter <=4) {
1.225 brouard 2407: #else
2408: #endif
1.224 brouard 2409: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2410: #else
1.161 brouard 2411: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2412: #endif
1.162 brouard 2413: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2414: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2415: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2416: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2417: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2418: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2419: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2420: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2421: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2422: /* Even if f3 <f1, directest can be negative and t >0 */
2423: /* mu² and del² are equal when f3=f1 */
2424: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2425: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2426: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2427: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2428: #ifdef NRCORIGINAL
2429: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2430: #else
2431: 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 2432: t= t- del*SQR(fp-fptt);
1.183 brouard 2433: #endif
1.202 brouard 2434: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2435: #ifdef DEBUG
1.181 brouard 2436: 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);
2437: 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 2438: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2439: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2440: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2441: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2442: 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);
2443: 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);
2444: #endif
1.183 brouard 2445: #ifdef POWELLORIGINAL
2446: if (t < 0.0) { /* Then we use it for new direction */
2447: #else
1.182 brouard 2448: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2449: 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 2450: 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 2451: 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 2452: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2453: }
1.181 brouard 2454: if (directest < 0.0) { /* Then we use it for new direction */
2455: #endif
1.191 brouard 2456: #ifdef DEBUGLINMIN
1.234 brouard 2457: printf("Before linmin in direction P%d-P0\n",n);
2458: for (j=1;j<=n;j++) {
2459: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2460: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2461: if(j % ncovmodel == 0){
2462: printf("\n");
2463: fprintf(ficlog,"\n");
2464: }
2465: }
1.224 brouard 2466: #endif
2467: #ifdef LINMINORIGINAL
1.234 brouard 2468: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2469: #else
1.234 brouard 2470: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2471: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2472: #endif
1.234 brouard 2473:
1.191 brouard 2474: #ifdef DEBUGLINMIN
1.234 brouard 2475: for (j=1;j<=n;j++) {
2476: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2477: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2478: if(j % ncovmodel == 0){
2479: printf("\n");
2480: fprintf(ficlog,"\n");
2481: }
2482: }
1.224 brouard 2483: #endif
1.234 brouard 2484: for (j=1;j<=n;j++) {
2485: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2486: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2487: }
1.224 brouard 2488: #ifdef LINMINORIGINAL
2489: #else
1.234 brouard 2490: for (j=1, flatd=0;j<=n;j++) {
2491: if(flatdir[j]>0)
2492: flatd++;
2493: }
2494: if(flatd >0){
1.255 brouard 2495: printf("%d flat directions: ",flatd);
2496: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2497: for (j=1;j<=n;j++) {
2498: if(flatdir[j]>0){
2499: printf("%d ",j);
2500: fprintf(ficlog,"%d ",j);
2501: }
2502: }
2503: printf("\n");
2504: fprintf(ficlog,"\n");
2505: }
1.191 brouard 2506: #endif
1.234 brouard 2507: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2508: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2509:
1.126 brouard 2510: #ifdef DEBUG
1.234 brouard 2511: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2512: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2513: for(j=1;j<=n;j++){
2514: printf(" %lf",xit[j]);
2515: fprintf(ficlog," %lf",xit[j]);
2516: }
2517: printf("\n");
2518: fprintf(ficlog,"\n");
1.126 brouard 2519: #endif
1.192 brouard 2520: } /* end of t or directest negative */
1.224 brouard 2521: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2522: #else
1.234 brouard 2523: } /* end if (fptt < fp) */
1.192 brouard 2524: #endif
1.225 brouard 2525: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2526: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2527: #else
1.224 brouard 2528: #endif
1.234 brouard 2529: } /* loop iteration */
1.126 brouard 2530: }
1.234 brouard 2531:
1.126 brouard 2532: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2533:
1.235 brouard 2534: 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 2535: {
1.279 brouard 2536: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2537: * (and selected quantitative values in nres)
2538: * by left multiplying the unit
2539: * matrix by transitions matrix until convergence is reached with precision ftolpl
2540: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2541: * Wx is row vector: population in state 1, population in state 2, population dead
2542: * or prevalence in state 1, prevalence in state 2, 0
2543: * newm is the matrix after multiplications, its rows are identical at a factor.
2544: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2545: * Output is prlim.
2546: * Initial matrix pimij
2547: */
1.206 brouard 2548: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2549: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2550: /* 0, 0 , 1} */
2551: /*
2552: * and after some iteration: */
2553: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2554: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2555: /* 0, 0 , 1} */
2556: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2557: /* {0.51571254859325999, 0.4842874514067399, */
2558: /* 0.51326036147820708, 0.48673963852179264} */
2559: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2560:
1.126 brouard 2561: int i, ii,j,k;
1.209 brouard 2562: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2563: /* double **matprod2(); */ /* test */
1.218 brouard 2564: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2565: double **newm;
1.209 brouard 2566: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2567: int ncvloop=0;
1.169 brouard 2568:
1.209 brouard 2569: min=vector(1,nlstate);
2570: max=vector(1,nlstate);
2571: meandiff=vector(1,nlstate);
2572:
1.218 brouard 2573: /* Starting with matrix unity */
1.126 brouard 2574: for (ii=1;ii<=nlstate+ndeath;ii++)
2575: for (j=1;j<=nlstate+ndeath;j++){
2576: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2577: }
1.169 brouard 2578:
2579: cov[1]=1.;
2580:
2581: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2582: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2583: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2584: ncvloop++;
1.126 brouard 2585: newm=savm;
2586: /* Covariates have to be included here again */
1.138 brouard 2587: cov[2]=agefin;
1.187 brouard 2588: if(nagesqr==1)
2589: cov[3]= agefin*agefin;;
1.234 brouard 2590: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2591: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2592: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2593: /* 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 2594: }
2595: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2596: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2597: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2598: /* 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 2599: }
1.237 brouard 2600: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2601: if(Dummy[Tvar[Tage[k]]]){
2602: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2603: } else{
1.235 brouard 2604: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2605: }
1.235 brouard 2606: /* 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 2607: }
1.237 brouard 2608: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2609: /* 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 2610: if(Dummy[Tvard[k][1]==0]){
2611: if(Dummy[Tvard[k][2]==0]){
2612: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2613: }else{
2614: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2615: }
2616: }else{
2617: if(Dummy[Tvard[k][2]==0]){
2618: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2619: }else{
2620: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2621: }
2622: }
1.234 brouard 2623: }
1.138 brouard 2624: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2625: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2626: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2627: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2628: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2629: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2630: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2631:
1.126 brouard 2632: savm=oldm;
2633: oldm=newm;
1.209 brouard 2634:
2635: for(j=1; j<=nlstate; j++){
2636: max[j]=0.;
2637: min[j]=1.;
2638: }
2639: for(i=1;i<=nlstate;i++){
2640: sumnew=0;
2641: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2642: for(j=1; j<=nlstate; j++){
2643: prlim[i][j]= newm[i][j]/(1-sumnew);
2644: max[j]=FMAX(max[j],prlim[i][j]);
2645: min[j]=FMIN(min[j],prlim[i][j]);
2646: }
2647: }
2648:
1.126 brouard 2649: maxmax=0.;
1.209 brouard 2650: for(j=1; j<=nlstate; j++){
2651: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2652: maxmax=FMAX(maxmax,meandiff[j]);
2653: /* 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 2654: } /* j loop */
1.203 brouard 2655: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2656: /* 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 2657: if(maxmax < ftolpl){
1.209 brouard 2658: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2659: free_vector(min,1,nlstate);
2660: free_vector(max,1,nlstate);
2661: free_vector(meandiff,1,nlstate);
1.126 brouard 2662: return prlim;
2663: }
1.169 brouard 2664: } /* age loop */
1.208 brouard 2665: /* After some age loop it doesn't converge */
1.209 brouard 2666: printf("Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.0f years. Try to lower 'ftolpl'. \n\
1.208 brouard 2667: Earliest 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);
1.209 brouard 2668: /* 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); */
2669: free_vector(min,1,nlstate);
2670: free_vector(max,1,nlstate);
2671: free_vector(meandiff,1,nlstate);
1.208 brouard 2672:
1.169 brouard 2673: return prlim; /* should not reach here */
1.126 brouard 2674: }
2675:
1.217 brouard 2676:
2677: /**** Back Prevalence limit (stable or period prevalence) ****************/
2678:
1.218 brouard 2679: /* 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) */
2680: /* 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 2681: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2682: {
1.264 brouard 2683: /* 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 2684: matrix by transitions matrix until convergence is reached with precision ftolpl */
2685: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2686: /* Wx is row vector: population in state 1, population in state 2, population dead */
2687: /* or prevalence in state 1, prevalence in state 2, 0 */
2688: /* newm is the matrix after multiplications, its rows are identical at a factor */
2689: /* Initial matrix pimij */
2690: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2691: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2692: /* 0, 0 , 1} */
2693: /*
2694: * and after some iteration: */
2695: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2696: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2697: /* 0, 0 , 1} */
2698: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2699: /* {0.51571254859325999, 0.4842874514067399, */
2700: /* 0.51326036147820708, 0.48673963852179264} */
2701: /* If we start from prlim again, prlim tends to a constant matrix */
2702:
2703: int i, ii,j,k;
1.247 brouard 2704: int first=0;
1.217 brouard 2705: double *min, *max, *meandiff, maxmax,sumnew=0.;
2706: /* double **matprod2(); */ /* test */
2707: double **out, cov[NCOVMAX+1], **bmij();
2708: double **newm;
1.218 brouard 2709: double **dnewm, **doldm, **dsavm; /* for use */
2710: double **oldm, **savm; /* for use */
2711:
1.217 brouard 2712: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2713: int ncvloop=0;
2714:
2715: min=vector(1,nlstate);
2716: max=vector(1,nlstate);
2717: meandiff=vector(1,nlstate);
2718:
1.266 brouard 2719: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2720: oldm=oldms; savm=savms;
2721:
2722: /* Starting with matrix unity */
2723: for (ii=1;ii<=nlstate+ndeath;ii++)
2724: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2725: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2726: }
2727:
2728: cov[1]=1.;
2729:
2730: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2731: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2732: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2733: for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2734: ncvloop++;
1.218 brouard 2735: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2736: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2737: /* Covariates have to be included here again */
2738: cov[2]=agefin;
2739: if(nagesqr==1)
2740: cov[3]= agefin*agefin;;
1.242 brouard 2741: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2742: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2743: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2744: /* 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 2745: }
2746: /* for (k=1; k<=cptcovn;k++) { */
2747: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2748: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2749: /* /\* 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])]); *\/ */
2750: /* } */
2751: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2752: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2753: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2754: /* 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]); */
2755: }
2756: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2757: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2758: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2759: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2760: for (k=1; k<=cptcovage;k++){ /* For product with age */
2761: if(Dummy[Tvar[Tage[k]]]){
2762: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2763: } else{
2764: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2765: }
2766: /* 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]); */
2767: }
2768: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2769: /* 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]); */
2770: if(Dummy[Tvard[k][1]==0]){
2771: if(Dummy[Tvard[k][2]==0]){
2772: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2773: }else{
2774: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2775: }
2776: }else{
2777: if(Dummy[Tvard[k][2]==0]){
2778: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2779: }else{
2780: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2781: }
2782: }
1.217 brouard 2783: }
2784:
2785: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2786: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2787: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2788: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2789: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2790: /* ij should be linked to the correct index of cov */
2791: /* age and covariate values ij are in 'cov', but we need to pass
2792: * ij for the observed prevalence at age and status and covariate
2793: * number: prevacurrent[(int)agefin][ii][ij]
2794: */
2795: /* 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 *\/ */
2796: /* 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 *\/ */
2797: 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 2798: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2799: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2800: /* for(i=1; i<=nlstate+ndeath; i++) { */
2801: /* printf("%d newm= ",i); */
2802: /* for(j=1;j<=nlstate+ndeath;j++) { */
2803: /* printf("%f ",newm[i][j]); */
2804: /* } */
2805: /* printf("oldm * "); */
2806: /* for(j=1;j<=nlstate+ndeath;j++) { */
2807: /* printf("%f ",oldm[i][j]); */
2808: /* } */
1.268 brouard 2809: /* printf(" bmmij "); */
1.266 brouard 2810: /* for(j=1;j<=nlstate+ndeath;j++) { */
2811: /* printf("%f ",pmmij[i][j]); */
2812: /* } */
2813: /* printf("\n"); */
2814: /* } */
2815: /* } */
1.217 brouard 2816: savm=oldm;
2817: oldm=newm;
1.266 brouard 2818:
1.217 brouard 2819: for(j=1; j<=nlstate; j++){
2820: max[j]=0.;
2821: min[j]=1.;
2822: }
2823: for(j=1; j<=nlstate; j++){
2824: for(i=1;i<=nlstate;i++){
1.234 brouard 2825: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2826: bprlim[i][j]= newm[i][j];
2827: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2828: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2829: }
2830: }
1.218 brouard 2831:
1.217 brouard 2832: maxmax=0.;
2833: for(i=1; i<=nlstate; i++){
2834: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2835: maxmax=FMAX(maxmax,meandiff[i]);
2836: /* 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 2837: } /* i loop */
1.217 brouard 2838: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 2839: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2840: if(maxmax < ftolpl){
1.220 brouard 2841: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2842: free_vector(min,1,nlstate);
2843: free_vector(max,1,nlstate);
2844: free_vector(meandiff,1,nlstate);
2845: return bprlim;
2846: }
2847: } /* age loop */
2848: /* After some age loop it doesn't converge */
1.247 brouard 2849: if(first){
2850: first=1;
2851: 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\
2852: 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);
2853: }
2854: 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 2855: 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);
2856: /* 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); */
2857: free_vector(min,1,nlstate);
2858: free_vector(max,1,nlstate);
2859: free_vector(meandiff,1,nlstate);
2860:
2861: return bprlim; /* should not reach here */
2862: }
2863:
1.126 brouard 2864: /*************** transition probabilities ***************/
2865:
2866: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2867: {
1.138 brouard 2868: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2869: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2870: model to the ncovmodel covariates (including constant and age).
2871: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2872: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2873: ncth covariate in the global vector x is given by the formula:
2874: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2875: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2876: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2877: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 2878: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 2879: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 2880: Sum on j ps[i][j] should equal to 1.
1.138 brouard 2881: */
2882: double s1, lnpijopii;
1.126 brouard 2883: /*double t34;*/
1.164 brouard 2884: int i,j, nc, ii, jj;
1.126 brouard 2885:
1.223 brouard 2886: for(i=1; i<= nlstate; i++){
2887: for(j=1; j<i;j++){
2888: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2889: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2890: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2891: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2892: }
2893: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2894: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2895: }
2896: for(j=i+1; j<=nlstate+ndeath;j++){
2897: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2898: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2899: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2900: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2901: }
2902: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2903: }
2904: }
1.218 brouard 2905:
1.223 brouard 2906: for(i=1; i<= nlstate; i++){
2907: s1=0;
2908: for(j=1; j<i; j++){
2909: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2910: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2911: }
2912: for(j=i+1; j<=nlstate+ndeath; j++){
2913: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2914: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2915: }
2916: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2917: ps[i][i]=1./(s1+1.);
2918: /* Computing other pijs */
2919: for(j=1; j<i; j++)
2920: ps[i][j]= exp(ps[i][j])*ps[i][i];
2921: for(j=i+1; j<=nlstate+ndeath; j++)
2922: ps[i][j]= exp(ps[i][j])*ps[i][i];
2923: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2924: } /* end i */
1.218 brouard 2925:
1.223 brouard 2926: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2927: for(jj=1; jj<= nlstate+ndeath; jj++){
2928: ps[ii][jj]=0;
2929: ps[ii][ii]=1;
2930: }
2931: }
1.218 brouard 2932:
2933:
1.223 brouard 2934: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2935: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2936: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2937: /* } */
2938: /* printf("\n "); */
2939: /* } */
2940: /* printf("\n ");printf("%lf ",cov[2]);*/
2941: /*
2942: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2943: goto end;*/
1.266 brouard 2944: return ps; /* Pointer is unchanged since its call */
1.126 brouard 2945: }
2946:
1.218 brouard 2947: /*************** backward transition probabilities ***************/
2948:
2949: /* 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 ) */
2950: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2951: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
2952: {
1.266 brouard 2953: /* Computes the backward probability at age agefin and covariate combination ij. In fact cov is already filled and x too.
2954: * 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 2955: */
1.218 brouard 2956: int i, ii, j,k;
1.222 brouard 2957:
2958: double **out, **pmij();
2959: double sumnew=0.;
1.218 brouard 2960: double agefin;
1.268 brouard 2961: 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 2962: double **dnewm, **dsavm, **doldm;
2963: double **bbmij;
2964:
1.218 brouard 2965: doldm=ddoldms; /* global pointers */
1.222 brouard 2966: dnewm=ddnewms;
2967: dsavm=ddsavms;
2968:
2969: agefin=cov[2];
1.268 brouard 2970: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 2971: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 2972: the observed prevalence (with this covariate ij) at beginning of transition */
2973: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 2974:
2975: /* P_x */
1.266 brouard 2976: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 2977: /* outputs pmmij which is a stochastic matrix in row */
2978:
2979: /* Diag(w_x) */
2980: /* Problem with prevacurrent which can be zero */
2981: sumnew=0.;
1.269 brouard 2982: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 2983: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.269 brouard 2984: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 2985: sumnew+=prevacurrent[(int)agefin][ii][ij];
2986: }
2987: if(sumnew >0.01){ /* At least some value in the prevalence */
2988: for (ii=1;ii<=nlstate+ndeath;ii++){
2989: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 2990: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 2991: }
2992: }else{
2993: for (ii=1;ii<=nlstate+ndeath;ii++){
2994: for (j=1;j<=nlstate+ndeath;j++)
2995: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
2996: }
2997: /* if(sumnew <0.9){ */
2998: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
2999: /* } */
3000: }
3001: k3=0.0; /* We put the last diagonal to 0 */
3002: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3003: doldm[ii][ii]= k3;
3004: }
3005: /* End doldm, At the end doldm is diag[(w_i)] */
3006:
3007: /* left Product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm) */
3008: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* Bug Valgrind */
3009:
3010: /* Diag(Sum_i w^i_x p^ij_x */
3011: /* 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 3012: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3013: sumnew=0.;
1.222 brouard 3014: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3015: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3016: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3017: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3018: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3019: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3020: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3021: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3022: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3023: /* }else */
1.268 brouard 3024: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3025: } /*End ii */
3026: } /* 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 */
3027:
3028: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* Bug Valgrind */
3029: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3030: /* end bmij */
1.266 brouard 3031: return ps; /*pointer is unchanged */
1.218 brouard 3032: }
1.217 brouard 3033: /*************** transition probabilities ***************/
3034:
1.218 brouard 3035: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3036: {
3037: /* According to parameters values stored in x and the covariate's values stored in cov,
3038: computes the probability to be observed in state j being in state i by appying the
3039: model to the ncovmodel covariates (including constant and age).
3040: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3041: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3042: ncth covariate in the global vector x is given by the formula:
3043: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3044: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3045: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3046: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3047: Outputs ps[i][j] the probability to be observed in j being in j according to
3048: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3049: */
3050: double s1, lnpijopii;
3051: /*double t34;*/
3052: int i,j, nc, ii, jj;
3053:
1.234 brouard 3054: for(i=1; i<= nlstate; i++){
3055: for(j=1; j<i;j++){
3056: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3057: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3058: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3059: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3060: }
3061: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3062: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3063: }
3064: for(j=i+1; j<=nlstate+ndeath;j++){
3065: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3066: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3067: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3068: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3069: }
3070: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3071: }
3072: }
3073:
3074: for(i=1; i<= nlstate; i++){
3075: s1=0;
3076: for(j=1; j<i; j++){
3077: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3078: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3079: }
3080: for(j=i+1; j<=nlstate+ndeath; j++){
3081: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3082: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3083: }
3084: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3085: ps[i][i]=1./(s1+1.);
3086: /* Computing other pijs */
3087: for(j=1; j<i; j++)
3088: ps[i][j]= exp(ps[i][j])*ps[i][i];
3089: for(j=i+1; j<=nlstate+ndeath; j++)
3090: ps[i][j]= exp(ps[i][j])*ps[i][i];
3091: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3092: } /* end i */
3093:
3094: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3095: for(jj=1; jj<= nlstate+ndeath; jj++){
3096: ps[ii][jj]=0;
3097: ps[ii][ii]=1;
3098: }
3099: }
3100: /* Added for backcast */ /* Transposed matrix too */
3101: for(jj=1; jj<= nlstate+ndeath; jj++){
3102: s1=0.;
3103: for(ii=1; ii<= nlstate+ndeath; ii++){
3104: s1+=ps[ii][jj];
3105: }
3106: for(ii=1; ii<= nlstate; ii++){
3107: ps[ii][jj]=ps[ii][jj]/s1;
3108: }
3109: }
3110: /* Transposition */
3111: for(jj=1; jj<= nlstate+ndeath; jj++){
3112: for(ii=jj; ii<= nlstate+ndeath; ii++){
3113: s1=ps[ii][jj];
3114: ps[ii][jj]=ps[jj][ii];
3115: ps[jj][ii]=s1;
3116: }
3117: }
3118: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3119: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3120: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3121: /* } */
3122: /* printf("\n "); */
3123: /* } */
3124: /* printf("\n ");printf("%lf ",cov[2]);*/
3125: /*
3126: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3127: goto end;*/
3128: return ps;
1.217 brouard 3129: }
3130:
3131:
1.126 brouard 3132: /**************** Product of 2 matrices ******************/
3133:
1.145 brouard 3134: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3135: {
3136: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3137: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3138: /* in, b, out are matrice of pointers which should have been initialized
3139: before: only the contents of out is modified. The function returns
3140: a pointer to pointers identical to out */
1.145 brouard 3141: int i, j, k;
1.126 brouard 3142: for(i=nrl; i<= nrh; i++)
1.145 brouard 3143: for(k=ncolol; k<=ncoloh; k++){
3144: out[i][k]=0.;
3145: for(j=ncl; j<=nch; j++)
3146: out[i][k] +=in[i][j]*b[j][k];
3147: }
1.126 brouard 3148: return out;
3149: }
3150:
3151:
3152: /************* Higher Matrix Product ***************/
3153:
1.235 brouard 3154: 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 3155: {
1.218 brouard 3156: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3157: 'nhstepm*hstepm*stepm' months (i.e. until
3158: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3159: nhstepm*hstepm matrices.
3160: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3161: (typically every 2 years instead of every month which is too big
3162: for the memory).
3163: Model is determined by parameters x and covariates have to be
3164: included manually here.
3165:
3166: */
3167:
3168: int i, j, d, h, k;
1.131 brouard 3169: double **out, cov[NCOVMAX+1];
1.126 brouard 3170: double **newm;
1.187 brouard 3171: double agexact;
1.214 brouard 3172: double agebegin, ageend;
1.126 brouard 3173:
3174: /* Hstepm could be zero and should return the unit matrix */
3175: for (i=1;i<=nlstate+ndeath;i++)
3176: for (j=1;j<=nlstate+ndeath;j++){
3177: oldm[i][j]=(i==j ? 1.0 : 0.0);
3178: po[i][j][0]=(i==j ? 1.0 : 0.0);
3179: }
3180: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3181: for(h=1; h <=nhstepm; h++){
3182: for(d=1; d <=hstepm; d++){
3183: newm=savm;
3184: /* Covariates have to be included here again */
3185: cov[1]=1.;
1.214 brouard 3186: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3187: cov[2]=agexact;
3188: if(nagesqr==1)
1.227 brouard 3189: cov[3]= agexact*agexact;
1.235 brouard 3190: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3191: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3192: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3193: /* 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)); */
3194: }
3195: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3196: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3197: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3198: /* 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]); */
3199: }
3200: for (k=1; k<=cptcovage;k++){
3201: if(Dummy[Tvar[Tage[k]]]){
3202: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3203: } else{
3204: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3205: }
3206: /* 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]); */
3207: }
3208: for (k=1; k<=cptcovprod;k++){ /* */
3209: /* 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]); */
3210: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3211: }
3212: /* for (k=1; k<=cptcovn;k++) */
3213: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3214: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3215: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3216: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3217: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3218:
3219:
1.126 brouard 3220: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3221: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3222: /* right multiplication of oldm by the current matrix */
1.126 brouard 3223: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3224: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3225: /* if((int)age == 70){ */
3226: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3227: /* for(i=1; i<=nlstate+ndeath; i++) { */
3228: /* printf("%d pmmij ",i); */
3229: /* for(j=1;j<=nlstate+ndeath;j++) { */
3230: /* printf("%f ",pmmij[i][j]); */
3231: /* } */
3232: /* printf(" oldm "); */
3233: /* for(j=1;j<=nlstate+ndeath;j++) { */
3234: /* printf("%f ",oldm[i][j]); */
3235: /* } */
3236: /* printf("\n"); */
3237: /* } */
3238: /* } */
1.126 brouard 3239: savm=oldm;
3240: oldm=newm;
3241: }
3242: for(i=1; i<=nlstate+ndeath; i++)
3243: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3244: po[i][j][h]=newm[i][j];
3245: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3246: }
1.128 brouard 3247: /*printf("h=%d ",h);*/
1.126 brouard 3248: } /* end h */
1.267 brouard 3249: /* printf("\n H=%d \n",h); */
1.126 brouard 3250: return po;
3251: }
3252:
1.217 brouard 3253: /************* Higher Back Matrix Product ***************/
1.218 brouard 3254: /* 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 3255: 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 3256: {
1.266 brouard 3257: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3258: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3259: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3260: nhstepm*hstepm matrices.
3261: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3262: (typically every 2 years instead of every month which is too big
1.217 brouard 3263: for the memory).
1.218 brouard 3264: Model is determined by parameters x and covariates have to be
1.266 brouard 3265: included manually here. Then we use a call to bmij(x and cov)
3266: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3267: */
1.217 brouard 3268:
3269: int i, j, d, h, k;
1.266 brouard 3270: double **out, cov[NCOVMAX+1], **bmij();
3271: double **newm, ***newmm;
1.217 brouard 3272: double agexact;
3273: double agebegin, ageend;
1.222 brouard 3274: double **oldm, **savm;
1.217 brouard 3275:
1.266 brouard 3276: newmm=po; /* To be saved */
3277: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3278: /* Hstepm could be zero and should return the unit matrix */
3279: for (i=1;i<=nlstate+ndeath;i++)
3280: for (j=1;j<=nlstate+ndeath;j++){
3281: oldm[i][j]=(i==j ? 1.0 : 0.0);
3282: po[i][j][0]=(i==j ? 1.0 : 0.0);
3283: }
3284: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3285: for(h=1; h <=nhstepm; h++){
3286: for(d=1; d <=hstepm; d++){
3287: newm=savm;
3288: /* Covariates have to be included here again */
3289: cov[1]=1.;
1.271 brouard 3290: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3291: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3292: cov[2]=agexact;
3293: if(nagesqr==1)
1.222 brouard 3294: cov[3]= agexact*agexact;
1.266 brouard 3295: for (k=1; k<=cptcovn;k++){
3296: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3297: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3298: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3299: /* 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)); */
3300: }
1.267 brouard 3301: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3302: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3303: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3304: /* 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]); */
3305: }
3306: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3307: if(Dummy[Tvar[Tage[k]]]){
3308: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3309: } else{
3310: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3311: }
3312: /* 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]); */
3313: }
3314: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3315: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3316: }
1.217 brouard 3317: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3318: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3319:
1.218 brouard 3320: /* Careful transposed matrix */
1.266 brouard 3321: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3322: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3323: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3324: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3325: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3326: /* if((int)age == 70){ */
3327: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3328: /* for(i=1; i<=nlstate+ndeath; i++) { */
3329: /* printf("%d pmmij ",i); */
3330: /* for(j=1;j<=nlstate+ndeath;j++) { */
3331: /* printf("%f ",pmmij[i][j]); */
3332: /* } */
3333: /* printf(" oldm "); */
3334: /* for(j=1;j<=nlstate+ndeath;j++) { */
3335: /* printf("%f ",oldm[i][j]); */
3336: /* } */
3337: /* printf("\n"); */
3338: /* } */
3339: /* } */
3340: savm=oldm;
3341: oldm=newm;
3342: }
3343: for(i=1; i<=nlstate+ndeath; i++)
3344: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3345: po[i][j][h]=newm[i][j];
1.268 brouard 3346: /* if(h==nhstepm) */
3347: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3348: }
1.268 brouard 3349: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3350: } /* end h */
1.268 brouard 3351: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3352: return po;
3353: }
3354:
3355:
1.162 brouard 3356: #ifdef NLOPT
3357: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3358: double fret;
3359: double *xt;
3360: int j;
3361: myfunc_data *d2 = (myfunc_data *) pd;
3362: /* xt = (p1-1); */
3363: xt=vector(1,n);
3364: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3365:
3366: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3367: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3368: printf("Function = %.12lf ",fret);
3369: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3370: printf("\n");
3371: free_vector(xt,1,n);
3372: return fret;
3373: }
3374: #endif
1.126 brouard 3375:
3376: /*************** log-likelihood *************/
3377: double func( double *x)
3378: {
1.226 brouard 3379: int i, ii, j, k, mi, d, kk;
3380: int ioffset=0;
3381: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3382: double **out;
3383: double lli; /* Individual log likelihood */
3384: int s1, s2;
1.228 brouard 3385: 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 3386: double bbh, survp;
3387: long ipmx;
3388: double agexact;
3389: /*extern weight */
3390: /* We are differentiating ll according to initial status */
3391: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3392: /*for(i=1;i<imx;i++)
3393: printf(" %d\n",s[4][i]);
3394: */
1.162 brouard 3395:
1.226 brouard 3396: ++countcallfunc;
1.162 brouard 3397:
1.226 brouard 3398: cov[1]=1.;
1.126 brouard 3399:
1.226 brouard 3400: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3401: ioffset=0;
1.226 brouard 3402: if(mle==1){
3403: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3404: /* Computes the values of the ncovmodel covariates of the model
3405: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3406: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3407: to be observed in j being in i according to the model.
3408: */
1.243 brouard 3409: ioffset=2+nagesqr ;
1.233 brouard 3410: /* Fixed */
1.234 brouard 3411: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3412: 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)*/
3413: }
1.226 brouard 3414: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3415: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3416: has been calculated etc */
3417: /* For an individual i, wav[i] gives the number of effective waves */
3418: /* We compute the contribution to Likelihood of each effective transition
3419: mw[mi][i] is real wave of the mi th effectve wave */
3420: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3421: s2=s[mw[mi+1][i]][i];
3422: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3423: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3424: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3425: */
3426: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3427: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3428: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3429: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3430: }
3431: for (ii=1;ii<=nlstate+ndeath;ii++)
3432: for (j=1;j<=nlstate+ndeath;j++){
3433: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3434: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3435: }
3436: for(d=0; d<dh[mi][i]; d++){
3437: newm=savm;
3438: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3439: cov[2]=agexact;
3440: if(nagesqr==1)
3441: cov[3]= agexact*agexact; /* Should be changed here */
3442: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3443: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3444: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3445: else
3446: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3447: }
3448: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3449: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3450: savm=oldm;
3451: oldm=newm;
3452: } /* end mult */
3453:
3454: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3455: /* But now since version 0.9 we anticipate for bias at large stepm.
3456: * If stepm is larger than one month (smallest stepm) and if the exact delay
3457: * (in months) between two waves is not a multiple of stepm, we rounded to
3458: * the nearest (and in case of equal distance, to the lowest) interval but now
3459: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3460: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3461: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3462: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3463: * -stepm/2 to stepm/2 .
3464: * For stepm=1 the results are the same as for previous versions of Imach.
3465: * For stepm > 1 the results are less biased than in previous versions.
3466: */
1.234 brouard 3467: s1=s[mw[mi][i]][i];
3468: s2=s[mw[mi+1][i]][i];
3469: bbh=(double)bh[mi][i]/(double)stepm;
3470: /* bias bh is positive if real duration
3471: * is higher than the multiple of stepm and negative otherwise.
3472: */
3473: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3474: if( s2 > nlstate){
3475: /* i.e. if s2 is a death state and if the date of death is known
3476: then the contribution to the likelihood is the probability to
3477: die between last step unit time and current step unit time,
3478: which is also equal to probability to die before dh
3479: minus probability to die before dh-stepm .
3480: In version up to 0.92 likelihood was computed
3481: as if date of death was unknown. Death was treated as any other
3482: health state: the date of the interview describes the actual state
3483: and not the date of a change in health state. The former idea was
3484: to consider that at each interview the state was recorded
3485: (healthy, disable or death) and IMaCh was corrected; but when we
3486: introduced the exact date of death then we should have modified
3487: the contribution of an exact death to the likelihood. This new
3488: contribution is smaller and very dependent of the step unit
3489: stepm. It is no more the probability to die between last interview
3490: and month of death but the probability to survive from last
3491: interview up to one month before death multiplied by the
3492: probability to die within a month. Thanks to Chris
3493: Jackson for correcting this bug. Former versions increased
3494: mortality artificially. The bad side is that we add another loop
3495: which slows down the processing. The difference can be up to 10%
3496: lower mortality.
3497: */
3498: /* If, at the beginning of the maximization mostly, the
3499: cumulative probability or probability to be dead is
3500: constant (ie = 1) over time d, the difference is equal to
3501: 0. out[s1][3] = savm[s1][3]: probability, being at state
3502: s1 at precedent wave, to be dead a month before current
3503: wave is equal to probability, being at state s1 at
3504: precedent wave, to be dead at mont of the current
3505: wave. Then the observed probability (that this person died)
3506: is null according to current estimated parameter. In fact,
3507: it should be very low but not zero otherwise the log go to
3508: infinity.
3509: */
1.183 brouard 3510: /* #ifdef INFINITYORIGINAL */
3511: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3512: /* #else */
3513: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3514: /* lli=log(mytinydouble); */
3515: /* else */
3516: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3517: /* #endif */
1.226 brouard 3518: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3519:
1.226 brouard 3520: } else if ( s2==-1 ) { /* alive */
3521: for (j=1,survp=0. ; j<=nlstate; j++)
3522: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3523: /*survp += out[s1][j]; */
3524: lli= log(survp);
3525: }
3526: else if (s2==-4) {
3527: for (j=3,survp=0. ; j<=nlstate; j++)
3528: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3529: lli= log(survp);
3530: }
3531: else if (s2==-5) {
3532: for (j=1,survp=0. ; j<=2; j++)
3533: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3534: lli= log(survp);
3535: }
3536: else{
3537: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3538: /* 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 */
3539: }
3540: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3541: /*if(lli ==000.0)*/
3542: /*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); */
3543: ipmx +=1;
3544: sw += weight[i];
3545: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3546: /* if (lli < log(mytinydouble)){ */
3547: /* 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); */
3548: /* 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]); */
3549: /* } */
3550: } /* end of wave */
3551: } /* end of individual */
3552: } else if(mle==2){
3553: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3554: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3555: for(mi=1; mi<= wav[i]-1; mi++){
3556: for (ii=1;ii<=nlstate+ndeath;ii++)
3557: for (j=1;j<=nlstate+ndeath;j++){
3558: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3559: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3560: }
3561: for(d=0; d<=dh[mi][i]; d++){
3562: newm=savm;
3563: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3564: cov[2]=agexact;
3565: if(nagesqr==1)
3566: cov[3]= agexact*agexact;
3567: for (kk=1; kk<=cptcovage;kk++) {
3568: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3569: }
3570: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3571: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3572: savm=oldm;
3573: oldm=newm;
3574: } /* end mult */
3575:
3576: s1=s[mw[mi][i]][i];
3577: s2=s[mw[mi+1][i]][i];
3578: bbh=(double)bh[mi][i]/(double)stepm;
3579: 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 */
3580: ipmx +=1;
3581: sw += weight[i];
3582: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3583: } /* end of wave */
3584: } /* end of individual */
3585: } else if(mle==3){ /* exponential inter-extrapolation */
3586: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3587: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3588: for(mi=1; mi<= wav[i]-1; mi++){
3589: for (ii=1;ii<=nlstate+ndeath;ii++)
3590: for (j=1;j<=nlstate+ndeath;j++){
3591: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3592: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3593: }
3594: for(d=0; d<dh[mi][i]; d++){
3595: newm=savm;
3596: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3597: cov[2]=agexact;
3598: if(nagesqr==1)
3599: cov[3]= agexact*agexact;
3600: for (kk=1; kk<=cptcovage;kk++) {
3601: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3602: }
3603: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3604: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3605: savm=oldm;
3606: oldm=newm;
3607: } /* end mult */
3608:
3609: s1=s[mw[mi][i]][i];
3610: s2=s[mw[mi+1][i]][i];
3611: bbh=(double)bh[mi][i]/(double)stepm;
3612: 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 */
3613: ipmx +=1;
3614: sw += weight[i];
3615: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3616: } /* end of wave */
3617: } /* end of individual */
3618: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3619: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3620: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3621: for(mi=1; mi<= wav[i]-1; mi++){
3622: for (ii=1;ii<=nlstate+ndeath;ii++)
3623: for (j=1;j<=nlstate+ndeath;j++){
3624: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3625: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3626: }
3627: for(d=0; d<dh[mi][i]; d++){
3628: newm=savm;
3629: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3630: cov[2]=agexact;
3631: if(nagesqr==1)
3632: cov[3]= agexact*agexact;
3633: for (kk=1; kk<=cptcovage;kk++) {
3634: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3635: }
1.126 brouard 3636:
1.226 brouard 3637: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3638: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3639: savm=oldm;
3640: oldm=newm;
3641: } /* end mult */
3642:
3643: s1=s[mw[mi][i]][i];
3644: s2=s[mw[mi+1][i]][i];
3645: if( s2 > nlstate){
3646: lli=log(out[s1][s2] - savm[s1][s2]);
3647: } else if ( s2==-1 ) { /* alive */
3648: for (j=1,survp=0. ; j<=nlstate; j++)
3649: survp += out[s1][j];
3650: lli= log(survp);
3651: }else{
3652: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3653: }
3654: ipmx +=1;
3655: sw += weight[i];
3656: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3657: /* 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 3658: } /* end of wave */
3659: } /* end of individual */
3660: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3661: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3662: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3663: for(mi=1; mi<= wav[i]-1; mi++){
3664: for (ii=1;ii<=nlstate+ndeath;ii++)
3665: for (j=1;j<=nlstate+ndeath;j++){
3666: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3667: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3668: }
3669: for(d=0; d<dh[mi][i]; d++){
3670: newm=savm;
3671: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3672: cov[2]=agexact;
3673: if(nagesqr==1)
3674: cov[3]= agexact*agexact;
3675: for (kk=1; kk<=cptcovage;kk++) {
3676: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3677: }
1.126 brouard 3678:
1.226 brouard 3679: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3680: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3681: savm=oldm;
3682: oldm=newm;
3683: } /* end mult */
3684:
3685: s1=s[mw[mi][i]][i];
3686: s2=s[mw[mi+1][i]][i];
3687: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3688: ipmx +=1;
3689: sw += weight[i];
3690: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3691: /*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]);*/
3692: } /* end of wave */
3693: } /* end of individual */
3694: } /* End of if */
3695: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3696: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3697: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3698: return -l;
1.126 brouard 3699: }
3700:
3701: /*************** log-likelihood *************/
3702: double funcone( double *x)
3703: {
1.228 brouard 3704: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3705: int i, ii, j, k, mi, d, kk;
1.228 brouard 3706: int ioffset=0;
1.131 brouard 3707: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3708: double **out;
3709: double lli; /* Individual log likelihood */
3710: double llt;
3711: int s1, s2;
1.228 brouard 3712: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3713:
1.126 brouard 3714: double bbh, survp;
1.187 brouard 3715: double agexact;
1.214 brouard 3716: double agebegin, ageend;
1.126 brouard 3717: /*extern weight */
3718: /* We are differentiating ll according to initial status */
3719: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3720: /*for(i=1;i<imx;i++)
3721: printf(" %d\n",s[4][i]);
3722: */
3723: cov[1]=1.;
3724:
3725: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3726: ioffset=0;
3727: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3728: /* ioffset=2+nagesqr+cptcovage; */
3729: ioffset=2+nagesqr;
1.232 brouard 3730: /* Fixed */
1.224 brouard 3731: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3732: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3733: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3734: 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)*/
3735: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3736: /* cov[2+6]=covar[Tvar[6]][i]; */
3737: /* cov[2+6]=covar[2][i]; V2 */
3738: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3739: /* cov[2+7]=covar[Tvar[7]][i]; */
3740: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3741: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3742: /* cov[2+9]=covar[Tvar[9]][i]; */
3743: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3744: }
1.232 brouard 3745: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3746: /* 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?)*\/ */
3747: /* } */
1.231 brouard 3748: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3749: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3750: /* } */
1.225 brouard 3751:
1.233 brouard 3752:
3753: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3754: /* Wave varying (but not age varying) */
3755: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3756: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3757: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3758: }
1.232 brouard 3759: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3760: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3761: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3762: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3763: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3764: /* 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 3765: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3766: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3767: /* /\* 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]); *\/ */
3768: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3769: /* } */
1.126 brouard 3770: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3771: for (j=1;j<=nlstate+ndeath;j++){
3772: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3773: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3774: }
1.214 brouard 3775:
3776: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3777: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3778: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3779: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3780: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3781: and mw[mi+1][i]. dh depends on stepm.*/
3782: newm=savm;
1.247 brouard 3783: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3784: cov[2]=agexact;
3785: if(nagesqr==1)
3786: cov[3]= agexact*agexact;
3787: for (kk=1; kk<=cptcovage;kk++) {
3788: if(!FixedV[Tvar[Tage[kk]]])
3789: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3790: else
3791: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3792: }
3793: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3794: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3795: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3796: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3797: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3798: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3799: savm=oldm;
3800: oldm=newm;
1.126 brouard 3801: } /* end mult */
3802:
3803: s1=s[mw[mi][i]][i];
3804: s2=s[mw[mi+1][i]][i];
1.217 brouard 3805: /* if(s2==-1){ */
1.268 brouard 3806: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3807: /* /\* exit(1); *\/ */
3808: /* } */
1.126 brouard 3809: bbh=(double)bh[mi][i]/(double)stepm;
3810: /* bias is positive if real duration
3811: * is higher than the multiple of stepm and negative otherwise.
3812: */
3813: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3814: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3815: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3816: for (j=1,survp=0. ; j<=nlstate; j++)
3817: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3818: lli= log(survp);
1.126 brouard 3819: }else if (mle==1){
1.242 brouard 3820: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3821: } else if(mle==2){
1.242 brouard 3822: 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 3823: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3824: 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 3825: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3826: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3827: } else{ /* mle=0 back to 1 */
1.242 brouard 3828: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3829: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3830: } /* End of if */
3831: ipmx +=1;
3832: sw += weight[i];
3833: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3834: /*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 3835: if(globpr){
1.246 brouard 3836: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3837: %11.6f %11.6f %11.6f ", \
1.242 brouard 3838: 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 3839: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3840: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3841: llt +=ll[k]*gipmx/gsw;
3842: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3843: }
3844: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3845: }
1.232 brouard 3846: } /* end of wave */
3847: } /* end of individual */
3848: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3849: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3850: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3851: if(globpr==0){ /* First time we count the contributions and weights */
3852: gipmx=ipmx;
3853: gsw=sw;
3854: }
3855: return -l;
1.126 brouard 3856: }
3857:
3858:
3859: /*************** function likelione ***********/
3860: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*funcone)(double []))
3861: {
3862: /* This routine should help understanding what is done with
3863: the selection of individuals/waves and
3864: to check the exact contribution to the likelihood.
3865: Plotting could be done.
3866: */
3867: int k;
3868:
3869: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3870: strcpy(fileresilk,"ILK_");
1.202 brouard 3871: strcat(fileresilk,fileresu);
1.126 brouard 3872: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3873: printf("Problem with resultfile: %s\n", fileresilk);
3874: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3875: }
1.214 brouard 3876: 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");
3877: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3878: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3879: for(k=1; k<=nlstate; k++)
3880: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3881: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3882: }
3883:
3884: *fretone=(*funcone)(p);
3885: if(*globpri !=0){
3886: fclose(ficresilk);
1.205 brouard 3887: if (mle ==0)
3888: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3889: else if(mle >=1)
3890: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3891: 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 3892: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 3893:
3894: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3895: 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 3896: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3897: }
1.207 brouard 3898: 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 3899: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3900: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3901: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3902: fflush(fichtm);
1.205 brouard 3903: }
1.126 brouard 3904: return;
3905: }
3906:
3907:
3908: /*********** Maximum Likelihood Estimation ***************/
3909:
3910: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3911: {
1.165 brouard 3912: int i,j, iter=0;
1.126 brouard 3913: double **xi;
3914: double fret;
3915: double fretone; /* Only one call to likelihood */
3916: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3917:
3918: #ifdef NLOPT
3919: int creturn;
3920: nlopt_opt opt;
3921: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3922: double *lb;
3923: double minf; /* the minimum objective value, upon return */
3924: double * p1; /* Shifted parameters from 0 instead of 1 */
3925: myfunc_data dinst, *d = &dinst;
3926: #endif
3927:
3928:
1.126 brouard 3929: xi=matrix(1,npar,1,npar);
3930: for (i=1;i<=npar;i++)
3931: for (j=1;j<=npar;j++)
3932: xi[i][j]=(i==j ? 1.0 : 0.0);
3933: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3934: strcpy(filerespow,"POW_");
1.126 brouard 3935: strcat(filerespow,fileres);
3936: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3937: printf("Problem with resultfile: %s\n", filerespow);
3938: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3939: }
3940: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3941: for (i=1;i<=nlstate;i++)
3942: for(j=1;j<=nlstate+ndeath;j++)
3943: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3944: fprintf(ficrespow,"\n");
1.162 brouard 3945: #ifdef POWELL
1.126 brouard 3946: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3947: #endif
1.126 brouard 3948:
1.162 brouard 3949: #ifdef NLOPT
3950: #ifdef NEWUOA
3951: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
3952: #else
3953: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
3954: #endif
3955: lb=vector(0,npar-1);
3956: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
3957: nlopt_set_lower_bounds(opt, lb);
3958: nlopt_set_initial_step1(opt, 0.1);
3959:
3960: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
3961: d->function = func;
3962: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
3963: nlopt_set_min_objective(opt, myfunc, d);
3964: nlopt_set_xtol_rel(opt, ftol);
3965: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
3966: printf("nlopt failed! %d\n",creturn);
3967: }
3968: else {
3969: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
3970: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
3971: iter=1; /* not equal */
3972: }
3973: nlopt_destroy(opt);
3974: #endif
1.126 brouard 3975: free_matrix(xi,1,npar,1,npar);
3976: fclose(ficrespow);
1.203 brouard 3977: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
3978: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 3979: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 3980:
3981: }
3982:
3983: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 3984: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 3985: {
3986: double **a,**y,*x,pd;
1.203 brouard 3987: /* double **hess; */
1.164 brouard 3988: int i, j;
1.126 brouard 3989: int *indx;
3990:
3991: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 3992: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 3993: void lubksb(double **a, int npar, int *indx, double b[]) ;
3994: void ludcmp(double **a, int npar, int *indx, double *d) ;
3995: double gompertz(double p[]);
1.203 brouard 3996: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 3997:
3998: printf("\nCalculation of the hessian matrix. Wait...\n");
3999: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4000: for (i=1;i<=npar;i++){
1.203 brouard 4001: printf("%d-",i);fflush(stdout);
4002: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4003:
4004: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4005:
4006: /* printf(" %f ",p[i]);
4007: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4008: }
4009:
4010: for (i=1;i<=npar;i++) {
4011: for (j=1;j<=npar;j++) {
4012: if (j>i) {
1.203 brouard 4013: printf(".%d-%d",i,j);fflush(stdout);
4014: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4015: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4016:
4017: hess[j][i]=hess[i][j];
4018: /*printf(" %lf ",hess[i][j]);*/
4019: }
4020: }
4021: }
4022: printf("\n");
4023: fprintf(ficlog,"\n");
4024:
4025: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4026: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4027:
4028: a=matrix(1,npar,1,npar);
4029: y=matrix(1,npar,1,npar);
4030: x=vector(1,npar);
4031: indx=ivector(1,npar);
4032: for (i=1;i<=npar;i++)
4033: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4034: ludcmp(a,npar,indx,&pd);
4035:
4036: for (j=1;j<=npar;j++) {
4037: for (i=1;i<=npar;i++) x[i]=0;
4038: x[j]=1;
4039: lubksb(a,npar,indx,x);
4040: for (i=1;i<=npar;i++){
4041: matcov[i][j]=x[i];
4042: }
4043: }
4044:
4045: printf("\n#Hessian matrix#\n");
4046: fprintf(ficlog,"\n#Hessian matrix#\n");
4047: for (i=1;i<=npar;i++) {
4048: for (j=1;j<=npar;j++) {
1.203 brouard 4049: printf("%.6e ",hess[i][j]);
4050: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4051: }
4052: printf("\n");
4053: fprintf(ficlog,"\n");
4054: }
4055:
1.203 brouard 4056: /* printf("\n#Covariance matrix#\n"); */
4057: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4058: /* for (i=1;i<=npar;i++) { */
4059: /* for (j=1;j<=npar;j++) { */
4060: /* printf("%.6e ",matcov[i][j]); */
4061: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4062: /* } */
4063: /* printf("\n"); */
4064: /* fprintf(ficlog,"\n"); */
4065: /* } */
4066:
1.126 brouard 4067: /* Recompute Inverse */
1.203 brouard 4068: /* for (i=1;i<=npar;i++) */
4069: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4070: /* ludcmp(a,npar,indx,&pd); */
4071:
4072: /* printf("\n#Hessian matrix recomputed#\n"); */
4073:
4074: /* for (j=1;j<=npar;j++) { */
4075: /* for (i=1;i<=npar;i++) x[i]=0; */
4076: /* x[j]=1; */
4077: /* lubksb(a,npar,indx,x); */
4078: /* for (i=1;i<=npar;i++){ */
4079: /* y[i][j]=x[i]; */
4080: /* printf("%.3e ",y[i][j]); */
4081: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4082: /* } */
4083: /* printf("\n"); */
4084: /* fprintf(ficlog,"\n"); */
4085: /* } */
4086:
4087: /* Verifying the inverse matrix */
4088: #ifdef DEBUGHESS
4089: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4090:
1.203 brouard 4091: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4092: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4093:
4094: for (j=1;j<=npar;j++) {
4095: for (i=1;i<=npar;i++){
1.203 brouard 4096: printf("%.2f ",y[i][j]);
4097: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4098: }
4099: printf("\n");
4100: fprintf(ficlog,"\n");
4101: }
1.203 brouard 4102: #endif
1.126 brouard 4103:
4104: free_matrix(a,1,npar,1,npar);
4105: free_matrix(y,1,npar,1,npar);
4106: free_vector(x,1,npar);
4107: free_ivector(indx,1,npar);
1.203 brouard 4108: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4109:
4110:
4111: }
4112:
4113: /*************** hessian matrix ****************/
4114: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4115: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4116: int i;
4117: int l=1, lmax=20;
1.203 brouard 4118: double k1,k2, res, fx;
1.132 brouard 4119: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4120: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4121: int k=0,kmax=10;
4122: double l1;
4123:
4124: fx=func(x);
4125: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4126: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4127: l1=pow(10,l);
4128: delts=delt;
4129: for(k=1 ; k <kmax; k=k+1){
4130: delt = delta*(l1*k);
4131: p2[theta]=x[theta] +delt;
1.145 brouard 4132: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4133: p2[theta]=x[theta]-delt;
4134: k2=func(p2)-fx;
4135: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4136: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4137:
1.203 brouard 4138: #ifdef DEBUGHESSII
1.126 brouard 4139: 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);
4140: 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);
4141: #endif
4142: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4143: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4144: k=kmax;
4145: }
4146: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4147: k=kmax; l=lmax*10;
1.126 brouard 4148: }
4149: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4150: delts=delt;
4151: }
1.203 brouard 4152: } /* End loop k */
1.126 brouard 4153: }
4154: delti[theta]=delts;
4155: return res;
4156:
4157: }
4158:
1.203 brouard 4159: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4160: {
4161: int i;
1.164 brouard 4162: int l=1, lmax=20;
1.126 brouard 4163: double k1,k2,k3,k4,res,fx;
1.132 brouard 4164: double p2[MAXPARM+1];
1.203 brouard 4165: int k, kmax=1;
4166: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4167:
4168: int firstime=0;
1.203 brouard 4169:
1.126 brouard 4170: fx=func(x);
1.203 brouard 4171: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4172: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4173: p2[thetai]=x[thetai]+delti[thetai]*k;
4174: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4175: k1=func(p2)-fx;
4176:
1.203 brouard 4177: p2[thetai]=x[thetai]+delti[thetai]*k;
4178: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4179: k2=func(p2)-fx;
4180:
1.203 brouard 4181: p2[thetai]=x[thetai]-delti[thetai]*k;
4182: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4183: k3=func(p2)-fx;
4184:
1.203 brouard 4185: p2[thetai]=x[thetai]-delti[thetai]*k;
4186: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4187: k4=func(p2)-fx;
1.203 brouard 4188: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4189: if(k1*k2*k3*k4 <0.){
1.208 brouard 4190: firstime=1;
1.203 brouard 4191: kmax=kmax+10;
1.208 brouard 4192: }
4193: if(kmax >=10 || firstime ==1){
1.246 brouard 4194: 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);
4195: 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 4196: 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);
4197: 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);
4198: }
4199: #ifdef DEBUGHESSIJ
4200: v1=hess[thetai][thetai];
4201: v2=hess[thetaj][thetaj];
4202: cv12=res;
4203: /* Computing eigen value of Hessian matrix */
4204: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4205: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4206: if ((lc2 <0) || (lc1 <0) ){
4207: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4208: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4209: 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);
4210: 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);
4211: }
1.126 brouard 4212: #endif
4213: }
4214: return res;
4215: }
4216:
1.203 brouard 4217: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4218: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4219: /* { */
4220: /* int i; */
4221: /* int l=1, lmax=20; */
4222: /* double k1,k2,k3,k4,res,fx; */
4223: /* double p2[MAXPARM+1]; */
4224: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4225: /* int k=0,kmax=10; */
4226: /* double l1; */
4227:
4228: /* fx=func(x); */
4229: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4230: /* l1=pow(10,l); */
4231: /* delts=delt; */
4232: /* for(k=1 ; k <kmax; k=k+1){ */
4233: /* delt = delti*(l1*k); */
4234: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4235: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4236: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4237: /* k1=func(p2)-fx; */
4238:
4239: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4240: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4241: /* k2=func(p2)-fx; */
4242:
4243: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4244: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4245: /* k3=func(p2)-fx; */
4246:
4247: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4248: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4249: /* k4=func(p2)-fx; */
4250: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4251: /* #ifdef DEBUGHESSIJ */
4252: /* 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); */
4253: /* 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); */
4254: /* #endif */
4255: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4256: /* k=kmax; */
4257: /* } */
4258: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4259: /* k=kmax; l=lmax*10; */
4260: /* } */
4261: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4262: /* delts=delt; */
4263: /* } */
4264: /* } /\* End loop k *\/ */
4265: /* } */
4266: /* delti[theta]=delts; */
4267: /* return res; */
4268: /* } */
4269:
4270:
1.126 brouard 4271: /************** Inverse of matrix **************/
4272: void ludcmp(double **a, int n, int *indx, double *d)
4273: {
4274: int i,imax,j,k;
4275: double big,dum,sum,temp;
4276: double *vv;
4277:
4278: vv=vector(1,n);
4279: *d=1.0;
4280: for (i=1;i<=n;i++) {
4281: big=0.0;
4282: for (j=1;j<=n;j++)
4283: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4284: if (big == 0.0){
4285: printf(" Singular Hessian matrix at row %d:\n",i);
4286: for (j=1;j<=n;j++) {
4287: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4288: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4289: }
4290: fflush(ficlog);
4291: fclose(ficlog);
4292: nrerror("Singular matrix in routine ludcmp");
4293: }
1.126 brouard 4294: vv[i]=1.0/big;
4295: }
4296: for (j=1;j<=n;j++) {
4297: for (i=1;i<j;i++) {
4298: sum=a[i][j];
4299: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4300: a[i][j]=sum;
4301: }
4302: big=0.0;
4303: for (i=j;i<=n;i++) {
4304: sum=a[i][j];
4305: for (k=1;k<j;k++)
4306: sum -= a[i][k]*a[k][j];
4307: a[i][j]=sum;
4308: if ( (dum=vv[i]*fabs(sum)) >= big) {
4309: big=dum;
4310: imax=i;
4311: }
4312: }
4313: if (j != imax) {
4314: for (k=1;k<=n;k++) {
4315: dum=a[imax][k];
4316: a[imax][k]=a[j][k];
4317: a[j][k]=dum;
4318: }
4319: *d = -(*d);
4320: vv[imax]=vv[j];
4321: }
4322: indx[j]=imax;
4323: if (a[j][j] == 0.0) a[j][j]=TINY;
4324: if (j != n) {
4325: dum=1.0/(a[j][j]);
4326: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4327: }
4328: }
4329: free_vector(vv,1,n); /* Doesn't work */
4330: ;
4331: }
4332:
4333: void lubksb(double **a, int n, int *indx, double b[])
4334: {
4335: int i,ii=0,ip,j;
4336: double sum;
4337:
4338: for (i=1;i<=n;i++) {
4339: ip=indx[i];
4340: sum=b[ip];
4341: b[ip]=b[i];
4342: if (ii)
4343: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4344: else if (sum) ii=i;
4345: b[i]=sum;
4346: }
4347: for (i=n;i>=1;i--) {
4348: sum=b[i];
4349: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4350: b[i]=sum/a[i][i];
4351: }
4352: }
4353:
4354: void pstamp(FILE *fichier)
4355: {
1.196 brouard 4356: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4357: }
4358:
1.253 brouard 4359:
4360:
1.126 brouard 4361: /************ Frequencies ********************/
1.251 brouard 4362: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4363: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4364: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4365: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4366:
1.265 brouard 4367: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4368: int iind=0, iage=0;
4369: int mi; /* Effective wave */
4370: int first;
4371: double ***freq; /* Frequencies */
1.268 brouard 4372: 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 */
4373: 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 4374: double *meanq, *stdq, *idq;
1.226 brouard 4375: double **meanqt;
4376: double *pp, **prop, *posprop, *pospropt;
4377: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4378: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4379: double agebegin, ageend;
4380:
4381: pp=vector(1,nlstate);
1.251 brouard 4382: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4383: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4384: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4385: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4386: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 ! brouard 4387: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4388: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4389: meanqt=matrix(1,lastpass,1,nqtveff);
4390: strcpy(fileresp,"P_");
4391: strcat(fileresp,fileresu);
4392: /*strcat(fileresphtm,fileresu);*/
4393: if((ficresp=fopen(fileresp,"w"))==NULL) {
4394: printf("Problem with prevalence resultfile: %s\n", fileresp);
4395: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4396: exit(0);
4397: }
1.240 brouard 4398:
1.226 brouard 4399: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4400: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4401: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4402: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4403: fflush(ficlog);
4404: exit(70);
4405: }
4406: else{
4407: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4408: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4409: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4410: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4411: }
1.237 brouard 4412: 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 4413:
1.226 brouard 4414: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4415: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4416: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4417: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4418: fflush(ficlog);
4419: exit(70);
1.240 brouard 4420: } else{
1.226 brouard 4421: 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 4422: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4423: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4424: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4425: }
1.240 brouard 4426: 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);
4427:
1.253 brouard 4428: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4429: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4430: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4431: j1=0;
1.126 brouard 4432:
1.227 brouard 4433: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4434: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4435: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4436:
4437:
1.226 brouard 4438: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4439: reference=low_education V1=0,V2=0
4440: med_educ V1=1 V2=0,
4441: high_educ V1=0 V2=1
4442: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4443: */
1.249 brouard 4444: dateintsum=0;
4445: k2cpt=0;
4446:
1.253 brouard 4447: if(cptcoveff == 0 )
1.265 brouard 4448: nl=1; /* Constant and age model only */
1.253 brouard 4449: else
4450: nl=2;
1.265 brouard 4451:
4452: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4453: /* Loop on nj=1 or 2 if dummy covariates j!=0
4454: * Loop on j1(1 to 2**cptcoveff) covariate combination
4455: * freq[s1][s2][iage] =0.
4456: * Loop on iind
4457: * ++freq[s1][s2][iage] weighted
4458: * end iind
4459: * if covariate and j!0
4460: * headers Variable on one line
4461: * endif cov j!=0
4462: * header of frequency table by age
4463: * Loop on age
4464: * pp[s1]+=freq[s1][s2][iage] weighted
4465: * pos+=freq[s1][s2][iage] weighted
4466: * Loop on s1 initial state
4467: * fprintf(ficresp
4468: * end s1
4469: * end age
4470: * if j!=0 computes starting values
4471: * end compute starting values
4472: * end j1
4473: * end nl
4474: */
1.253 brouard 4475: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4476: if(nj==1)
4477: j=0; /* First pass for the constant */
1.265 brouard 4478: else{
1.253 brouard 4479: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4480: }
1.251 brouard 4481: first=1;
1.265 brouard 4482: 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 4483: posproptt=0.;
4484: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4485: scanf("%d", i);*/
4486: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4487: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4488: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4489: freq[i][s2][m]=0;
1.251 brouard 4490:
4491: for (i=1; i<=nlstate; i++) {
1.240 brouard 4492: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4493: prop[i][m]=0;
4494: posprop[i]=0;
4495: pospropt[i]=0;
4496: }
1.283 brouard 4497: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 ! brouard 4498: idq[z1]=0.;
! 4499: meanq[z1]=0.;
! 4500: stdq[z1]=0.;
1.283 brouard 4501: }
4502: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4503: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4504: /* meanqt[m][z1]=0.; */
4505: /* } */
4506: /* } */
1.251 brouard 4507: /* dateintsum=0; */
4508: /* k2cpt=0; */
4509:
1.265 brouard 4510: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4511: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4512: bool=1;
4513: if(j !=0){
4514: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4515: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4516: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4517: /* if(Tvaraff[z1] ==-20){ */
4518: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4519: /* }else if(Tvaraff[z1] ==-10){ */
4520: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4521: /* }else */
4522: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4523: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4524: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4525: /* 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",
4526: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4527: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4528: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4529: } /* Onlyf fixed */
4530: } /* end z1 */
4531: } /* cptcovn > 0 */
4532: } /* end any */
4533: }/* end j==0 */
1.265 brouard 4534: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4535: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 ! brouard 4536: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4537: m=mw[mi][iind];
4538: if(j!=0){
4539: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4540: for (z1=1; z1<=cptcoveff; z1++) {
4541: if( Fixed[Tmodelind[z1]]==1){
4542: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4543: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4544: value is -1, we don't select. It differs from the
4545: constant and age model which counts them. */
4546: bool=0; /* not selected */
4547: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4548: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4549: bool=0;
4550: }
4551: }
4552: }
4553: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4554: } /* end j==0 */
4555: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 ! brouard 4556: if(bool==1){ /*Selected */
1.251 brouard 4557: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4558: and mw[mi+1][iind]. dh depends on stepm. */
4559: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4560: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4561: if(m >=firstpass && m <=lastpass){
4562: k2=anint[m][iind]+(mint[m][iind]/12.);
4563: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4564: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4565: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4566: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4567: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4568: if (m<lastpass) {
4569: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4570: /* 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]); */
4571: if(s[m][iind]==-1)
4572: 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.));
4573: 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 4574: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean */
! 4575: idq[z1]=idq[z1]+weight[iind];
! 4576: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
! 4577: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
! 4578: }
1.251 brouard 4579: /* if((int)agev[m][iind] == 55) */
4580: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4581: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4582: 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 4583: }
1.251 brouard 4584: } /* end if between passes */
4585: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4586: dateintsum=dateintsum+k2; /* on all covariates ?*/
4587: k2cpt++;
4588: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4589: }
1.251 brouard 4590: }else{
4591: bool=1;
4592: }/* end bool 2 */
4593: } /* end m */
1.284 ! brouard 4594: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
! 4595: /* idq[z1]=idq[z1]+weight[iind]; */
! 4596: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
! 4597: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
! 4598: /* } */
1.251 brouard 4599: } /* end bool */
4600: } /* end iind = 1 to imx */
4601: /* prop[s][age] is feeded for any initial and valid live state as well as
4602: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4603:
4604:
4605: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4606: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4607: pstamp(ficresp);
1.251 brouard 4608: if (cptcoveff>0 && j!=0){
1.265 brouard 4609: pstamp(ficresp);
1.251 brouard 4610: printf( "\n#********** Variable ");
4611: fprintf(ficresp, "\n#********** Variable ");
4612: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4613: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4614: fprintf(ficlog, "\n#********** Variable ");
4615: for (z1=1; z1<=cptcoveff; z1++){
4616: if(!FixedV[Tvaraff[z1]]){
4617: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4618: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4619: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4620: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4621: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4622: }else{
1.251 brouard 4623: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4624: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4625: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4626: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4627: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4628: }
4629: }
4630: printf( "**********\n#");
4631: fprintf(ficresp, "**********\n#");
4632: fprintf(ficresphtm, "**********</h3>\n");
4633: fprintf(ficresphtmfr, "**********</h3>\n");
4634: fprintf(ficlog, "**********\n");
4635: }
1.284 ! brouard 4636: /*
! 4637: Printing means of quantitative variables if any
! 4638: */
! 4639: for (z1=1; z1<= nqfveff; z1++) {
! 4640: fprintf(ficlog,"Mean of quantitative variable V%d on %.0f individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
! 4641: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
! 4642: if(weightopt==1){
! 4643: printf(" Weighted mean and standard deviation of");
! 4644: fprintf(ficlog," Weighted mean and standard deviation of");
! 4645: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
! 4646: }
! 4647: printf(" 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]));
! 4648: fprintf(ficlog," 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]));
! 4649: fprintf(ficresphtmfr," 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]));
! 4650: }
! 4651: /* for (z1=1; z1<= nqtveff; z1++) { */
! 4652: /* for(m=1;m<=lastpass;m++){ */
! 4653: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
! 4654: /* } */
! 4655: /* } */
1.283 brouard 4656:
1.251 brouard 4657: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4658: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4659: fprintf(ficresp, " Age");
4660: 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 4661: for(i=1; i<=nlstate;i++) {
1.265 brouard 4662: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4663: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4664: }
1.265 brouard 4665: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4666: fprintf(ficresphtm, "\n");
4667:
4668: /* Header of frequency table by age */
4669: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4670: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4671: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4672: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4673: if(s2!=0 && m!=0)
4674: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4675: }
1.226 brouard 4676: }
1.251 brouard 4677: fprintf(ficresphtmfr, "\n");
4678:
4679: /* For each age */
4680: for(iage=iagemin; iage <= iagemax+3; iage++){
4681: fprintf(ficresphtm,"<tr>");
4682: if(iage==iagemax+1){
4683: fprintf(ficlog,"1");
4684: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4685: }else if(iage==iagemax+2){
4686: fprintf(ficlog,"0");
4687: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4688: }else if(iage==iagemax+3){
4689: fprintf(ficlog,"Total");
4690: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4691: }else{
1.240 brouard 4692: if(first==1){
1.251 brouard 4693: first=0;
4694: printf("See log file for details...\n");
4695: }
4696: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4697: fprintf(ficlog,"Age %d", iage);
4698: }
1.265 brouard 4699: for(s1=1; s1 <=nlstate ; s1++){
4700: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4701: pp[s1] += freq[s1][m][iage];
1.251 brouard 4702: }
1.265 brouard 4703: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4704: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4705: pos += freq[s1][m][iage];
4706: if(pp[s1]>=1.e-10){
1.251 brouard 4707: if(first==1){
1.265 brouard 4708: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4709: }
1.265 brouard 4710: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4711: }else{
4712: if(first==1)
1.265 brouard 4713: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4714: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4715: }
4716: }
4717:
1.265 brouard 4718: for(s1=1; s1 <=nlstate ; s1++){
4719: /* posprop[s1]=0; */
4720: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4721: pp[s1] += freq[s1][m][iage];
4722: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4723:
4724: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4725: pos += pp[s1]; /* pos is the total number of transitions until this age */
4726: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4727: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4728: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4729: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4730: }
4731:
4732: /* Writing ficresp */
4733: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4734: if( iage <= iagemax){
4735: fprintf(ficresp," %d",iage);
4736: }
4737: }else if( nj==2){
4738: if( iage <= iagemax){
4739: fprintf(ficresp," %d",iage);
4740: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4741: }
1.240 brouard 4742: }
1.265 brouard 4743: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4744: if(pos>=1.e-5){
1.251 brouard 4745: if(first==1)
1.265 brouard 4746: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4747: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4748: }else{
4749: if(first==1)
1.265 brouard 4750: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4751: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4752: }
4753: if( iage <= iagemax){
4754: if(pos>=1.e-5){
1.265 brouard 4755: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4756: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4757: }else if( nj==2){
4758: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4759: }
4760: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4761: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4762: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4763: } else{
4764: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4765: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4766: }
1.240 brouard 4767: }
1.265 brouard 4768: pospropt[s1] +=posprop[s1];
4769: } /* end loop s1 */
1.251 brouard 4770: /* pospropt=0.; */
1.265 brouard 4771: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4772: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4773: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4774: if(first==1){
1.265 brouard 4775: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4776: }
1.265 brouard 4777: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4778: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4779: }
1.265 brouard 4780: if(s1!=0 && m!=0)
4781: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4782: }
1.265 brouard 4783: } /* end loop s1 */
1.251 brouard 4784: posproptt=0.;
1.265 brouard 4785: for(s1=1; s1 <=nlstate; s1++){
4786: posproptt += pospropt[s1];
1.251 brouard 4787: }
4788: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4789: fprintf(ficresphtm,"</tr>\n");
4790: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4791: if(iage <= iagemax)
4792: fprintf(ficresp,"\n");
1.240 brouard 4793: }
1.251 brouard 4794: if(first==1)
4795: printf("Others in log...\n");
4796: fprintf(ficlog,"\n");
4797: } /* end loop age iage */
1.265 brouard 4798:
1.251 brouard 4799: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4800: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4801: if(posproptt < 1.e-5){
1.265 brouard 4802: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4803: }else{
1.265 brouard 4804: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4805: }
1.226 brouard 4806: }
1.251 brouard 4807: fprintf(ficresphtm,"</tr>\n");
4808: fprintf(ficresphtm,"</table>\n");
4809: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4810: if(posproptt < 1.e-5){
1.251 brouard 4811: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4812: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4813: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4814: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4815: invalidvarcomb[j1]=1;
1.226 brouard 4816: }else{
1.251 brouard 4817: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4818: invalidvarcomb[j1]=0;
1.226 brouard 4819: }
1.251 brouard 4820: fprintf(ficresphtmfr,"</table>\n");
4821: fprintf(ficlog,"\n");
4822: if(j!=0){
4823: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4824: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4825: for(k=1; k <=(nlstate+ndeath); k++){
4826: if (k != i) {
1.265 brouard 4827: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4828: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4829: if(j1==1){ /* All dummy covariates to zero */
4830: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4831: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4832: printf("%d%d ",i,k);
4833: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4834: 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]));
4835: 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]));
4836: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4837: }
1.253 brouard 4838: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4839: for(iage=iagemin; iage <= iagemax+3; iage++){
4840: x[iage]= (double)iage;
4841: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4842: /* 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 4843: }
1.268 brouard 4844: /* Some are not finite, but linreg will ignore these ages */
4845: no=0;
1.253 brouard 4846: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4847: pstart[s1]=b;
4848: pstart[s1-1]=a;
1.252 brouard 4849: }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 */
4850: 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]);
4851: 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 4852: 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 4853: printf("%d%d ",i,k);
4854: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4855: 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 4856: }else{ /* Other cases, like quantitative fixed or varying covariates */
4857: ;
4858: }
4859: /* printf("%12.7f )", param[i][jj][k]); */
4860: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4861: s1++;
1.251 brouard 4862: } /* end jj */
4863: } /* end k!= i */
4864: } /* end k */
1.265 brouard 4865: } /* end i, s1 */
1.251 brouard 4866: } /* end j !=0 */
4867: } /* end selected combination of covariate j1 */
4868: if(j==0){ /* We can estimate starting values from the occurences in each case */
4869: printf("#Freqsummary: Starting values for the constants:\n");
4870: fprintf(ficlog,"\n");
1.265 brouard 4871: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4872: for(k=1; k <=(nlstate+ndeath); k++){
4873: if (k != i) {
4874: printf("%d%d ",i,k);
4875: fprintf(ficlog,"%d%d ",i,k);
4876: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 4877: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 4878: if(jj==1){ /* Age has to be done */
1.265 brouard 4879: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
4880: 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]));
4881: 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 4882: }
4883: /* printf("%12.7f )", param[i][jj][k]); */
4884: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4885: s1++;
1.250 brouard 4886: }
1.251 brouard 4887: printf("\n");
4888: fprintf(ficlog,"\n");
1.250 brouard 4889: }
4890: }
1.284 ! brouard 4891: } /* end of state i */
1.251 brouard 4892: printf("#Freqsummary\n");
4893: fprintf(ficlog,"\n");
1.265 brouard 4894: for(s1=-1; s1 <=nlstate+ndeath; s1++){
4895: for(s2=-1; s2 <=nlstate+ndeath; s2++){
4896: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
4897: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4898: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4899: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
4900: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
4901: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 4902: /* } */
4903: }
1.265 brouard 4904: } /* end loop s1 */
1.251 brouard 4905:
4906: printf("\n");
4907: fprintf(ficlog,"\n");
4908: } /* end j=0 */
1.249 brouard 4909: } /* end j */
1.252 brouard 4910:
1.253 brouard 4911: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 4912: for(i=1, jk=1; i <=nlstate; i++){
4913: for(j=1; j <=nlstate+ndeath; j++){
4914: if(j!=i){
4915: /*ca[0]= k+'a'-1;ca[1]='\0';*/
4916: printf("%1d%1d",i,j);
4917: fprintf(ficparo,"%1d%1d",i,j);
4918: for(k=1; k<=ncovmodel;k++){
4919: /* printf(" %lf",param[i][j][k]); */
4920: /* fprintf(ficparo," %lf",param[i][j][k]); */
4921: p[jk]=pstart[jk];
4922: printf(" %f ",pstart[jk]);
4923: fprintf(ficparo," %f ",pstart[jk]);
4924: jk++;
4925: }
4926: printf("\n");
4927: fprintf(ficparo,"\n");
4928: }
4929: }
4930: }
4931: } /* end mle=-2 */
1.226 brouard 4932: dateintmean=dateintsum/k2cpt;
1.240 brouard 4933:
1.226 brouard 4934: fclose(ficresp);
4935: fclose(ficresphtm);
4936: fclose(ficresphtmfr);
1.283 brouard 4937: free_vector(idq,1,nqfveff);
1.226 brouard 4938: free_vector(meanq,1,nqfveff);
1.284 ! brouard 4939: free_vector(stdq,1,nqfveff);
1.226 brouard 4940: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 4941: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
4942: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 4943: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4944: free_vector(pospropt,1,nlstate);
4945: free_vector(posprop,1,nlstate);
1.251 brouard 4946: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4947: free_vector(pp,1,nlstate);
4948: /* End of freqsummary */
4949: }
1.126 brouard 4950:
1.268 brouard 4951: /* Simple linear regression */
4952: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
4953:
4954: /* y=a+bx regression */
4955: double sumx = 0.0; /* sum of x */
4956: double sumx2 = 0.0; /* sum of x**2 */
4957: double sumxy = 0.0; /* sum of x * y */
4958: double sumy = 0.0; /* sum of y */
4959: double sumy2 = 0.0; /* sum of y**2 */
4960: double sume2 = 0.0; /* sum of square or residuals */
4961: double yhat;
4962:
4963: double denom=0;
4964: int i;
4965: int ne=*no;
4966:
4967: for ( i=ifi, ne=0;i<=ila;i++) {
4968: if(!isfinite(x[i]) || !isfinite(y[i])){
4969: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
4970: continue;
4971: }
4972: ne=ne+1;
4973: sumx += x[i];
4974: sumx2 += x[i]*x[i];
4975: sumxy += x[i] * y[i];
4976: sumy += y[i];
4977: sumy2 += y[i]*y[i];
4978: denom = (ne * sumx2 - sumx*sumx);
4979: /* 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); */
4980: }
4981:
4982: denom = (ne * sumx2 - sumx*sumx);
4983: if (denom == 0) {
4984: // vertical, slope m is infinity
4985: *b = INFINITY;
4986: *a = 0;
4987: if (r) *r = 0;
4988: return 1;
4989: }
4990:
4991: *b = (ne * sumxy - sumx * sumy) / denom;
4992: *a = (sumy * sumx2 - sumx * sumxy) / denom;
4993: if (r!=NULL) {
4994: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
4995: sqrt((sumx2 - sumx*sumx/ne) *
4996: (sumy2 - sumy*sumy/ne));
4997: }
4998: *no=ne;
4999: for ( i=ifi, ne=0;i<=ila;i++) {
5000: if(!isfinite(x[i]) || !isfinite(y[i])){
5001: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5002: continue;
5003: }
5004: ne=ne+1;
5005: yhat = y[i] - *a -*b* x[i];
5006: sume2 += yhat * yhat ;
5007:
5008: denom = (ne * sumx2 - sumx*sumx);
5009: /* 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); */
5010: }
5011: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5012: *sa= *sb * sqrt(sumx2/ne);
5013:
5014: return 0;
5015: }
5016:
1.126 brouard 5017: /************ Prevalence ********************/
1.227 brouard 5018: 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)
5019: {
5020: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5021: in each health status at the date of interview (if between dateprev1 and dateprev2).
5022: We still use firstpass and lastpass as another selection.
5023: */
1.126 brouard 5024:
1.227 brouard 5025: int i, m, jk, j1, bool, z1,j, iv;
5026: int mi; /* Effective wave */
5027: int iage;
5028: double agebegin, ageend;
5029:
5030: double **prop;
5031: double posprop;
5032: double y2; /* in fractional years */
5033: int iagemin, iagemax;
5034: int first; /** to stop verbosity which is redirected to log file */
5035:
5036: iagemin= (int) agemin;
5037: iagemax= (int) agemax;
5038: /*pp=vector(1,nlstate);*/
1.251 brouard 5039: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5040: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5041: j1=0;
1.222 brouard 5042:
1.227 brouard 5043: /*j=cptcoveff;*/
5044: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5045:
1.227 brouard 5046: first=1;
5047: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5048: for (i=1; i<=nlstate; i++)
1.251 brouard 5049: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5050: prop[i][iage]=0.0;
5051: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5052: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5053: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5054:
5055: for (i=1; i<=imx; i++) { /* Each individual */
5056: bool=1;
5057: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5058: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5059: m=mw[mi][i];
5060: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5061: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5062: for (z1=1; z1<=cptcoveff; z1++){
5063: if( Fixed[Tmodelind[z1]]==1){
5064: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5065: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5066: bool=0;
5067: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5068: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5069: bool=0;
5070: }
5071: }
5072: if(bool==1){ /* Otherwise we skip that wave/person */
5073: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5074: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5075: if(m >=firstpass && m <=lastpass){
5076: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5077: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5078: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5079: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5080: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5081: 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);
5082: exit(1);
5083: }
5084: if (s[m][i]>0 && s[m][i]<=nlstate) {
5085: /*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]]);*/
5086: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5087: prop[s[m][i]][iagemax+3] += weight[i];
5088: } /* end valid statuses */
5089: } /* end selection of dates */
5090: } /* end selection of waves */
5091: } /* end bool */
5092: } /* end wave */
5093: } /* end individual */
5094: for(i=iagemin; i <= iagemax+3; i++){
5095: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5096: posprop += prop[jk][i];
5097: }
5098:
5099: for(jk=1; jk <=nlstate ; jk++){
5100: if( i <= iagemax){
5101: if(posprop>=1.e-5){
5102: probs[i][jk][j1]= prop[jk][i]/posprop;
5103: } else{
5104: if(first==1){
5105: first=0;
1.266 brouard 5106: 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]);
5107: fprintf(ficlog,"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]);
5108: }else{
5109: fprintf(ficlog,"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]);
1.227 brouard 5110: }
5111: }
5112: }
5113: }/* end jk */
5114: }/* end i */
1.222 brouard 5115: /*} *//* end i1 */
1.227 brouard 5116: } /* end j1 */
1.222 brouard 5117:
1.227 brouard 5118: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5119: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5120: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5121: } /* End of prevalence */
1.126 brouard 5122:
5123: /************* Waves Concatenation ***************/
5124:
5125: 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)
5126: {
5127: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
5128: Death is a valid wave (if date is known).
5129: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5130: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
5131: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 5132: */
1.126 brouard 5133:
1.224 brouard 5134: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5135: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5136: double sum=0., jmean=0.;*/
1.224 brouard 5137: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5138: int j, k=0,jk, ju, jl;
5139: double sum=0.;
5140: first=0;
1.214 brouard 5141: firstwo=0;
1.217 brouard 5142: firsthree=0;
1.218 brouard 5143: firstfour=0;
1.164 brouard 5144: jmin=100000;
1.126 brouard 5145: jmax=-1;
5146: jmean=0.;
1.224 brouard 5147:
5148: /* Treating live states */
1.214 brouard 5149: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5150: mi=0; /* First valid wave */
1.227 brouard 5151: mli=0; /* Last valid wave */
1.126 brouard 5152: m=firstpass;
1.214 brouard 5153: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 5154: 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 */
5155: mli=m-1;/* mw[++mi][i]=m-1; */
5156: }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 */
5157: mw[++mi][i]=m;
5158: mli=m;
1.224 brouard 5159: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5160: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5161: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5162: }
1.227 brouard 5163: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 5164: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5165: break;
1.224 brouard 5166: #else
1.227 brouard 5167: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
5168: if(firsthree == 0){
1.262 brouard 5169: 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 5170: firsthree=1;
5171: }
1.262 brouard 5172: 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 5173: mw[++mi][i]=m;
5174: mli=m;
5175: }
5176: if(s[m][i]==-2){ /* Vital status is really unknown */
5177: nbwarn++;
5178: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
5179: 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);
5180: 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);
5181: }
5182: break;
5183: }
5184: break;
1.224 brouard 5185: #endif
1.227 brouard 5186: }/* End m >= lastpass */
1.126 brouard 5187: }/* end while */
1.224 brouard 5188:
1.227 brouard 5189: /* 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 5190: /* After last pass */
1.224 brouard 5191: /* Treating death states */
1.214 brouard 5192: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5193: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5194: /* } */
1.126 brouard 5195: mi++; /* Death is another wave */
5196: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5197: /* Only death is a correct wave */
1.126 brouard 5198: mw[mi][i]=m;
1.257 brouard 5199: } /* else not in a death state */
1.224 brouard 5200: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5201: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5202: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 5203: 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 */
5204: nbwarn++;
5205: if(firstfiv==0){
5206: 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 );
5207: firstfiv=1;
5208: }else{
5209: 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 );
5210: }
5211: }else{ /* Death occured afer last wave potential bias */
5212: nberr++;
5213: if(firstwo==0){
1.257 brouard 5214: 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 5215: firstwo=1;
5216: }
1.257 brouard 5217: 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 5218: }
1.257 brouard 5219: }else{ /* if date of interview is unknown */
1.227 brouard 5220: /* death is known but not confirmed by death status at any wave */
5221: if(firstfour==0){
5222: 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 );
5223: firstfour=1;
5224: }
5225: 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 5226: }
1.224 brouard 5227: } /* end if date of death is known */
5228: #endif
5229: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5230: /* wav[i]=mw[mi][i]; */
1.126 brouard 5231: if(mi==0){
5232: nbwarn++;
5233: if(first==0){
1.227 brouard 5234: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5235: first=1;
1.126 brouard 5236: }
5237: if(first==1){
1.227 brouard 5238: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5239: }
5240: } /* end mi==0 */
5241: } /* End individuals */
1.214 brouard 5242: /* wav and mw are no more changed */
1.223 brouard 5243:
1.214 brouard 5244:
1.126 brouard 5245: for(i=1; i<=imx; i++){
5246: for(mi=1; mi<wav[i];mi++){
5247: if (stepm <=0)
1.227 brouard 5248: dh[mi][i]=1;
1.126 brouard 5249: else{
1.260 brouard 5250: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5251: if (agedc[i] < 2*AGESUP) {
5252: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5253: if(j==0) j=1; /* Survives at least one month after exam */
5254: else if(j<0){
5255: nberr++;
5256: 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]);
5257: j=1; /* Temporary Dangerous patch */
5258: 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);
5259: 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]);
5260: 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);
5261: }
5262: k=k+1;
5263: if (j >= jmax){
5264: jmax=j;
5265: ijmax=i;
5266: }
5267: if (j <= jmin){
5268: jmin=j;
5269: ijmin=i;
5270: }
5271: sum=sum+j;
5272: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5273: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5274: }
5275: }
5276: else{
5277: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5278: /* 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 5279:
1.227 brouard 5280: k=k+1;
5281: if (j >= jmax) {
5282: jmax=j;
5283: ijmax=i;
5284: }
5285: else if (j <= jmin){
5286: jmin=j;
5287: ijmin=i;
5288: }
5289: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5290: /*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]);*/
5291: if(j<0){
5292: nberr++;
5293: 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]);
5294: 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]);
5295: }
5296: sum=sum+j;
5297: }
5298: jk= j/stepm;
5299: jl= j -jk*stepm;
5300: ju= j -(jk+1)*stepm;
5301: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5302: if(jl==0){
5303: dh[mi][i]=jk;
5304: bh[mi][i]=0;
5305: }else{ /* We want a negative bias in order to only have interpolation ie
5306: * to avoid the price of an extra matrix product in likelihood */
5307: dh[mi][i]=jk+1;
5308: bh[mi][i]=ju;
5309: }
5310: }else{
5311: if(jl <= -ju){
5312: dh[mi][i]=jk;
5313: bh[mi][i]=jl; /* bias is positive if real duration
5314: * is higher than the multiple of stepm and negative otherwise.
5315: */
5316: }
5317: else{
5318: dh[mi][i]=jk+1;
5319: bh[mi][i]=ju;
5320: }
5321: if(dh[mi][i]==0){
5322: dh[mi][i]=1; /* At least one step */
5323: bh[mi][i]=ju; /* At least one step */
5324: /* 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);*/
5325: }
5326: } /* end if mle */
1.126 brouard 5327: }
5328: } /* end wave */
5329: }
5330: jmean=sum/k;
5331: 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 5332: 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 5333: }
1.126 brouard 5334:
5335: /*********** Tricode ****************************/
1.220 brouard 5336: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5337: {
5338: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5339: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5340: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5341: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5342: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5343: */
1.130 brouard 5344:
1.242 brouard 5345: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5346: int modmaxcovj=0; /* Modality max of covariates j */
5347: int cptcode=0; /* Modality max of covariates j */
5348: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5349:
5350:
1.242 brouard 5351: /* cptcoveff=0; */
5352: /* *cptcov=0; */
1.126 brouard 5353:
1.242 brouard 5354: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.126 brouard 5355:
1.242 brouard 5356: /* Loop on covariates without age and products and no quantitative variable */
5357: /* for (j=1; j<=(cptcovs); j++) { /\* From model V1 + V2*age+ V3 + V3*V4 keeps V1 + V3 = 2 only *\/ */
5358: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5359: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5360: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5361: switch(Fixed[k]) {
5362: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5363: 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*/
5364: ij=(int)(covar[Tvar[k]][i]);
5365: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5366: * If product of Vn*Vm, still boolean *:
5367: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5368: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5369: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5370: modality of the nth covariate of individual i. */
5371: if (ij > modmaxcovj)
5372: modmaxcovj=ij;
5373: else if (ij < modmincovj)
5374: modmincovj=ij;
5375: if ((ij < -1) && (ij > NCOVMAX)){
5376: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5377: exit(1);
5378: }else
5379: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5380: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5381: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5382: /* getting the maximum value of the modality of the covariate
5383: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5384: female ies 1, then modmaxcovj=1.
5385: */
5386: } /* end for loop on individuals i */
5387: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5388: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5389: cptcode=modmaxcovj;
5390: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5391: /*for (i=0; i<=cptcode; i++) {*/
5392: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5393: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5394: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5395: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5396: if( j != -1){
5397: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5398: covariate for which somebody answered excluding
5399: undefined. Usually 2: 0 and 1. */
5400: }
5401: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5402: covariate for which somebody answered including
5403: undefined. Usually 3: -1, 0 and 1. */
5404: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5405: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5406: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5407:
1.242 brouard 5408: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5409: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5410: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5411: /* modmincovj=3; modmaxcovj = 7; */
5412: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5413: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5414: /* defining two dummy variables: variables V1_1 and V1_2.*/
5415: /* nbcode[Tvar[j]][ij]=k; */
5416: /* nbcode[Tvar[j]][1]=0; */
5417: /* nbcode[Tvar[j]][2]=1; */
5418: /* nbcode[Tvar[j]][3]=2; */
5419: /* To be continued (not working yet). */
5420: ij=0; /* ij is similar to i but can jump over null modalities */
5421: 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*/
5422: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5423: break;
5424: }
5425: ij++;
5426: 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*/
5427: cptcode = ij; /* New max modality for covar j */
5428: } /* end of loop on modality i=-1 to 1 or more */
5429: break;
5430: case 1: /* Testing on varying covariate, could be simple and
5431: * should look at waves or product of fixed *
5432: * varying. No time to test -1, assuming 0 and 1 only */
5433: ij=0;
5434: for(i=0; i<=1;i++){
5435: nbcode[Tvar[k]][++ij]=i;
5436: }
5437: break;
5438: default:
5439: break;
5440: } /* end switch */
5441: } /* end dummy test */
5442:
5443: /* for (k=0; k<= cptcode; k++) { /\* k=-1 ? k=0 to 1 *\//\* Could be 1 to 4 *\//\* cptcode=modmaxcovj *\/ */
5444: /* /\*recode from 0 *\/ */
5445: /* k is a modality. If we have model=V1+V1*sex */
5446: /* then: nbcode[1][1]=0 ; nbcode[1][2]=1; nbcode[2][1]=0 ; nbcode[2][2]=1; */
5447: /* But if some modality were not used, it is recoded from 0 to a newer modmaxcovj=cptcode *\/ */
5448: /* } */
5449: /* /\* cptcode = ij; *\/ /\* New max modality for covar j *\/ */
5450: /* if (ij > ncodemax[j]) { */
5451: /* printf( " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5452: /* fprintf(ficlog, " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5453: /* break; */
5454: /* } */
5455: /* } /\* end of loop on modality k *\/ */
5456: } /* end of loop on model-covariate j. nbcode[Tvarj][1]=0 and nbcode[Tvarj][2]=1 sets the value of covariate j*/
5457:
5458: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5459: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5460: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5461: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5462: 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 */
5463: 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 */
5464: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5465: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5466:
5467: ij=0;
5468: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5469: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5470: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5471: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5472: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5473: /* If product not in single variable we don't print results */
5474: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5475: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5476: 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*/
5477: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5478: 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 */
5479: if(Fixed[k]!=0)
5480: anyvaryingduminmodel=1;
5481: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5482: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5483: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5484: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5485: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5486: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5487: }
5488: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5489: /* ij--; */
5490: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5491: *cptcov=ij; /*Number of total real effective covariates: effective
5492: * because they can be excluded from the model and real
5493: * if in the model but excluded because missing values, but how to get k from ij?*/
5494: for(j=ij+1; j<= cptcovt; j++){
5495: Tvaraff[j]=0;
5496: Tmodelind[j]=0;
5497: }
5498: for(j=ntveff+1; j<= cptcovt; j++){
5499: TmodelInvind[j]=0;
5500: }
5501: /* To be sorted */
5502: ;
5503: }
1.126 brouard 5504:
1.145 brouard 5505:
1.126 brouard 5506: /*********** Health Expectancies ****************/
5507:
1.235 brouard 5508: 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 5509:
5510: {
5511: /* Health expectancies, no variances */
1.164 brouard 5512: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5513: int nhstepma, nstepma; /* Decreasing with age */
5514: double age, agelim, hf;
5515: double ***p3mat;
5516: double eip;
5517:
1.238 brouard 5518: /* pstamp(ficreseij); */
1.126 brouard 5519: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5520: fprintf(ficreseij,"# Age");
5521: for(i=1; i<=nlstate;i++){
5522: for(j=1; j<=nlstate;j++){
5523: fprintf(ficreseij," e%1d%1d ",i,j);
5524: }
5525: fprintf(ficreseij," e%1d. ",i);
5526: }
5527: fprintf(ficreseij,"\n");
5528:
5529:
5530: if(estepm < stepm){
5531: printf ("Problem %d lower than %d\n",estepm, stepm);
5532: }
5533: else hstepm=estepm;
5534: /* We compute the life expectancy from trapezoids spaced every estepm months
5535: * This is mainly to measure the difference between two models: for example
5536: * if stepm=24 months pijx are given only every 2 years and by summing them
5537: * we are calculating an estimate of the Life Expectancy assuming a linear
5538: * progression in between and thus overestimating or underestimating according
5539: * to the curvature of the survival function. If, for the same date, we
5540: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5541: * to compare the new estimate of Life expectancy with the same linear
5542: * hypothesis. A more precise result, taking into account a more precise
5543: * curvature will be obtained if estepm is as small as stepm. */
5544:
5545: /* For example we decided to compute the life expectancy with the smallest unit */
5546: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5547: nhstepm is the number of hstepm from age to agelim
5548: nstepm is the number of stepm from age to agelin.
1.270 brouard 5549: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5550: and note for a fixed period like estepm months */
5551: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5552: survival function given by stepm (the optimization length). Unfortunately it
5553: means that if the survival funtion is printed only each two years of age and if
5554: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5555: results. So we changed our mind and took the option of the best precision.
5556: */
5557: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5558:
5559: agelim=AGESUP;
5560: /* If stepm=6 months */
5561: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5562: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5563:
5564: /* nhstepm age range expressed in number of stepm */
5565: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5566: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5567: /* if (stepm >= YEARM) hstepm=1;*/
5568: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5569: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5570:
5571: for (age=bage; age<=fage; age ++){
5572: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5573: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5574: /* if (stepm >= YEARM) hstepm=1;*/
5575: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5576:
5577: /* If stepm=6 months */
5578: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5579: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5580:
1.235 brouard 5581: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5582:
5583: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5584:
5585: printf("%d|",(int)age);fflush(stdout);
5586: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5587:
5588: /* Computing expectancies */
5589: for(i=1; i<=nlstate;i++)
5590: for(j=1; j<=nlstate;j++)
5591: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5592: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5593:
5594: /* 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]);*/
5595:
5596: }
5597:
5598: fprintf(ficreseij,"%3.0f",age );
5599: for(i=1; i<=nlstate;i++){
5600: eip=0;
5601: for(j=1; j<=nlstate;j++){
5602: eip +=eij[i][j][(int)age];
5603: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5604: }
5605: fprintf(ficreseij,"%9.4f", eip );
5606: }
5607: fprintf(ficreseij,"\n");
5608:
5609: }
5610: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5611: printf("\n");
5612: fprintf(ficlog,"\n");
5613:
5614: }
5615:
1.235 brouard 5616: 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 5617:
5618: {
5619: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5620: to initial status i, ei. .
1.126 brouard 5621: */
5622: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5623: int nhstepma, nstepma; /* Decreasing with age */
5624: double age, agelim, hf;
5625: double ***p3matp, ***p3matm, ***varhe;
5626: double **dnewm,**doldm;
5627: double *xp, *xm;
5628: double **gp, **gm;
5629: double ***gradg, ***trgradg;
5630: int theta;
5631:
5632: double eip, vip;
5633:
5634: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5635: xp=vector(1,npar);
5636: xm=vector(1,npar);
5637: dnewm=matrix(1,nlstate*nlstate,1,npar);
5638: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5639:
5640: pstamp(ficresstdeij);
5641: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5642: fprintf(ficresstdeij,"# Age");
5643: for(i=1; i<=nlstate;i++){
5644: for(j=1; j<=nlstate;j++)
5645: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5646: fprintf(ficresstdeij," e%1d. ",i);
5647: }
5648: fprintf(ficresstdeij,"\n");
5649:
5650: pstamp(ficrescveij);
5651: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5652: fprintf(ficrescveij,"# Age");
5653: for(i=1; i<=nlstate;i++)
5654: for(j=1; j<=nlstate;j++){
5655: cptj= (j-1)*nlstate+i;
5656: for(i2=1; i2<=nlstate;i2++)
5657: for(j2=1; j2<=nlstate;j2++){
5658: cptj2= (j2-1)*nlstate+i2;
5659: if(cptj2 <= cptj)
5660: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5661: }
5662: }
5663: fprintf(ficrescveij,"\n");
5664:
5665: if(estepm < stepm){
5666: printf ("Problem %d lower than %d\n",estepm, stepm);
5667: }
5668: else hstepm=estepm;
5669: /* We compute the life expectancy from trapezoids spaced every estepm months
5670: * This is mainly to measure the difference between two models: for example
5671: * if stepm=24 months pijx are given only every 2 years and by summing them
5672: * we are calculating an estimate of the Life Expectancy assuming a linear
5673: * progression in between and thus overestimating or underestimating according
5674: * to the curvature of the survival function. If, for the same date, we
5675: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5676: * to compare the new estimate of Life expectancy with the same linear
5677: * hypothesis. A more precise result, taking into account a more precise
5678: * curvature will be obtained if estepm is as small as stepm. */
5679:
5680: /* For example we decided to compute the life expectancy with the smallest unit */
5681: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5682: nhstepm is the number of hstepm from age to agelim
5683: nstepm is the number of stepm from age to agelin.
5684: Look at hpijx to understand the reason of that which relies in memory size
5685: and note for a fixed period like estepm months */
5686: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5687: survival function given by stepm (the optimization length). Unfortunately it
5688: means that if the survival funtion is printed only each two years of age and if
5689: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5690: results. So we changed our mind and took the option of the best precision.
5691: */
5692: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5693:
5694: /* If stepm=6 months */
5695: /* nhstepm age range expressed in number of stepm */
5696: agelim=AGESUP;
5697: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5698: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5699: /* if (stepm >= YEARM) hstepm=1;*/
5700: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5701:
5702: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5703: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5704: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5705: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5706: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5707: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5708:
5709: for (age=bage; age<=fage; age ++){
5710: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5711: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5712: /* if (stepm >= YEARM) hstepm=1;*/
5713: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5714:
1.126 brouard 5715: /* If stepm=6 months */
5716: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5717: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5718:
5719: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5720:
1.126 brouard 5721: /* Computing Variances of health expectancies */
5722: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5723: decrease memory allocation */
5724: for(theta=1; theta <=npar; theta++){
5725: for(i=1; i<=npar; i++){
1.222 brouard 5726: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5727: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5728: }
1.235 brouard 5729: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5730: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5731:
1.126 brouard 5732: for(j=1; j<= nlstate; j++){
1.222 brouard 5733: for(i=1; i<=nlstate; i++){
5734: for(h=0; h<=nhstepm-1; h++){
5735: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5736: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5737: }
5738: }
1.126 brouard 5739: }
1.218 brouard 5740:
1.126 brouard 5741: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5742: for(h=0; h<=nhstepm-1; h++){
5743: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5744: }
1.126 brouard 5745: }/* End theta */
5746:
5747:
5748: for(h=0; h<=nhstepm-1; h++)
5749: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5750: for(theta=1; theta <=npar; theta++)
5751: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5752:
1.218 brouard 5753:
1.222 brouard 5754: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5755: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5756: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5757:
1.222 brouard 5758: printf("%d|",(int)age);fflush(stdout);
5759: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5760: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5761: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5762: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5763: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5764: for(ij=1;ij<=nlstate*nlstate;ij++)
5765: for(ji=1;ji<=nlstate*nlstate;ji++)
5766: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5767: }
5768: }
1.218 brouard 5769:
1.126 brouard 5770: /* Computing expectancies */
1.235 brouard 5771: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5772: for(i=1; i<=nlstate;i++)
5773: for(j=1; j<=nlstate;j++)
1.222 brouard 5774: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5775: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5776:
1.222 brouard 5777: /* 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 5778:
1.222 brouard 5779: }
1.269 brouard 5780:
5781: /* Standard deviation of expectancies ij */
1.126 brouard 5782: fprintf(ficresstdeij,"%3.0f",age );
5783: for(i=1; i<=nlstate;i++){
5784: eip=0.;
5785: vip=0.;
5786: for(j=1; j<=nlstate;j++){
1.222 brouard 5787: eip += eij[i][j][(int)age];
5788: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5789: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5790: 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 5791: }
5792: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5793: }
5794: fprintf(ficresstdeij,"\n");
1.218 brouard 5795:
1.269 brouard 5796: /* Variance of expectancies ij */
1.126 brouard 5797: fprintf(ficrescveij,"%3.0f",age );
5798: for(i=1; i<=nlstate;i++)
5799: for(j=1; j<=nlstate;j++){
1.222 brouard 5800: cptj= (j-1)*nlstate+i;
5801: for(i2=1; i2<=nlstate;i2++)
5802: for(j2=1; j2<=nlstate;j2++){
5803: cptj2= (j2-1)*nlstate+i2;
5804: if(cptj2 <= cptj)
5805: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5806: }
1.126 brouard 5807: }
5808: fprintf(ficrescveij,"\n");
1.218 brouard 5809:
1.126 brouard 5810: }
5811: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5812: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5813: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5814: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5815: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5816: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5817: printf("\n");
5818: fprintf(ficlog,"\n");
1.218 brouard 5819:
1.126 brouard 5820: free_vector(xm,1,npar);
5821: free_vector(xp,1,npar);
5822: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5823: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5824: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5825: }
1.218 brouard 5826:
1.126 brouard 5827: /************ Variance ******************/
1.235 brouard 5828: 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 5829: {
1.279 brouard 5830: /** Variance of health expectancies
5831: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
5832: * double **newm;
5833: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
5834: */
1.218 brouard 5835:
5836: /* int movingaverage(); */
5837: double **dnewm,**doldm;
5838: double **dnewmp,**doldmp;
5839: int i, j, nhstepm, hstepm, h, nstepm ;
5840: int k;
5841: double *xp;
1.279 brouard 5842: double **gp, **gm; /**< for var eij */
5843: double ***gradg, ***trgradg; /**< for var eij */
5844: double **gradgp, **trgradgp; /**< for var p point j */
5845: double *gpp, *gmp; /**< for var p point j */
5846: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 5847: double ***p3mat;
5848: double age,agelim, hf;
5849: /* double ***mobaverage; */
5850: int theta;
5851: char digit[4];
5852: char digitp[25];
5853:
5854: char fileresprobmorprev[FILENAMELENGTH];
5855:
5856: if(popbased==1){
5857: if(mobilav!=0)
5858: strcpy(digitp,"-POPULBASED-MOBILAV_");
5859: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5860: }
5861: else
5862: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5863:
1.218 brouard 5864: /* if (mobilav!=0) { */
5865: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5866: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5867: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5868: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5869: /* } */
5870: /* } */
5871:
5872: strcpy(fileresprobmorprev,"PRMORPREV-");
5873: sprintf(digit,"%-d",ij);
5874: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5875: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5876: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5877: strcat(fileresprobmorprev,fileresu);
5878: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5879: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5880: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5881: }
5882: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5883: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5884: pstamp(ficresprobmorprev);
5885: 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 5886: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5887: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5888: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5889: }
5890: for(j=1;j<=cptcoveff;j++)
5891: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5892: fprintf(ficresprobmorprev,"\n");
5893:
1.218 brouard 5894: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5895: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5896: fprintf(ficresprobmorprev," p.%-d SE",j);
5897: for(i=1; i<=nlstate;i++)
5898: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5899: }
5900: fprintf(ficresprobmorprev,"\n");
5901:
5902: fprintf(ficgp,"\n# Routine varevsij");
5903: fprintf(ficgp,"\nunset title \n");
5904: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5905: 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");
5906: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 5907:
1.218 brouard 5908: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5909: pstamp(ficresvij);
5910: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5911: if(popbased==1)
5912: 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);
5913: else
5914: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5915: fprintf(ficresvij,"# Age");
5916: for(i=1; i<=nlstate;i++)
5917: for(j=1; j<=nlstate;j++)
5918: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5919: fprintf(ficresvij,"\n");
5920:
5921: xp=vector(1,npar);
5922: dnewm=matrix(1,nlstate,1,npar);
5923: doldm=matrix(1,nlstate,1,nlstate);
5924: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5925: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5926:
5927: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5928: gpp=vector(nlstate+1,nlstate+ndeath);
5929: gmp=vector(nlstate+1,nlstate+ndeath);
5930: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5931:
1.218 brouard 5932: if(estepm < stepm){
5933: printf ("Problem %d lower than %d\n",estepm, stepm);
5934: }
5935: else hstepm=estepm;
5936: /* For example we decided to compute the life expectancy with the smallest unit */
5937: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5938: nhstepm is the number of hstepm from age to agelim
5939: nstepm is the number of stepm from age to agelim.
5940: Look at function hpijx to understand why because of memory size limitations,
5941: we decided (b) to get a life expectancy respecting the most precise curvature of the
5942: survival function given by stepm (the optimization length). Unfortunately it
5943: means that if the survival funtion is printed every two years of age and if
5944: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5945: results. So we changed our mind and took the option of the best precision.
5946: */
5947: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5948: agelim = AGESUP;
5949: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5950: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5951: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5952: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5953: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
5954: gp=matrix(0,nhstepm,1,nlstate);
5955: gm=matrix(0,nhstepm,1,nlstate);
5956:
5957:
5958: for(theta=1; theta <=npar; theta++){
5959: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
5960: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5961: }
1.279 brouard 5962: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
5963: * returns into prlim .
5964: */
1.242 brouard 5965: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 5966:
5967: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 5968: if (popbased==1) {
5969: if(mobilav ==0){
5970: for(i=1; i<=nlstate;i++)
5971: prlim[i][i]=probs[(int)age][i][ij];
5972: }else{ /* mobilav */
5973: for(i=1; i<=nlstate;i++)
5974: prlim[i][i]=mobaverage[(int)age][i][ij];
5975: }
5976: }
1.279 brouard 5977: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}_x\f$ at horizon h.
5978: */
5979: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Returns p3mat[i][j][h] for h=0 to nhstepm */
5980: /**< And for each alive state j, sums over i \f$ w^i_x {}{h}_p^{ij}_x\f$, which are the probability
5981: * at horizon h in state j including mortality.
5982: */
1.218 brouard 5983: for(j=1; j<= nlstate; j++){
5984: for(h=0; h<=nhstepm; h++){
5985: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
5986: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
5987: }
5988: }
1.279 brouard 5989: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 5990: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 5991: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 5992: */
5993: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5994: for(i=1,gpp[j]=0.; i<= nlstate; i++)
5995: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 5996: }
5997:
5998: /* Again with minus shift */
1.218 brouard 5999:
6000: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6001: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6002:
1.242 brouard 6003: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6004:
6005: if (popbased==1) {
6006: if(mobilav ==0){
6007: for(i=1; i<=nlstate;i++)
6008: prlim[i][i]=probs[(int)age][i][ij];
6009: }else{ /* mobilav */
6010: for(i=1; i<=nlstate;i++)
6011: prlim[i][i]=mobaverage[(int)age][i][ij];
6012: }
6013: }
6014:
1.235 brouard 6015: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6016:
6017: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6018: for(h=0; h<=nhstepm; h++){
6019: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6020: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6021: }
6022: }
6023: /* This for computing probability of death (h=1 means
6024: computed over hstepm matrices product = hstepm*stepm months)
6025: as a weighted average of prlim.
6026: */
6027: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6028: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6029: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6030: }
1.279 brouard 6031: /* end shifting computations */
6032:
6033: /**< Computing gradient matrix at horizon h
6034: */
1.218 brouard 6035: for(j=1; j<= nlstate; j++) /* vareij */
6036: for(h=0; h<=nhstepm; h++){
6037: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6038: }
1.279 brouard 6039: /**< Gradient of overall mortality p.3 (or p.j)
6040: */
6041: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6042: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6043: }
6044:
6045: } /* End theta */
1.279 brouard 6046:
6047: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6048: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6049:
6050: for(h=0; h<=nhstepm; h++) /* veij */
6051: for(j=1; j<=nlstate;j++)
6052: for(theta=1; theta <=npar; theta++)
6053: trgradg[h][j][theta]=gradg[h][theta][j];
6054:
6055: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6056: for(theta=1; theta <=npar; theta++)
6057: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6058: /**< as well as its transposed matrix
6059: */
1.218 brouard 6060:
6061: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6062: for(i=1;i<=nlstate;i++)
6063: for(j=1;j<=nlstate;j++)
6064: vareij[i][j][(int)age] =0.;
1.279 brouard 6065:
6066: /* Computing trgradg by matcov by gradg at age and summing over h
6067: * and k (nhstepm) formula 15 of article
6068: * Lievre-Brouard-Heathcote
6069: */
6070:
1.218 brouard 6071: for(h=0;h<=nhstepm;h++){
6072: for(k=0;k<=nhstepm;k++){
6073: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6074: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6075: for(i=1;i<=nlstate;i++)
6076: for(j=1;j<=nlstate;j++)
6077: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6078: }
6079: }
6080:
1.279 brouard 6081: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6082: * p.j overall mortality formula 49 but computed directly because
6083: * we compute the grad (wix pijx) instead of grad (pijx),even if
6084: * wix is independent of theta.
6085: */
1.218 brouard 6086: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6087: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6088: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6089: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6090: varppt[j][i]=doldmp[j][i];
6091: /* end ppptj */
6092: /* x centered again */
6093:
1.242 brouard 6094: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6095:
6096: if (popbased==1) {
6097: if(mobilav ==0){
6098: for(i=1; i<=nlstate;i++)
6099: prlim[i][i]=probs[(int)age][i][ij];
6100: }else{ /* mobilav */
6101: for(i=1; i<=nlstate;i++)
6102: prlim[i][i]=mobaverage[(int)age][i][ij];
6103: }
6104: }
6105:
6106: /* This for computing probability of death (h=1 means
6107: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6108: as a weighted average of prlim.
6109: */
1.235 brouard 6110: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6111: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6112: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6113: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6114: }
6115: /* end probability of death */
6116:
6117: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6118: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6119: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6120: for(i=1; i<=nlstate;i++){
6121: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6122: }
6123: }
6124: fprintf(ficresprobmorprev,"\n");
6125:
6126: fprintf(ficresvij,"%.0f ",age );
6127: for(i=1; i<=nlstate;i++)
6128: for(j=1; j<=nlstate;j++){
6129: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6130: }
6131: fprintf(ficresvij,"\n");
6132: free_matrix(gp,0,nhstepm,1,nlstate);
6133: free_matrix(gm,0,nhstepm,1,nlstate);
6134: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6135: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6136: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6137: } /* End age */
6138: free_vector(gpp,nlstate+1,nlstate+ndeath);
6139: free_vector(gmp,nlstate+1,nlstate+ndeath);
6140: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6141: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6142: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6143: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6144: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6145: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6146: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6147: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6148: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6149: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6150: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6151: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6152: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6153: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6154: 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);
6155: /* 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 6156: */
1.218 brouard 6157: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6158: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6159:
1.218 brouard 6160: free_vector(xp,1,npar);
6161: free_matrix(doldm,1,nlstate,1,nlstate);
6162: free_matrix(dnewm,1,nlstate,1,npar);
6163: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6164: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6165: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6166: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6167: fclose(ficresprobmorprev);
6168: fflush(ficgp);
6169: fflush(fichtm);
6170: } /* end varevsij */
1.126 brouard 6171:
6172: /************ Variance of prevlim ******************/
1.269 brouard 6173: 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 6174: {
1.205 brouard 6175: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6176: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6177:
1.268 brouard 6178: double **dnewmpar,**doldm;
1.126 brouard 6179: int i, j, nhstepm, hstepm;
6180: double *xp;
6181: double *gp, *gm;
6182: double **gradg, **trgradg;
1.208 brouard 6183: double **mgm, **mgp;
1.126 brouard 6184: double age,agelim;
6185: int theta;
6186:
6187: pstamp(ficresvpl);
6188: fprintf(ficresvpl,"# Standard deviation of period (stable) prevalences \n");
1.241 brouard 6189: fprintf(ficresvpl,"# Age ");
6190: if(nresult >=1)
6191: fprintf(ficresvpl," Result# ");
1.126 brouard 6192: for(i=1; i<=nlstate;i++)
6193: fprintf(ficresvpl," %1d-%1d",i,i);
6194: fprintf(ficresvpl,"\n");
6195:
6196: xp=vector(1,npar);
1.268 brouard 6197: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6198: doldm=matrix(1,nlstate,1,nlstate);
6199:
6200: hstepm=1*YEARM; /* Every year of age */
6201: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6202: agelim = AGESUP;
6203: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6204: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6205: if (stepm >= YEARM) hstepm=1;
6206: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6207: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6208: mgp=matrix(1,npar,1,nlstate);
6209: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6210: gp=vector(1,nlstate);
6211: gm=vector(1,nlstate);
6212:
6213: for(theta=1; theta <=npar; theta++){
6214: for(i=1; i<=npar; i++){ /* Computes gradient */
6215: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6216: }
1.209 brouard 6217: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 6218: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 6219: else
1.235 brouard 6220: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6221: for(i=1;i<=nlstate;i++){
1.126 brouard 6222: gp[i] = prlim[i][i];
1.208 brouard 6223: mgp[theta][i] = prlim[i][i];
6224: }
1.126 brouard 6225: for(i=1; i<=npar; i++) /* Computes gradient */
6226: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.209 brouard 6227: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 6228: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 6229: else
1.235 brouard 6230: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6231: for(i=1;i<=nlstate;i++){
1.126 brouard 6232: gm[i] = prlim[i][i];
1.208 brouard 6233: mgm[theta][i] = prlim[i][i];
6234: }
1.126 brouard 6235: for(i=1;i<=nlstate;i++)
6236: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6237: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6238: } /* End theta */
6239:
6240: trgradg =matrix(1,nlstate,1,npar);
6241:
6242: for(j=1; j<=nlstate;j++)
6243: for(theta=1; theta <=npar; theta++)
6244: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6245: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6246: /* printf("\nmgm mgp %d ",(int)age); */
6247: /* for(j=1; j<=nlstate;j++){ */
6248: /* printf(" %d ",j); */
6249: /* for(theta=1; theta <=npar; theta++) */
6250: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6251: /* printf("\n "); */
6252: /* } */
6253: /* } */
6254: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6255: /* printf("\n gradg %d ",(int)age); */
6256: /* for(j=1; j<=nlstate;j++){ */
6257: /* printf("%d ",j); */
6258: /* for(theta=1; theta <=npar; theta++) */
6259: /* printf("%d %lf ",theta,gradg[theta][j]); */
6260: /* printf("\n "); */
6261: /* } */
6262: /* } */
1.126 brouard 6263:
6264: for(i=1;i<=nlstate;i++)
6265: varpl[i][(int)age] =0.;
1.209 brouard 6266: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6267: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6268: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6269: }else{
1.268 brouard 6270: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6271: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6272: }
1.126 brouard 6273: for(i=1;i<=nlstate;i++)
6274: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6275:
6276: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6277: if(nresult >=1)
6278: fprintf(ficresvpl,"%d ",nres );
1.126 brouard 6279: for(i=1; i<=nlstate;i++)
6280: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
6281: fprintf(ficresvpl,"\n");
6282: free_vector(gp,1,nlstate);
6283: free_vector(gm,1,nlstate);
1.208 brouard 6284: free_matrix(mgm,1,npar,1,nlstate);
6285: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6286: free_matrix(gradg,1,npar,1,nlstate);
6287: free_matrix(trgradg,1,nlstate,1,npar);
6288: } /* End age */
6289:
6290: free_vector(xp,1,npar);
6291: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6292: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6293:
6294: }
6295:
6296:
6297: /************ Variance of backprevalence limit ******************/
1.269 brouard 6298: 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 6299: {
6300: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6301: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6302:
6303: double **dnewmpar,**doldm;
6304: int i, j, nhstepm, hstepm;
6305: double *xp;
6306: double *gp, *gm;
6307: double **gradg, **trgradg;
6308: double **mgm, **mgp;
6309: double age,agelim;
6310: int theta;
6311:
6312: pstamp(ficresvbl);
6313: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6314: fprintf(ficresvbl,"# Age ");
6315: if(nresult >=1)
6316: fprintf(ficresvbl," Result# ");
6317: for(i=1; i<=nlstate;i++)
6318: fprintf(ficresvbl," %1d-%1d",i,i);
6319: fprintf(ficresvbl,"\n");
6320:
6321: xp=vector(1,npar);
6322: dnewmpar=matrix(1,nlstate,1,npar);
6323: doldm=matrix(1,nlstate,1,nlstate);
6324:
6325: hstepm=1*YEARM; /* Every year of age */
6326: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6327: agelim = AGEINF;
6328: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6329: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6330: if (stepm >= YEARM) hstepm=1;
6331: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6332: gradg=matrix(1,npar,1,nlstate);
6333: mgp=matrix(1,npar,1,nlstate);
6334: mgm=matrix(1,npar,1,nlstate);
6335: gp=vector(1,nlstate);
6336: gm=vector(1,nlstate);
6337:
6338: for(theta=1; theta <=npar; theta++){
6339: for(i=1; i<=npar; i++){ /* Computes gradient */
6340: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6341: }
6342: if(mobilavproj > 0 )
6343: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6344: else
6345: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6346: for(i=1;i<=nlstate;i++){
6347: gp[i] = bprlim[i][i];
6348: mgp[theta][i] = bprlim[i][i];
6349: }
6350: for(i=1; i<=npar; i++) /* Computes gradient */
6351: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6352: if(mobilavproj > 0 )
6353: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6354: else
6355: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6356: for(i=1;i<=nlstate;i++){
6357: gm[i] = bprlim[i][i];
6358: mgm[theta][i] = bprlim[i][i];
6359: }
6360: for(i=1;i<=nlstate;i++)
6361: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6362: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6363: } /* End theta */
6364:
6365: trgradg =matrix(1,nlstate,1,npar);
6366:
6367: for(j=1; j<=nlstate;j++)
6368: for(theta=1; theta <=npar; theta++)
6369: trgradg[j][theta]=gradg[theta][j];
6370: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6371: /* printf("\nmgm mgp %d ",(int)age); */
6372: /* for(j=1; j<=nlstate;j++){ */
6373: /* printf(" %d ",j); */
6374: /* for(theta=1; theta <=npar; theta++) */
6375: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6376: /* printf("\n "); */
6377: /* } */
6378: /* } */
6379: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6380: /* printf("\n gradg %d ",(int)age); */
6381: /* for(j=1; j<=nlstate;j++){ */
6382: /* printf("%d ",j); */
6383: /* for(theta=1; theta <=npar; theta++) */
6384: /* printf("%d %lf ",theta,gradg[theta][j]); */
6385: /* printf("\n "); */
6386: /* } */
6387: /* } */
6388:
6389: for(i=1;i<=nlstate;i++)
6390: varbpl[i][(int)age] =0.;
6391: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6392: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6393: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6394: }else{
6395: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6396: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6397: }
6398: for(i=1;i<=nlstate;i++)
6399: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6400:
6401: fprintf(ficresvbl,"%.0f ",age );
6402: if(nresult >=1)
6403: fprintf(ficresvbl,"%d ",nres );
6404: for(i=1; i<=nlstate;i++)
6405: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6406: fprintf(ficresvbl,"\n");
6407: free_vector(gp,1,nlstate);
6408: free_vector(gm,1,nlstate);
6409: free_matrix(mgm,1,npar,1,nlstate);
6410: free_matrix(mgp,1,npar,1,nlstate);
6411: free_matrix(gradg,1,npar,1,nlstate);
6412: free_matrix(trgradg,1,nlstate,1,npar);
6413: } /* End age */
6414:
6415: free_vector(xp,1,npar);
6416: free_matrix(doldm,1,nlstate,1,npar);
6417: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6418:
6419: }
6420:
6421: /************ Variance of one-step probabilities ******************/
6422: 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 6423: {
6424: int i, j=0, k1, l1, tj;
6425: int k2, l2, j1, z1;
6426: int k=0, l;
6427: int first=1, first1, first2;
6428: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6429: double **dnewm,**doldm;
6430: double *xp;
6431: double *gp, *gm;
6432: double **gradg, **trgradg;
6433: double **mu;
6434: double age, cov[NCOVMAX+1];
6435: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6436: int theta;
6437: char fileresprob[FILENAMELENGTH];
6438: char fileresprobcov[FILENAMELENGTH];
6439: char fileresprobcor[FILENAMELENGTH];
6440: double ***varpij;
6441:
6442: strcpy(fileresprob,"PROB_");
6443: strcat(fileresprob,fileres);
6444: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6445: printf("Problem with resultfile: %s\n", fileresprob);
6446: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6447: }
6448: strcpy(fileresprobcov,"PROBCOV_");
6449: strcat(fileresprobcov,fileresu);
6450: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6451: printf("Problem with resultfile: %s\n", fileresprobcov);
6452: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6453: }
6454: strcpy(fileresprobcor,"PROBCOR_");
6455: strcat(fileresprobcor,fileresu);
6456: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6457: printf("Problem with resultfile: %s\n", fileresprobcor);
6458: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6459: }
6460: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6461: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6462: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6463: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6464: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6465: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6466: pstamp(ficresprob);
6467: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6468: fprintf(ficresprob,"# Age");
6469: pstamp(ficresprobcov);
6470: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6471: fprintf(ficresprobcov,"# Age");
6472: pstamp(ficresprobcor);
6473: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6474: fprintf(ficresprobcor,"# Age");
1.126 brouard 6475:
6476:
1.222 brouard 6477: for(i=1; i<=nlstate;i++)
6478: for(j=1; j<=(nlstate+ndeath);j++){
6479: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6480: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6481: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6482: }
6483: /* fprintf(ficresprob,"\n");
6484: fprintf(ficresprobcov,"\n");
6485: fprintf(ficresprobcor,"\n");
6486: */
6487: xp=vector(1,npar);
6488: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6489: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6490: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6491: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6492: first=1;
6493: fprintf(ficgp,"\n# Routine varprob");
6494: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6495: fprintf(fichtm,"\n");
6496:
1.266 brouard 6497: 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. %s</li>\n",optionfilehtmcov,optionfilehtmcov);
1.222 brouard 6498: 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);
6499: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6500: and drawn. It helps understanding how is the covariance between two incidences.\
6501: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6502: 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 6503: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6504: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6505: standard deviations wide on each axis. <br>\
6506: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6507: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6508: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6509:
1.222 brouard 6510: cov[1]=1;
6511: /* tj=cptcoveff; */
1.225 brouard 6512: tj = (int) pow(2,cptcoveff);
1.222 brouard 6513: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6514: j1=0;
1.224 brouard 6515: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6516: if (cptcovn>0) {
6517: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6518: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6519: fprintf(ficresprob, "**********\n#\n");
6520: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6521: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6522: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6523:
1.222 brouard 6524: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6525: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6526: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6527:
6528:
1.222 brouard 6529: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6530: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6531: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6532:
1.222 brouard 6533: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6534: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6535: fprintf(ficresprobcor, "**********\n#");
6536: if(invalidvarcomb[j1]){
6537: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6538: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6539: continue;
6540: }
6541: }
6542: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6543: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6544: gp=vector(1,(nlstate)*(nlstate+ndeath));
6545: gm=vector(1,(nlstate)*(nlstate+ndeath));
6546: for (age=bage; age<=fage; age ++){
6547: cov[2]=age;
6548: if(nagesqr==1)
6549: cov[3]= age*age;
6550: for (k=1; k<=cptcovn;k++) {
6551: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6552: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6553: * 1 1 1 1 1
6554: * 2 2 1 1 1
6555: * 3 1 2 1 1
6556: */
6557: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6558: }
6559: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6560: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6561: for (k=1; k<=cptcovprod;k++)
6562: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6563:
6564:
1.222 brouard 6565: for(theta=1; theta <=npar; theta++){
6566: for(i=1; i<=npar; i++)
6567: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6568:
1.222 brouard 6569: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6570:
1.222 brouard 6571: k=0;
6572: for(i=1; i<= (nlstate); i++){
6573: for(j=1; j<=(nlstate+ndeath);j++){
6574: k=k+1;
6575: gp[k]=pmmij[i][j];
6576: }
6577: }
1.220 brouard 6578:
1.222 brouard 6579: for(i=1; i<=npar; i++)
6580: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6581:
1.222 brouard 6582: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6583: k=0;
6584: for(i=1; i<=(nlstate); i++){
6585: for(j=1; j<=(nlstate+ndeath);j++){
6586: k=k+1;
6587: gm[k]=pmmij[i][j];
6588: }
6589: }
1.220 brouard 6590:
1.222 brouard 6591: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6592: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6593: }
1.126 brouard 6594:
1.222 brouard 6595: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6596: for(theta=1; theta <=npar; theta++)
6597: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6598:
1.222 brouard 6599: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6600: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6601:
1.222 brouard 6602: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6603:
1.222 brouard 6604: k=0;
6605: for(i=1; i<=(nlstate); i++){
6606: for(j=1; j<=(nlstate+ndeath);j++){
6607: k=k+1;
6608: mu[k][(int) age]=pmmij[i][j];
6609: }
6610: }
6611: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6612: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6613: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6614:
1.222 brouard 6615: /*printf("\n%d ",(int)age);
6616: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6617: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6618: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6619: }*/
1.220 brouard 6620:
1.222 brouard 6621: fprintf(ficresprob,"\n%d ",(int)age);
6622: fprintf(ficresprobcov,"\n%d ",(int)age);
6623: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6624:
1.222 brouard 6625: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6626: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6627: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6628: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6629: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6630: }
6631: i=0;
6632: for (k=1; k<=(nlstate);k++){
6633: for (l=1; l<=(nlstate+ndeath);l++){
6634: i++;
6635: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6636: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6637: for (j=1; j<=i;j++){
6638: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6639: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6640: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6641: }
6642: }
6643: }/* end of loop for state */
6644: } /* end of loop for age */
6645: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6646: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6647: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6648: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6649:
6650: /* Confidence intervalle of pij */
6651: /*
6652: fprintf(ficgp,"\nunset parametric;unset label");
6653: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6654: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6655: 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);
6656: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6657: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6658: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6659: */
6660:
6661: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6662: first1=1;first2=2;
6663: for (k2=1; k2<=(nlstate);k2++){
6664: for (l2=1; l2<=(nlstate+ndeath);l2++){
6665: if(l2==k2) continue;
6666: j=(k2-1)*(nlstate+ndeath)+l2;
6667: for (k1=1; k1<=(nlstate);k1++){
6668: for (l1=1; l1<=(nlstate+ndeath);l1++){
6669: if(l1==k1) continue;
6670: i=(k1-1)*(nlstate+ndeath)+l1;
6671: if(i<=j) continue;
6672: for (age=bage; age<=fage; age ++){
6673: if ((int)age %5==0){
6674: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6675: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6676: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6677: mu1=mu[i][(int) age]/stepm*YEARM ;
6678: mu2=mu[j][(int) age]/stepm*YEARM;
6679: c12=cv12/sqrt(v1*v2);
6680: /* Computing eigen value of matrix of covariance */
6681: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6682: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6683: if ((lc2 <0) || (lc1 <0) ){
6684: if(first2==1){
6685: first1=0;
6686: 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);
6687: }
6688: 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);
6689: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6690: /* lc2=fabs(lc2); */
6691: }
1.220 brouard 6692:
1.222 brouard 6693: /* Eigen vectors */
1.280 brouard 6694: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
6695: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6696: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6697: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
6698: }else
6699: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 6700: /*v21=sqrt(1.-v11*v11); *//* error */
6701: v21=(lc1-v1)/cv12*v11;
6702: v12=-v21;
6703: v22=v11;
6704: tnalp=v21/v11;
6705: if(first1==1){
6706: first1=0;
6707: 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);
6708: }
6709: 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);
6710: /*printf(fignu*/
6711: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6712: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6713: if(first==1){
6714: first=0;
6715: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6716: fprintf(ficgp,"\nset parametric;unset label");
6717: 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);
6718: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6719: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6720: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6721: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6722: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6723: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6724: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6725: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6726: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6727: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6728: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6729: 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 6730: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
6731: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6732: }else{
6733: first=0;
6734: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6735: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6736: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6737: 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 6738: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6739: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6740: }/* if first */
6741: } /* age mod 5 */
6742: } /* end loop age */
6743: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6744: first=1;
6745: } /*l12 */
6746: } /* k12 */
6747: } /*l1 */
6748: }/* k1 */
6749: } /* loop on combination of covariates j1 */
6750: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6751: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6752: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6753: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6754: free_vector(xp,1,npar);
6755: fclose(ficresprob);
6756: fclose(ficresprobcov);
6757: fclose(ficresprobcor);
6758: fflush(ficgp);
6759: fflush(fichtmcov);
6760: }
1.126 brouard 6761:
6762:
6763: /******************* Printing html file ***********/
1.201 brouard 6764: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6765: int lastpass, int stepm, int weightopt, char model[],\
6766: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.258 brouard 6767: int popforecast, int mobilav, int prevfcast, int mobilavproj, int backcast, int estepm , \
1.273 brouard 6768: double jprev1, double mprev1,double anprev1, double dateprev1, double dateproj1, double dateback1, \
6769: double jprev2, double mprev2,double anprev2, double dateprev2, double dateproj2, double dateback2){
1.237 brouard 6770: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6771:
6772: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6773: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6774: </ul>");
1.237 brouard 6775: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6776: </ul>", model);
1.214 brouard 6777: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6778: 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",
6779: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6780: 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 6781: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6782: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6783: fprintf(fichtm,"\
6784: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6785: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6786: fprintf(fichtm,"\
1.217 brouard 6787: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6788: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6789: fprintf(fichtm,"\
1.126 brouard 6790: - Period (stable) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6791: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6792: fprintf(fichtm,"\
1.217 brouard 6793: - Period (stable) back prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
6794: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6795: fprintf(fichtm,"\
1.211 brouard 6796: - (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 6797: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6798: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6799: if(prevfcast==1){
6800: fprintf(fichtm,"\
6801: - Prevalence projections by age and states: \
1.201 brouard 6802: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6803: }
1.126 brouard 6804:
6805:
1.225 brouard 6806: m=pow(2,cptcoveff);
1.222 brouard 6807: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6808:
1.264 brouard 6809: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6810:
6811: jj1=0;
6812:
6813: fprintf(fichtm," \n<ul>");
6814: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6815: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6816: if(m != 1 && TKresult[nres]!= k1)
6817: continue;
6818: jj1++;
6819: if (cptcovn > 0) {
6820: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6821: for (cpt=1; cpt<=cptcoveff;cpt++){
6822: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6823: }
6824: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6825: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6826: }
6827: fprintf(fichtm,"\">");
6828:
6829: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6830: fprintf(fichtm,"************ Results for covariates");
6831: for (cpt=1; cpt<=cptcoveff;cpt++){
6832: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6833: }
6834: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6835: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6836: }
6837: if(invalidvarcomb[k1]){
6838: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
6839: continue;
6840: }
6841: fprintf(fichtm,"</a></li>");
6842: } /* cptcovn >0 */
6843: }
6844: fprintf(fichtm," \n</ul>");
6845:
1.222 brouard 6846: jj1=0;
1.237 brouard 6847:
6848: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6849: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6850: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6851: continue;
1.220 brouard 6852:
1.222 brouard 6853: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6854: jj1++;
6855: if (cptcovn > 0) {
1.264 brouard 6856: fprintf(fichtm,"\n<p><a name=\"rescov");
6857: for (cpt=1; cpt<=cptcoveff;cpt++){
6858: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6859: }
6860: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6861: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6862: }
6863: fprintf(fichtm,"\"</a>");
6864:
1.222 brouard 6865: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6866: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6867: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6868: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6869: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6870: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6871: }
1.237 brouard 6872: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6873: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6874: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6875: }
6876:
1.230 brouard 6877: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6878: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6879: if(invalidvarcomb[k1]){
6880: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6881: printf("\nCombination (%d) ignored because no cases \n",k1);
6882: continue;
6883: }
6884: }
6885: /* aij, bij */
1.259 brouard 6886: 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 6887: <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 6888: /* Pij */
1.241 brouard 6889: 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> \
6890: <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 6891: /* Quasi-incidences */
6892: 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 6893: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6894: 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 6895: 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> \
6896: <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 6897: /* Survival functions (period) in state j */
6898: for(cpt=1; cpt<=nlstate;cpt++){
1.241 brouard 6899: 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> \
6900: <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 6901: }
6902: /* State specific survival functions (period) */
6903: for(cpt=1; cpt<=nlstate;cpt++){
6904: fprintf(fichtm,"<br>\n- Survival functions from state %d in each live state and total.\
1.220 brouard 6905: Or probability to survive in various states (1 to %d) being in state %d at different ages. \
1.283 brouard 6906: <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 6907: }
6908: /* Period (stable) prevalence in each health state */
6909: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6910: 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> \
6911: <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 6912: }
6913: if(backcast==1){
6914: /* Period (stable) back prevalence in each health state */
6915: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6916: 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 6917: <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 6918: }
1.217 brouard 6919: }
1.222 brouard 6920: if(prevfcast==1){
6921: /* Projection of prevalence up to period (stable) prevalence in each health state */
6922: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 6923: 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) 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> \
6924: <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 6925: }
6926: }
1.268 brouard 6927: if(backcast==1){
6928: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
6929: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 6930: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
6931: 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 \
6932: 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) \
6933: with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
6934: <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 6935: }
6936: }
1.220 brouard 6937:
1.222 brouard 6938: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 6939: 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> \
6940: <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 6941: }
6942: /* } /\* end i1 *\/ */
6943: }/* End k1 */
6944: fprintf(fichtm,"</ul>");
1.126 brouard 6945:
1.222 brouard 6946: fprintf(fichtm,"\
1.126 brouard 6947: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 6948: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 6949: - 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 6950: But because parameters are usually highly correlated (a higher incidence of disability \
6951: and a higher incidence of recovery can give very close observed transition) it might \
6952: be very useful to look not only at linear confidence intervals estimated from the \
6953: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
6954: (parameters) of the logistic regression, it might be more meaningful to visualize the \
6955: covariance matrix of the one-step probabilities. \
6956: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 6957:
1.222 brouard 6958: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
6959: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
6960: fprintf(fichtm,"\
1.126 brouard 6961: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6962: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 6963:
1.222 brouard 6964: fprintf(fichtm,"\
1.126 brouard 6965: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6966: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
6967: fprintf(fichtm,"\
1.126 brouard 6968: - 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): \
6969: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6970: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 6971: fprintf(fichtm,"\
1.126 brouard 6972: - (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): \
6973: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6974: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 6975: fprintf(fichtm,"\
1.128 brouard 6976: - Variances and covariances of health expectancies by age. Status (i) based health expectancies (in state j), e<sup>ij</sup> are weighted by the 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 6977: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
6978: fprintf(fichtm,"\
1.128 brouard 6979: - 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 6980: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
6981: fprintf(fichtm,"\
1.126 brouard 6982: - Standard deviation of period (stable) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 6983: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 6984:
6985: /* if(popforecast==1) fprintf(fichtm,"\n */
6986: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
6987: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
6988: /* <br>",fileres,fileres,fileres,fileres); */
6989: /* else */
6990: /* 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 6991: fflush(fichtm);
6992: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 6993:
1.225 brouard 6994: m=pow(2,cptcoveff);
1.222 brouard 6995: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6996:
1.222 brouard 6997: jj1=0;
1.237 brouard 6998:
1.241 brouard 6999: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7000: for(k1=1; k1<=m;k1++){
1.253 brouard 7001: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7002: continue;
1.222 brouard 7003: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7004: jj1++;
1.126 brouard 7005: if (cptcovn > 0) {
7006: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7007: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 7008: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
7009: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7010: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7011: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7012: }
7013:
1.126 brouard 7014: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 7015:
1.222 brouard 7016: if(invalidvarcomb[k1]){
7017: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7018: continue;
7019: }
1.126 brouard 7020: }
7021: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7022: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 7023: 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 7024: <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 7025: }
7026: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 7027: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
7028: true period expectancies (those weighted with period prevalences are also\
7029: drawn in addition to the population based expectancies computed using\
1.241 brouard 7030: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
7031: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7032: /* } /\* end i1 *\/ */
7033: }/* End k1 */
1.241 brouard 7034: }/* End nres */
1.222 brouard 7035: fprintf(fichtm,"</ul>");
7036: fflush(fichtm);
1.126 brouard 7037: }
7038:
7039: /******************* Gnuplot file **************/
1.270 brouard 7040: 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 7041:
7042: char dirfileres[132],optfileres[132];
1.264 brouard 7043: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7044: 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 7045: int lv=0, vlv=0, kl=0;
1.130 brouard 7046: int ng=0;
1.201 brouard 7047: int vpopbased;
1.223 brouard 7048: int ioffset; /* variable offset for columns */
1.270 brouard 7049: int iyearc=1; /* variable column for year of projection */
7050: int iagec=1; /* variable column for age of projection */
1.235 brouard 7051: int nres=0; /* Index of resultline */
1.266 brouard 7052: int istart=1; /* For starting graphs in projections */
1.219 brouard 7053:
1.126 brouard 7054: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7055: /* printf("Problem with file %s",optionfilegnuplot); */
7056: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7057: /* } */
7058:
7059: /*#ifdef windows */
7060: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7061: /*#endif */
1.225 brouard 7062: m=pow(2,cptcoveff);
1.126 brouard 7063:
1.274 brouard 7064: /* diagram of the model */
7065: fprintf(ficgp,"\n#Diagram of the model \n");
7066: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7067: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7068: 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);
7069:
7070: 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);
7071: fprintf(ficgp,"\n#show arrow\nunset label\n");
7072: 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);
7073: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7074: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7075: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7076: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7077:
1.202 brouard 7078: /* Contribution to likelihood */
7079: /* Plot the probability implied in the likelihood */
1.223 brouard 7080: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7081: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7082: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7083: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7084: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7085: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7086: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7087: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7088: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7089: 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));
7090: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7091: 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));
7092: for (i=1; i<= nlstate ; i ++) {
7093: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7094: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7095: 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);
7096: for (j=2; j<= nlstate+ndeath ; j ++) {
7097: 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);
7098: }
7099: fprintf(ficgp,";\nset out; unset ylabel;\n");
7100: }
7101: /* 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 */
7102: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7103: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7104: fprintf(ficgp,"\nset out;unset log\n");
7105: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7106:
1.126 brouard 7107: strcpy(dirfileres,optionfilefiname);
7108: strcpy(optfileres,"vpl");
1.223 brouard 7109: /* 1eme*/
1.238 brouard 7110: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7111: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7112: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7113: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7114: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7115: continue;
7116: /* We are interested in selected combination by the resultline */
1.246 brouard 7117: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.238 brouard 7118: fprintf(ficgp,"\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7119: strcpy(gplotlabel,"(");
1.238 brouard 7120: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7121: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7122: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7123: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7124: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7125: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7126: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7127: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7128: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7129: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7130: }
7131: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7132: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7133: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7134: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7135: }
7136: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7137: /* printf("\n#\n"); */
1.238 brouard 7138: fprintf(ficgp,"\n#\n");
7139: if(invalidvarcomb[k1]){
1.260 brouard 7140: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7141: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7142: continue;
7143: }
1.235 brouard 7144:
1.241 brouard 7145: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7146: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7147: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
7148: fprintf(ficgp,"set title \"Alive state %d %s\" font \"Helvetica,12\"\n",cpt,gplotlabel);
1.260 brouard 7149: 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);
7150: /* 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); */
7151: /* k1-1 error should be nres-1*/
1.238 brouard 7152: for (i=1; i<= nlstate ; i ++) {
7153: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7154: else fprintf(ficgp," %%*lf (%%*lf)");
7155: }
1.260 brouard 7156: fprintf(ficgp,"\" t\"Period (stable) 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 7157: for (i=1; i<= nlstate ; i ++) {
7158: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7159: else fprintf(ficgp," %%*lf (%%*lf)");
7160: }
1.260 brouard 7161: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7162: for (i=1; i<= nlstate ; i ++) {
7163: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7164: else fprintf(ficgp," %%*lf (%%*lf)");
7165: }
1.265 brouard 7166: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7167:
7168: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7169: if(cptcoveff ==0){
1.271 brouard 7170: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7171: }else{
7172: kl=0;
7173: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7174: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7175: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7176: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7177: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7178: vlv= nbcode[Tvaraff[k]][lv];
7179: kl++;
7180: /* 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 *\/ */
7181: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7182: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7183: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7184: if(k==cptcoveff){
7185: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7186: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7187: }else{
7188: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7189: kl++;
7190: }
7191: } /* end covariate */
7192: } /* end if no covariate */
7193:
1.238 brouard 7194: if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
7195: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7196: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7197: if(cptcoveff ==0){
1.245 brouard 7198: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7199: }else{
7200: kl=0;
7201: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7202: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7203: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7204: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7205: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7206: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7207: kl++;
1.238 brouard 7208: /* 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 *\/ */
7209: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7210: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7211: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7212: if(k==cptcoveff){
1.245 brouard 7213: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7214: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7215: }else{
7216: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7217: kl++;
7218: }
7219: } /* end covariate */
7220: } /* end if no covariate */
1.268 brouard 7221: if(backcast == 1){
7222: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7223: /* k1-1 error should be nres-1*/
7224: for (i=1; i<= nlstate ; i ++) {
7225: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7226: else fprintf(ficgp," %%*lf (%%*lf)");
7227: }
1.271 brouard 7228: 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 7229: for (i=1; i<= nlstate ; i ++) {
7230: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7231: else fprintf(ficgp," %%*lf (%%*lf)");
7232: }
1.276 brouard 7233: 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 7234: for (i=1; i<= nlstate ; i ++) {
7235: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7236: else fprintf(ficgp," %%*lf (%%*lf)");
7237: }
1.274 brouard 7238: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7239: } /* end if backprojcast */
1.238 brouard 7240: } /* end if backcast */
1.276 brouard 7241: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7242: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7243: } /* nres */
1.201 brouard 7244: } /* k1 */
7245: } /* cpt */
1.235 brouard 7246:
7247:
1.126 brouard 7248: /*2 eme*/
1.238 brouard 7249: for (k1=1; k1<= m ; k1 ++){
7250: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7251: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7252: continue;
7253: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7254: strcpy(gplotlabel,"(");
1.238 brouard 7255: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7256: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7257: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7258: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7259: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7260: vlv= nbcode[Tvaraff[k]][lv];
7261: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7262: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7263: }
1.237 brouard 7264: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7265: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7266: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7267: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7268: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7269: }
1.264 brouard 7270: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7271: fprintf(ficgp,"\n#\n");
1.223 brouard 7272: if(invalidvarcomb[k1]){
7273: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7274: continue;
7275: }
1.219 brouard 7276:
1.241 brouard 7277: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7278: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7279: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7280: if(vpopbased==0){
1.238 brouard 7281: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7282: }else
1.238 brouard 7283: fprintf(ficgp,"\nreplot ");
7284: for (i=1; i<= nlstate+1 ; i ++) {
7285: k=2*i;
1.261 brouard 7286: 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 7287: for (j=1; j<= nlstate+1 ; j ++) {
7288: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7289: else fprintf(ficgp," %%*lf (%%*lf)");
7290: }
7291: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7292: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7293: 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 7294: for (j=1; j<= nlstate+1 ; j ++) {
7295: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7296: else fprintf(ficgp," %%*lf (%%*lf)");
7297: }
7298: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7299: 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 7300: for (j=1; j<= nlstate+1 ; j ++) {
7301: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7302: else fprintf(ficgp," %%*lf (%%*lf)");
7303: }
7304: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7305: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7306: } /* state */
7307: } /* vpopbased */
1.264 brouard 7308: 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 7309: } /* end nres */
7310: } /* k1 end 2 eme*/
7311:
7312:
7313: /*3eme*/
7314: for (k1=1; k1<= m ; k1 ++){
7315: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7316: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7317: continue;
7318:
7319: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7320: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7321: strcpy(gplotlabel,"(");
1.238 brouard 7322: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7323: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7324: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7325: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7326: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7327: vlv= nbcode[Tvaraff[k]][lv];
7328: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7329: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7330: }
7331: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7332: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7333: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7334: }
1.264 brouard 7335: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7336: fprintf(ficgp,"\n#\n");
7337: if(invalidvarcomb[k1]){
7338: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7339: continue;
7340: }
7341:
7342: /* k=2+nlstate*(2*cpt-2); */
7343: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7344: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7345: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7346: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7347: 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 7348: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7349: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7350: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7351: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7352: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7353: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7354:
1.238 brouard 7355: */
7356: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7357: 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 7358: /* 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 7359:
1.238 brouard 7360: }
1.261 brouard 7361: 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 7362: }
1.264 brouard 7363: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7364: } /* end nres */
7365: } /* end kl 3eme */
1.126 brouard 7366:
1.223 brouard 7367: /* 4eme */
1.201 brouard 7368: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7369: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7370: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7371: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7372: continue;
1.238 brouard 7373: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7374: strcpy(gplotlabel,"(");
1.238 brouard 7375: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7376: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7377: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7378: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7379: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7380: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7381: vlv= nbcode[Tvaraff[k]][lv];
7382: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7383: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7384: }
7385: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7386: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7387: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7388: }
1.264 brouard 7389: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7390: fprintf(ficgp,"\n#\n");
7391: if(invalidvarcomb[k1]){
7392: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7393: continue;
1.223 brouard 7394: }
1.238 brouard 7395:
1.241 brouard 7396: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7397: 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 7398: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7399: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7400: k=3;
7401: for (i=1; i<= nlstate ; i ++){
7402: if(i==1){
7403: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7404: }else{
7405: fprintf(ficgp,", '' ");
7406: }
7407: l=(nlstate+ndeath)*(i-1)+1;
7408: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7409: for (j=2; j<= nlstate+ndeath ; j ++)
7410: fprintf(ficgp,"+$%d",k+l+j-1);
7411: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7412: } /* nlstate */
1.264 brouard 7413: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7414: } /* end cpt state*/
7415: } /* end nres */
7416: } /* end covariate k1 */
7417:
1.220 brouard 7418: /* 5eme */
1.201 brouard 7419: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7420: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7421: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7422: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7423: continue;
1.238 brouard 7424: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7425: strcpy(gplotlabel,"(");
1.238 brouard 7426: 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);
7427: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7428: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7429: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7430: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7431: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7432: vlv= nbcode[Tvaraff[k]][lv];
7433: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7434: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7435: }
7436: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7437: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7438: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7439: }
1.264 brouard 7440: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7441: fprintf(ficgp,"\n#\n");
7442: if(invalidvarcomb[k1]){
7443: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7444: continue;
7445: }
1.227 brouard 7446:
1.241 brouard 7447: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7448: 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 7449: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7450: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7451: k=3;
7452: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7453: if(j==1)
7454: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7455: else
7456: fprintf(ficgp,", '' ");
7457: l=(nlstate+ndeath)*(cpt-1) +j;
7458: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7459: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7460: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7461: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7462: } /* nlstate */
7463: fprintf(ficgp,", '' ");
7464: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7465: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7466: l=(nlstate+ndeath)*(cpt-1) +j;
7467: if(j < nlstate)
7468: fprintf(ficgp,"$%d +",k+l);
7469: else
7470: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7471: }
1.264 brouard 7472: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7473: } /* end cpt state*/
7474: } /* end covariate */
7475: } /* end nres */
1.227 brouard 7476:
1.220 brouard 7477: /* 6eme */
1.202 brouard 7478: /* CV preval stable (period) for each covariate */
1.237 brouard 7479: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7480: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7481: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7482: continue;
1.255 brouard 7483: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7484: strcpy(gplotlabel,"(");
1.211 brouard 7485: fprintf(ficgp,"\n#\n#\n#CV preval stable (period): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7486: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7487: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7488: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7489: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7490: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7491: vlv= nbcode[Tvaraff[k]][lv];
7492: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7493: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7494: }
1.237 brouard 7495: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7496: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7497: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7498: }
1.264 brouard 7499: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7500: fprintf(ficgp,"\n#\n");
1.223 brouard 7501: if(invalidvarcomb[k1]){
1.227 brouard 7502: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7503: continue;
1.223 brouard 7504: }
1.227 brouard 7505:
1.241 brouard 7506: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7507: 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 7508: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7509: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7510: k=3; /* Offset */
1.255 brouard 7511: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7512: if(i==1)
7513: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7514: else
7515: fprintf(ficgp,", '' ");
1.255 brouard 7516: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7517: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7518: for (j=2; j<= nlstate ; j ++)
7519: fprintf(ficgp,"+$%d",k+l+j-1);
7520: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7521: } /* nlstate */
1.264 brouard 7522: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7523: } /* end cpt state*/
7524: } /* end covariate */
1.227 brouard 7525:
7526:
1.220 brouard 7527: /* 7eme */
1.218 brouard 7528: if(backcast == 1){
1.217 brouard 7529: /* CV back preval stable (period) for each covariate */
1.237 brouard 7530: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7531: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7532: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7533: continue;
1.268 brouard 7534: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7535: strcpy(gplotlabel,"(");
7536: fprintf(ficgp,"\n#\n#\n#CV Back preval stable (period): 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7537: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7538: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7539: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7540: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7541: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7542: vlv= nbcode[Tvaraff[k]][lv];
7543: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7544: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7545: }
1.237 brouard 7546: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7547: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7548: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7549: }
1.264 brouard 7550: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7551: fprintf(ficgp,"\n#\n");
7552: if(invalidvarcomb[k1]){
7553: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7554: continue;
7555: }
7556:
1.241 brouard 7557: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7558: 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 7559: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7560: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7561: k=3; /* Offset */
1.268 brouard 7562: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7563: if(i==1)
7564: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7565: else
7566: fprintf(ficgp,", '' ");
7567: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7568: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7569: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7570: /* 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 7571: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7572: /* for (j=2; j<= nlstate ; j ++) */
7573: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7574: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7575: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7576: } /* nlstate */
1.264 brouard 7577: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7578: } /* end cpt state*/
7579: } /* end covariate */
7580: } /* End if backcast */
7581:
1.223 brouard 7582: /* 8eme */
1.218 brouard 7583: if(prevfcast==1){
7584: /* Projection from cross-sectional to stable (period) for each covariate */
7585:
1.237 brouard 7586: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7587: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7588: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7589: continue;
1.211 brouard 7590: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7591: strcpy(gplotlabel,"(");
1.227 brouard 7592: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to stable (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
7593: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7594: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7595: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7596: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7597: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7598: vlv= nbcode[Tvaraff[k]][lv];
7599: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7600: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7601: }
1.237 brouard 7602: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7603: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7604: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7605: }
1.264 brouard 7606: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7607: fprintf(ficgp,"\n#\n");
7608: if(invalidvarcomb[k1]){
7609: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7610: continue;
7611: }
7612:
7613: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7614: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7615: 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 7616: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7617: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7618:
7619: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7620: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7621: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7622: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7623: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7624: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7625: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7626: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7627: if(i==istart){
1.227 brouard 7628: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7629: }else{
7630: fprintf(ficgp,",\\\n '' ");
7631: }
7632: if(cptcoveff ==0){ /* No covariate */
7633: ioffset=2; /* Age is in 2 */
7634: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7635: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7636: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7637: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7638: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7639: if(i==nlstate+1){
1.270 brouard 7640: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 7641: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7642: fprintf(ficgp,",\\\n '' ");
7643: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7644: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 7645: offyear, \
1.268 brouard 7646: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7647: }else
1.227 brouard 7648: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7649: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7650: }else{ /* more than 2 covariates */
1.270 brouard 7651: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7652: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7653: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7654: iyearc=ioffset-1;
7655: iagec=ioffset;
1.227 brouard 7656: fprintf(ficgp," u %d:(",ioffset);
7657: kl=0;
7658: strcpy(gplotcondition,"(");
7659: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7660: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7661: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7662: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7663: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7664: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7665: kl++;
7666: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7667: kl++;
7668: if(k <cptcoveff && cptcoveff>1)
7669: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7670: }
7671: strcpy(gplotcondition+strlen(gplotcondition),")");
7672: /* 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 *\/ */
7673: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7674: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7675: /* '' 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*/
7676: if(i==nlstate+1){
1.270 brouard 7677: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
7678: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 7679: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7680: fprintf(ficgp," u %d:(",iagec);
7681: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
7682: iyearc, iagec, offyear, \
7683: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 7684: /* '' 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 7685: }else{
7686: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7687: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7688: }
7689: } /* end if covariate */
7690: } /* nlstate */
1.264 brouard 7691: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7692: } /* end cpt state*/
7693: } /* end covariate */
7694: } /* End if prevfcast */
1.227 brouard 7695:
1.268 brouard 7696: if(backcast==1){
7697: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7698:
7699: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7700: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7701: if(m != 1 && TKresult[nres]!= k1)
7702: continue;
7703: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7704: strcpy(gplotlabel,"(");
7705: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7706: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7707: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7708: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7709: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7710: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7711: vlv= nbcode[Tvaraff[k]][lv];
7712: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7713: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7714: }
7715: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7716: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7717: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7718: }
7719: strcpy(gplotlabel+strlen(gplotlabel),")");
7720: fprintf(ficgp,"\n#\n");
7721: if(invalidvarcomb[k1]){
7722: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7723: continue;
7724: }
7725:
7726: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7727: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7728: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7729: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7730: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7731:
7732: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7733: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7734: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7735: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7736: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7737: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7738: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7739: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7740: if(i==istart){
7741: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
7742: }else{
7743: fprintf(ficgp,",\\\n '' ");
7744: }
7745: if(cptcoveff ==0){ /* No covariate */
7746: ioffset=2; /* Age is in 2 */
7747: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7748: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7749: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7750: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7751: fprintf(ficgp," u %d:(", ioffset);
7752: if(i==nlstate+1){
1.270 brouard 7753: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 7754: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7755: fprintf(ficgp,",\\\n '' ");
7756: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7757: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 7758: offbyear, \
7759: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7760: }else
7761: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
7762: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
7763: }else{ /* more than 2 covariates */
1.270 brouard 7764: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7765: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7766: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7767: iyearc=ioffset-1;
7768: iagec=ioffset;
1.268 brouard 7769: fprintf(ficgp," u %d:(",ioffset);
7770: kl=0;
7771: strcpy(gplotcondition,"(");
7772: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7773: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7774: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7775: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7776: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7777: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7778: kl++;
7779: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7780: kl++;
7781: if(k <cptcoveff && cptcoveff>1)
7782: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7783: }
7784: strcpy(gplotcondition+strlen(gplotcondition),")");
7785: /* 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 *\/ */
7786: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7787: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7788: /* '' 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*/
7789: if(i==nlstate+1){
1.270 brouard 7790: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
7791: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 7792: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7793: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 7794: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 7795: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
7796: iyearc,iagec,offbyear, \
7797: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 7798: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
7799: }else{
7800: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
7801: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
7802: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
7803: }
7804: } /* end if covariate */
7805: } /* nlstate */
7806: fprintf(ficgp,"\nset out; unset label;\n");
7807: } /* end cpt state*/
7808: } /* end covariate */
7809: } /* End if backcast */
7810:
1.227 brouard 7811:
1.238 brouard 7812: /* 9eme writing MLE parameters */
7813: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7814: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7815: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7816: for(k=1; k <=(nlstate+ndeath); k++){
7817: if (k != i) {
1.227 brouard 7818: fprintf(ficgp,"# current state %d\n",k);
7819: for(j=1; j <=ncovmodel; j++){
7820: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7821: jk++;
7822: }
7823: fprintf(ficgp,"\n");
1.126 brouard 7824: }
7825: }
1.223 brouard 7826: }
1.187 brouard 7827: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7828:
1.145 brouard 7829: /*goto avoid;*/
1.238 brouard 7830: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7831: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7832: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7833: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7834: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7835: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7836: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7837: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7838: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7839: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7840: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7841: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7842: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7843: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7844: fprintf(ficgp,"#\n");
1.223 brouard 7845: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7846: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7847: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7848: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 7849: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
7850: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7851: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 7852: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7853: continue;
1.264 brouard 7854: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
7855: strcpy(gplotlabel,"(");
1.276 brouard 7856: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 7857: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7858: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7859: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7860: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7861: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7862: vlv= nbcode[Tvaraff[k]][lv];
7863: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7864: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7865: }
1.237 brouard 7866: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7867: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7868: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7869: }
1.264 brouard 7870: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7871: fprintf(ficgp,"\n#\n");
1.264 brouard 7872: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 7873: fprintf(ficgp,"\nset key outside ");
7874: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
7875: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7876: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7877: if (ng==1){
7878: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7879: fprintf(ficgp,"\nunset log y");
7880: }else if (ng==2){
7881: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7882: fprintf(ficgp,"\nset log y");
7883: }else if (ng==3){
7884: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7885: fprintf(ficgp,"\nset log y");
7886: }else
7887: fprintf(ficgp,"\nunset title ");
7888: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7889: i=1;
7890: for(k2=1; k2<=nlstate; k2++) {
7891: k3=i;
7892: for(k=1; k<=(nlstate+ndeath); k++) {
7893: if (k != k2){
7894: switch( ng) {
7895: case 1:
7896: if(nagesqr==0)
7897: fprintf(ficgp," p%d+p%d*x",i,i+1);
7898: else /* nagesqr =1 */
7899: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7900: break;
7901: case 2: /* ng=2 */
7902: if(nagesqr==0)
7903: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
7904: else /* nagesqr =1 */
7905: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7906: break;
7907: case 3:
7908: if(nagesqr==0)
7909: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
7910: else /* nagesqr =1 */
7911: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
7912: break;
7913: }
7914: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 7915: ijp=1; /* product no age */
7916: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
7917: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 7918: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 7919: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7920: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
7921: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7922: if(DummyV[j]==0){
7923: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
7924: }else{ /* quantitative */
7925: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
7926: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7927: }
7928: ij++;
1.237 brouard 7929: }
1.268 brouard 7930: }
7931: }else if(cptcovprod >0){
7932: if(j==Tprod[ijp]) { /* */
7933: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
7934: if(ijp <=cptcovprod) { /* Product */
7935: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
7936: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
7937: /* 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)]); */
7938: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
7939: }else{ /* Vn is dummy and Vm is quanti */
7940: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
7941: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7942: }
7943: }else{ /* Vn*Vm Vn is quanti */
7944: if(DummyV[Tvard[ijp][2]]==0){
7945: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
7946: }else{ /* Both quanti */
7947: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7948: }
1.237 brouard 7949: }
1.268 brouard 7950: ijp++;
1.237 brouard 7951: }
1.268 brouard 7952: } /* end Tprod */
1.237 brouard 7953: } else{ /* simple covariate */
1.264 brouard 7954: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 7955: if(Dummy[j]==0){
7956: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
7957: }else{ /* quantitative */
7958: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 7959: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 7960: }
1.237 brouard 7961: } /* end simple */
7962: } /* end j */
1.223 brouard 7963: }else{
7964: i=i-ncovmodel;
7965: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
7966: fprintf(ficgp," (1.");
7967: }
1.227 brouard 7968:
1.223 brouard 7969: if(ng != 1){
7970: fprintf(ficgp,")/(1");
1.227 brouard 7971:
1.264 brouard 7972: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 7973: if(nagesqr==0)
1.264 brouard 7974: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 7975: else /* nagesqr =1 */
1.264 brouard 7976: 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 7977:
1.223 brouard 7978: ij=1;
7979: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 7980: if(cptcovage >0){
7981: if((j-2)==Tage[ij]) { /* Bug valgrind */
7982: if(ij <=cptcovage) { /* Bug valgrind */
7983: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
7984: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7985: ij++;
7986: }
7987: }
7988: }else
7989: 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 7990: }
7991: fprintf(ficgp,")");
7992: }
7993: fprintf(ficgp,")");
7994: if(ng ==2)
1.276 brouard 7995: 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 7996: else /* ng= 3 */
1.276 brouard 7997: 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 7998: }else{ /* end ng <> 1 */
7999: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8000: 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 8001: }
8002: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8003: fprintf(ficgp,",");
8004: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8005: fprintf(ficgp,",");
8006: i=i+ncovmodel;
8007: } /* end k */
8008: } /* end k2 */
1.276 brouard 8009: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8010: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8011: } /* end k1 */
1.223 brouard 8012: } /* end ng */
8013: /* avoid: */
8014: fflush(ficgp);
1.126 brouard 8015: } /* end gnuplot */
8016:
8017:
8018: /*************** Moving average **************/
1.219 brouard 8019: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8020: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8021:
1.222 brouard 8022: int i, cpt, cptcod;
8023: int modcovmax =1;
8024: int mobilavrange, mob;
8025: int iage=0;
8026:
1.266 brouard 8027: double sum=0., sumr=0.;
1.222 brouard 8028: double age;
1.266 brouard 8029: double *sumnewp, *sumnewm, *sumnewmr;
8030: double *agemingood, *agemaxgood;
8031: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8032:
8033:
1.278 brouard 8034: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8035: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8036:
8037: sumnewp = vector(1,ncovcombmax);
8038: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8039: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8040: agemingood = vector(1,ncovcombmax);
1.266 brouard 8041: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8042: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8043: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8044:
8045: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8046: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8047: sumnewp[cptcod]=0.;
1.266 brouard 8048: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8049: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8050: }
8051: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8052:
1.266 brouard 8053: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8054: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8055: else mobilavrange=mobilav;
8056: for (age=bage; age<=fage; age++)
8057: for (i=1; i<=nlstate;i++)
8058: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8059: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8060: /* We keep the original values on the extreme ages bage, fage and for
8061: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8062: we use a 5 terms etc. until the borders are no more concerned.
8063: */
8064: for (mob=3;mob <=mobilavrange;mob=mob+2){
8065: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8066: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8067: sumnewm[cptcod]=0.;
8068: for (i=1; i<=nlstate;i++){
1.222 brouard 8069: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8070: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8071: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8072: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8073: }
8074: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8075: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8076: } /* end i */
8077: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8078: } /* end cptcod */
1.222 brouard 8079: }/* end age */
8080: }/* end mob */
1.266 brouard 8081: }else{
8082: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8083: return -1;
1.266 brouard 8084: }
8085:
8086: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8087: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8088: if(invalidvarcomb[cptcod]){
8089: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8090: continue;
8091: }
1.219 brouard 8092:
1.266 brouard 8093: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8094: sumnewm[cptcod]=0.;
8095: sumnewmr[cptcod]=0.;
8096: for (i=1; i<=nlstate;i++){
8097: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8098: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8099: }
8100: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8101: agemingoodr[cptcod]=age;
8102: }
8103: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8104: agemingood[cptcod]=age;
8105: }
8106: } /* age */
8107: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8108: sumnewm[cptcod]=0.;
1.266 brouard 8109: sumnewmr[cptcod]=0.;
1.222 brouard 8110: for (i=1; i<=nlstate;i++){
8111: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8112: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8113: }
8114: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8115: agemaxgoodr[cptcod]=age;
1.222 brouard 8116: }
8117: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8118: agemaxgood[cptcod]=age;
8119: }
8120: } /* age */
8121: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8122: /* but they will change */
8123: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8124: sumnewm[cptcod]=0.;
8125: sumnewmr[cptcod]=0.;
8126: for (i=1; i<=nlstate;i++){
8127: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8128: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8129: }
8130: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8131: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8132: agemaxgoodr[cptcod]=age; /* age min */
8133: for (i=1; i<=nlstate;i++)
8134: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8135: }else{ /* bad we change the value with the values of good ages */
8136: for (i=1; i<=nlstate;i++){
8137: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8138: } /* i */
8139: } /* end bad */
8140: }else{
8141: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8142: agemaxgood[cptcod]=age;
8143: }else{ /* bad we change the value with the values of good ages */
8144: for (i=1; i<=nlstate;i++){
8145: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8146: } /* i */
8147: } /* end bad */
8148: }/* end else */
8149: sum=0.;sumr=0.;
8150: for (i=1; i<=nlstate;i++){
8151: sum+=mobaverage[(int)age][i][cptcod];
8152: sumr+=probs[(int)age][i][cptcod];
8153: }
8154: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8155: 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\n",cptcod,sumr, (int)age, (int)bage);
1.266 brouard 8156: } /* end bad */
8157: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8158: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8159: 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\n",cptcod,sumr, (int)age, (int)bage);
1.222 brouard 8160: } /* end bad */
8161: }/* age */
1.266 brouard 8162:
8163: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8164: sumnewm[cptcod]=0.;
1.266 brouard 8165: sumnewmr[cptcod]=0.;
1.222 brouard 8166: for (i=1; i<=nlstate;i++){
8167: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8168: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8169: }
8170: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8171: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8172: agemingoodr[cptcod]=age;
8173: for (i=1; i<=nlstate;i++)
8174: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8175: }else{ /* bad we change the value with the values of good ages */
8176: for (i=1; i<=nlstate;i++){
8177: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8178: } /* i */
8179: } /* end bad */
8180: }else{
8181: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8182: agemingood[cptcod]=age;
8183: }else{ /* bad */
8184: for (i=1; i<=nlstate;i++){
8185: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8186: } /* i */
8187: } /* end bad */
8188: }/* end else */
8189: sum=0.;sumr=0.;
8190: for (i=1; i<=nlstate;i++){
8191: sum+=mobaverage[(int)age][i][cptcod];
8192: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8193: }
1.266 brouard 8194: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8195: 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 8196: } /* end bad */
8197: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8198: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8199: 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 8200: } /* end bad */
8201: }/* age */
1.266 brouard 8202:
1.222 brouard 8203:
8204: for (age=bage; age<=fage; age++){
1.235 brouard 8205: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8206: sumnewp[cptcod]=0.;
8207: sumnewm[cptcod]=0.;
8208: for (i=1; i<=nlstate;i++){
8209: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8210: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8211: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8212: }
8213: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8214: }
8215: /* printf("\n"); */
8216: /* } */
1.266 brouard 8217:
1.222 brouard 8218: /* brutal averaging */
1.266 brouard 8219: /* for (i=1; i<=nlstate;i++){ */
8220: /* for (age=1; age<=bage; age++){ */
8221: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8222: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8223: /* } */
8224: /* for (age=fage; age<=AGESUP; age++){ */
8225: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8226: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8227: /* } */
8228: /* } /\* end i status *\/ */
8229: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8230: /* for (age=1; age<=AGESUP; age++){ */
8231: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8232: /* mobaverage[(int)age][i][cptcod]=0.; */
8233: /* } */
8234: /* } */
1.222 brouard 8235: }/* end cptcod */
1.266 brouard 8236: free_vector(agemaxgoodr,1, ncovcombmax);
8237: free_vector(agemaxgood,1, ncovcombmax);
8238: free_vector(agemingood,1, ncovcombmax);
8239: free_vector(agemingoodr,1, ncovcombmax);
8240: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8241: free_vector(sumnewm,1, ncovcombmax);
8242: free_vector(sumnewp,1, ncovcombmax);
8243: return 0;
8244: }/* End movingaverage */
1.218 brouard 8245:
1.126 brouard 8246:
8247: /************** Forecasting ******************/
1.269 brouard 8248: 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 8249: /* proj1, year, month, day of starting projection
8250: agemin, agemax range of age
8251: dateprev1 dateprev2 range of dates during which prevalence is computed
8252: anproj2 year of en of projection (same day and month as proj1).
8253: */
1.267 brouard 8254: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8255: double agec; /* generic age */
8256: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
8257: double *popeffectif,*popcount;
8258: double ***p3mat;
1.218 brouard 8259: /* double ***mobaverage; */
1.126 brouard 8260: char fileresf[FILENAMELENGTH];
8261:
8262: agelim=AGESUP;
1.211 brouard 8263: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8264: in each health status at the date of interview (if between dateprev1 and dateprev2).
8265: We still use firstpass and lastpass as another selection.
8266: */
1.214 brouard 8267: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8268: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8269:
1.201 brouard 8270: strcpy(fileresf,"F_");
8271: strcat(fileresf,fileresu);
1.126 brouard 8272: if((ficresf=fopen(fileresf,"w"))==NULL) {
8273: printf("Problem with forecast resultfile: %s\n", fileresf);
8274: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8275: }
1.235 brouard 8276: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8277: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8278:
1.225 brouard 8279: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8280:
8281:
8282: stepsize=(int) (stepm+YEARM-1)/YEARM;
8283: if (stepm<=12) stepsize=1;
8284: if(estepm < stepm){
8285: printf ("Problem %d lower than %d\n",estepm, stepm);
8286: }
1.270 brouard 8287: else{
8288: hstepm=estepm;
8289: }
8290: if(estepm > stepm){ /* Yes every two year */
8291: stepsize=2;
8292: }
1.126 brouard 8293:
8294: hstepm=hstepm/stepm;
8295: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8296: fractional in yp1 */
8297: anprojmean=yp;
8298: yp2=modf((yp1*12),&yp);
8299: mprojmean=yp;
8300: yp1=modf((yp2*30.5),&yp);
8301: jprojmean=yp;
8302: if(jprojmean==0) jprojmean=1;
8303: if(mprojmean==0) jprojmean=1;
8304:
1.227 brouard 8305: i1=pow(2,cptcoveff);
1.126 brouard 8306: if (cptcovn < 1){i1=1;}
8307:
8308: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
8309:
8310: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8311:
1.126 brouard 8312: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8313: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8314: for(k=1; k<=i1;k++){
1.253 brouard 8315: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8316: continue;
1.227 brouard 8317: if(invalidvarcomb[k]){
8318: printf("\nCombination (%d) projection ignored because no cases \n",k);
8319: continue;
8320: }
8321: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8322: for(j=1;j<=cptcoveff;j++) {
8323: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8324: }
1.235 brouard 8325: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8326: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8327: }
1.227 brouard 8328: fprintf(ficresf," yearproj age");
8329: for(j=1; j<=nlstate+ndeath;j++){
8330: for(i=1; i<=nlstate;i++)
8331: fprintf(ficresf," p%d%d",i,j);
8332: fprintf(ficresf," wp.%d",j);
8333: }
8334: for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {
8335: fprintf(ficresf,"\n");
8336: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
1.270 brouard 8337: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8338: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8339: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8340: nhstepm = nhstepm/hstepm;
8341: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8342: oldm=oldms;savm=savms;
1.268 brouard 8343: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8344: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8345: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8346: for (h=0; h<=nhstepm; h++){
8347: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8348: break;
8349: }
8350: }
8351: fprintf(ficresf,"\n");
8352: for(j=1;j<=cptcoveff;j++)
8353: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8354: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
8355:
8356: for(j=1; j<=nlstate+ndeath;j++) {
8357: ppij=0.;
8358: for(i=1; i<=nlstate;i++) {
1.278 brouard 8359: if (mobilav>=1)
8360: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8361: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8362: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8363: }
1.268 brouard 8364: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8365: } /* end i */
8366: fprintf(ficresf," %.3f", ppij);
8367: }/* end j */
1.227 brouard 8368: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8369: } /* end agec */
1.266 brouard 8370: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8371: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8372: } /* end yearp */
8373: } /* end k */
1.219 brouard 8374:
1.126 brouard 8375: fclose(ficresf);
1.215 brouard 8376: printf("End of Computing forecasting \n");
8377: fprintf(ficlog,"End of Computing forecasting\n");
8378:
1.126 brouard 8379: }
8380:
1.269 brouard 8381: /************** Back Forecasting ******************/
8382: 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 8383: /* back1, year, month, day of starting backection
8384: agemin, agemax range of age
8385: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8386: anback2 year of end of backprojection (same day and month as back1).
8387: prevacurrent and prev are prevalences.
1.267 brouard 8388: */
8389: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8390: double agec; /* generic age */
1.268 brouard 8391: double agelim, ppij, ppi, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
1.267 brouard 8392: double *popeffectif,*popcount;
8393: double ***p3mat;
8394: /* double ***mobaverage; */
8395: char fileresfb[FILENAMELENGTH];
8396:
1.268 brouard 8397: agelim=AGEINF;
1.267 brouard 8398: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8399: in each health status at the date of interview (if between dateprev1 and dateprev2).
8400: We still use firstpass and lastpass as another selection.
8401: */
8402: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8403: /* firstpass, lastpass, stepm, weightopt, model); */
8404:
8405: /*Do we need to compute prevalence again?*/
8406:
8407: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8408:
8409: strcpy(fileresfb,"FB_");
8410: strcat(fileresfb,fileresu);
8411: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8412: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8413: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8414: }
8415: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8416: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8417:
8418: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8419:
8420:
8421: stepsize=(int) (stepm+YEARM-1)/YEARM;
8422: if (stepm<=12) stepsize=1;
8423: if(estepm < stepm){
8424: printf ("Problem %d lower than %d\n",estepm, stepm);
8425: }
1.270 brouard 8426: else{
8427: hstepm=estepm;
8428: }
8429: if(estepm >= stepm){ /* Yes every two year */
8430: stepsize=2;
8431: }
1.267 brouard 8432:
8433: hstepm=hstepm/stepm;
8434: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8435: fractional in yp1 */
8436: anprojmean=yp;
8437: yp2=modf((yp1*12),&yp);
8438: mprojmean=yp;
8439: yp1=modf((yp2*30.5),&yp);
8440: jprojmean=yp;
8441: if(jprojmean==0) jprojmean=1;
8442: if(mprojmean==0) jprojmean=1;
8443:
8444: i1=pow(2,cptcoveff);
8445: if (cptcovn < 1){i1=1;}
8446:
8447: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.268 brouard 8448: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8449:
8450: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8451:
8452: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8453: for(k=1; k<=i1;k++){
8454: if(i1 != 1 && TKresult[nres]!= k)
8455: continue;
8456: if(invalidvarcomb[k]){
8457: printf("\nCombination (%d) projection ignored because no cases \n",k);
8458: continue;
8459: }
1.268 brouard 8460: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8461: for(j=1;j<=cptcoveff;j++) {
8462: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8463: }
8464: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8465: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8466: }
8467: fprintf(ficresfb," yearbproj age");
8468: for(j=1; j<=nlstate+ndeath;j++){
8469: for(i=1; i<=nlstate;i++)
1.268 brouard 8470: fprintf(ficresfb," b%d%d",i,j);
8471: fprintf(ficresfb," b.%d",j);
1.267 brouard 8472: }
8473: for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) {
8474: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8475: fprintf(ficresfb,"\n");
8476: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp);
1.273 brouard 8477: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8478: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8479: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8480: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8481: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8482: nhstepm = nhstepm/hstepm;
8483: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8484: oldm=oldms;savm=savms;
1.268 brouard 8485: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8486: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8487: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8488: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8489: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8490: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8491: for (h=0; h<=nhstepm; h++){
1.268 brouard 8492: if (h*hstepm/YEARM*stepm ==-yearp) {
8493: break;
8494: }
8495: }
8496: fprintf(ficresfb,"\n");
8497: for(j=1;j<=cptcoveff;j++)
8498: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8499: fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec-h*hstepm/YEARM*stepm);
8500: for(i=1; i<=nlstate+ndeath;i++) {
8501: ppij=0.;ppi=0.;
8502: for(j=1; j<=nlstate;j++) {
8503: /* if (mobilav==1) */
1.269 brouard 8504: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8505: ppi=ppi+prevacurrent[(int)agec][j][k];
8506: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8507: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8508: /* else { */
8509: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8510: /* } */
1.268 brouard 8511: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8512: } /* end j */
8513: if(ppi <0.99){
8514: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8515: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8516: }
8517: fprintf(ficresfb," %.3f", ppij);
8518: }/* end j */
1.267 brouard 8519: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8520: } /* end agec */
8521: } /* end yearp */
8522: } /* end k */
1.217 brouard 8523:
1.267 brouard 8524: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8525:
1.267 brouard 8526: fclose(ficresfb);
8527: printf("End of Computing Back forecasting \n");
8528: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8529:
1.267 brouard 8530: }
1.217 brouard 8531:
1.269 brouard 8532: /* Variance of prevalence limit: varprlim */
8533: 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){
8534: /*------- Variance of period (stable) prevalence------*/
8535:
8536: char fileresvpl[FILENAMELENGTH];
8537: FILE *ficresvpl;
8538: double **oldm, **savm;
8539: double **varpl; /* Variances of prevalence limits by age */
8540: int i1, k, nres, j ;
8541:
8542: strcpy(fileresvpl,"VPL_");
8543: strcat(fileresvpl,fileresu);
8544: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
8545: printf("Problem with variance of period (stable) prevalence resultfile: %s\n", fileresvpl);
8546: exit(0);
8547: }
8548: printf("Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8549: fprintf(ficlog, "Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
8550:
8551: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8552: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8553:
8554: i1=pow(2,cptcoveff);
8555: if (cptcovn < 1){i1=1;}
8556:
8557: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8558: for(k=1; k<=i1;k++){
8559: if(i1 != 1 && TKresult[nres]!= k)
8560: continue;
8561: fprintf(ficresvpl,"\n#****** ");
8562: printf("\n#****** ");
8563: fprintf(ficlog,"\n#****** ");
8564: for(j=1;j<=cptcoveff;j++) {
8565: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8566: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8567: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8568: }
8569: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8570: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8571: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8572: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8573: }
8574: fprintf(ficresvpl,"******\n");
8575: printf("******\n");
8576: fprintf(ficlog,"******\n");
8577:
8578: varpl=matrix(1,nlstate,(int) bage, (int) fage);
8579: oldm=oldms;savm=savms;
8580: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
8581: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
8582: /*}*/
8583: }
8584:
8585: fclose(ficresvpl);
8586: printf("done variance-covariance of period prevalence\n");fflush(stdout);
8587: fprintf(ficlog,"done variance-covariance of period prevalence\n");fflush(ficlog);
8588:
8589: }
8590: /* Variance of back prevalence: varbprlim */
8591: 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){
8592: /*------- Variance of back (stable) prevalence------*/
8593:
8594: char fileresvbl[FILENAMELENGTH];
8595: FILE *ficresvbl;
8596:
8597: double **oldm, **savm;
8598: double **varbpl; /* Variances of back prevalence limits by age */
8599: int i1, k, nres, j ;
8600:
8601: strcpy(fileresvbl,"VBL_");
8602: strcat(fileresvbl,fileresu);
8603: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
8604: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
8605: exit(0);
8606: }
8607: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
8608: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
8609:
8610:
8611: i1=pow(2,cptcoveff);
8612: if (cptcovn < 1){i1=1;}
8613:
8614: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8615: for(k=1; k<=i1;k++){
8616: if(i1 != 1 && TKresult[nres]!= k)
8617: continue;
8618: fprintf(ficresvbl,"\n#****** ");
8619: printf("\n#****** ");
8620: fprintf(ficlog,"\n#****** ");
8621: for(j=1;j<=cptcoveff;j++) {
8622: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8623: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8624: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8625: }
8626: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8627: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8628: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8629: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8630: }
8631: fprintf(ficresvbl,"******\n");
8632: printf("******\n");
8633: fprintf(ficlog,"******\n");
8634:
8635: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
8636: oldm=oldms;savm=savms;
8637:
8638: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
8639: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
8640: /*}*/
8641: }
8642:
8643: fclose(ficresvbl);
8644: printf("done variance-covariance of back prevalence\n");fflush(stdout);
8645: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
8646:
8647: } /* End of varbprlim */
8648:
1.126 brouard 8649: /************** Forecasting *****not tested NB*************/
1.227 brouard 8650: /* 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 8651:
1.227 brouard 8652: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8653: /* int *popage; */
8654: /* double calagedatem, agelim, kk1, kk2; */
8655: /* double *popeffectif,*popcount; */
8656: /* double ***p3mat,***tabpop,***tabpopprev; */
8657: /* /\* double ***mobaverage; *\/ */
8658: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8659:
1.227 brouard 8660: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8661: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8662: /* agelim=AGESUP; */
8663: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8664:
1.227 brouard 8665: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8666:
8667:
1.227 brouard 8668: /* strcpy(filerespop,"POP_"); */
8669: /* strcat(filerespop,fileresu); */
8670: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8671: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8672: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8673: /* } */
8674: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8675: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8676:
1.227 brouard 8677: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8678:
1.227 brouard 8679: /* /\* if (mobilav!=0) { *\/ */
8680: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8681: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8682: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8683: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8684: /* /\* } *\/ */
8685: /* /\* } *\/ */
1.126 brouard 8686:
1.227 brouard 8687: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8688: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8689:
1.227 brouard 8690: /* agelim=AGESUP; */
1.126 brouard 8691:
1.227 brouard 8692: /* hstepm=1; */
8693: /* hstepm=hstepm/stepm; */
1.218 brouard 8694:
1.227 brouard 8695: /* if (popforecast==1) { */
8696: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8697: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8698: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8699: /* } */
8700: /* popage=ivector(0,AGESUP); */
8701: /* popeffectif=vector(0,AGESUP); */
8702: /* popcount=vector(0,AGESUP); */
1.126 brouard 8703:
1.227 brouard 8704: /* i=1; */
8705: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8706:
1.227 brouard 8707: /* imx=i; */
8708: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8709: /* } */
1.218 brouard 8710:
1.227 brouard 8711: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8712: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8713: /* k=k+1; */
8714: /* fprintf(ficrespop,"\n#******"); */
8715: /* for(j=1;j<=cptcoveff;j++) { */
8716: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8717: /* } */
8718: /* fprintf(ficrespop,"******\n"); */
8719: /* fprintf(ficrespop,"# Age"); */
8720: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8721: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8722:
1.227 brouard 8723: /* for (cpt=0; cpt<=0;cpt++) { */
8724: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8725:
1.227 brouard 8726: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8727: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8728: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8729:
1.227 brouard 8730: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8731: /* oldm=oldms;savm=savms; */
8732: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8733:
1.227 brouard 8734: /* for (h=0; h<=nhstepm; h++){ */
8735: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8736: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8737: /* } */
8738: /* for(j=1; j<=nlstate+ndeath;j++) { */
8739: /* kk1=0.;kk2=0; */
8740: /* for(i=1; i<=nlstate;i++) { */
8741: /* if (mobilav==1) */
8742: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8743: /* else { */
8744: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8745: /* } */
8746: /* } */
8747: /* if (h==(int)(calagedatem+12*cpt)){ */
8748: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8749: /* /\*fprintf(ficrespop," %.3f", kk1); */
8750: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8751: /* } */
8752: /* } */
8753: /* for(i=1; i<=nlstate;i++){ */
8754: /* kk1=0.; */
8755: /* for(j=1; j<=nlstate;j++){ */
8756: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8757: /* } */
8758: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8759: /* } */
1.218 brouard 8760:
1.227 brouard 8761: /* if (h==(int)(calagedatem+12*cpt)) */
8762: /* for(j=1; j<=nlstate;j++) */
8763: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8764: /* } */
8765: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8766: /* } */
8767: /* } */
1.218 brouard 8768:
1.227 brouard 8769: /* /\******\/ */
1.218 brouard 8770:
1.227 brouard 8771: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8772: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8773: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8774: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8775: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8776:
1.227 brouard 8777: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8778: /* oldm=oldms;savm=savms; */
8779: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8780: /* for (h=0; h<=nhstepm; h++){ */
8781: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8782: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8783: /* } */
8784: /* for(j=1; j<=nlstate+ndeath;j++) { */
8785: /* kk1=0.;kk2=0; */
8786: /* for(i=1; i<=nlstate;i++) { */
8787: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8788: /* } */
8789: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8790: /* } */
8791: /* } */
8792: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8793: /* } */
8794: /* } */
8795: /* } */
8796: /* } */
1.218 brouard 8797:
1.227 brouard 8798: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8799:
1.227 brouard 8800: /* if (popforecast==1) { */
8801: /* free_ivector(popage,0,AGESUP); */
8802: /* free_vector(popeffectif,0,AGESUP); */
8803: /* free_vector(popcount,0,AGESUP); */
8804: /* } */
8805: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8806: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8807: /* fclose(ficrespop); */
8808: /* } /\* End of popforecast *\/ */
1.218 brouard 8809:
1.126 brouard 8810: int fileappend(FILE *fichier, char *optionfich)
8811: {
8812: if((fichier=fopen(optionfich,"a"))==NULL) {
8813: printf("Problem with file: %s\n", optionfich);
8814: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8815: return (0);
8816: }
8817: fflush(fichier);
8818: return (1);
8819: }
8820:
8821:
8822: /**************** function prwizard **********************/
8823: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8824: {
8825:
8826: /* Wizard to print covariance matrix template */
8827:
1.164 brouard 8828: char ca[32], cb[32];
8829: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8830: int numlinepar;
8831:
8832: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8833: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8834: for(i=1; i <=nlstate; i++){
8835: jj=0;
8836: for(j=1; j <=nlstate+ndeath; j++){
8837: if(j==i) continue;
8838: jj++;
8839: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8840: printf("%1d%1d",i,j);
8841: fprintf(ficparo,"%1d%1d",i,j);
8842: for(k=1; k<=ncovmodel;k++){
8843: /* printf(" %lf",param[i][j][k]); */
8844: /* fprintf(ficparo," %lf",param[i][j][k]); */
8845: printf(" 0.");
8846: fprintf(ficparo," 0.");
8847: }
8848: printf("\n");
8849: fprintf(ficparo,"\n");
8850: }
8851: }
8852: printf("# Scales (for hessian or gradient estimation)\n");
8853: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8854: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8855: for(i=1; i <=nlstate; i++){
8856: jj=0;
8857: for(j=1; j <=nlstate+ndeath; j++){
8858: if(j==i) continue;
8859: jj++;
8860: fprintf(ficparo,"%1d%1d",i,j);
8861: printf("%1d%1d",i,j);
8862: fflush(stdout);
8863: for(k=1; k<=ncovmodel;k++){
8864: /* printf(" %le",delti3[i][j][k]); */
8865: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8866: printf(" 0.");
8867: fprintf(ficparo," 0.");
8868: }
8869: numlinepar++;
8870: printf("\n");
8871: fprintf(ficparo,"\n");
8872: }
8873: }
8874: printf("# Covariance matrix\n");
8875: /* # 121 Var(a12)\n\ */
8876: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8877: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
8878: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
8879: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
8880: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
8881: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
8882: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8883: fflush(stdout);
8884: fprintf(ficparo,"# Covariance matrix\n");
8885: /* # 121 Var(a12)\n\ */
8886: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8887: /* # ...\n\ */
8888: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8889:
8890: for(itimes=1;itimes<=2;itimes++){
8891: jj=0;
8892: for(i=1; i <=nlstate; i++){
8893: for(j=1; j <=nlstate+ndeath; j++){
8894: if(j==i) continue;
8895: for(k=1; k<=ncovmodel;k++){
8896: jj++;
8897: ca[0]= k+'a'-1;ca[1]='\0';
8898: if(itimes==1){
8899: printf("#%1d%1d%d",i,j,k);
8900: fprintf(ficparo,"#%1d%1d%d",i,j,k);
8901: }else{
8902: printf("%1d%1d%d",i,j,k);
8903: fprintf(ficparo,"%1d%1d%d",i,j,k);
8904: /* printf(" %.5le",matcov[i][j]); */
8905: }
8906: ll=0;
8907: for(li=1;li <=nlstate; li++){
8908: for(lj=1;lj <=nlstate+ndeath; lj++){
8909: if(lj==li) continue;
8910: for(lk=1;lk<=ncovmodel;lk++){
8911: ll++;
8912: if(ll<=jj){
8913: cb[0]= lk +'a'-1;cb[1]='\0';
8914: if(ll<jj){
8915: if(itimes==1){
8916: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8917: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8918: }else{
8919: printf(" 0.");
8920: fprintf(ficparo," 0.");
8921: }
8922: }else{
8923: if(itimes==1){
8924: printf(" Var(%s%1d%1d)",ca,i,j);
8925: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
8926: }else{
8927: printf(" 0.");
8928: fprintf(ficparo," 0.");
8929: }
8930: }
8931: }
8932: } /* end lk */
8933: } /* end lj */
8934: } /* end li */
8935: printf("\n");
8936: fprintf(ficparo,"\n");
8937: numlinepar++;
8938: } /* end k*/
8939: } /*end j */
8940: } /* end i */
8941: } /* end itimes */
8942:
8943: } /* end of prwizard */
8944: /******************* Gompertz Likelihood ******************************/
8945: double gompertz(double x[])
8946: {
8947: double A,B,L=0.0,sump=0.,num=0.;
8948: int i,n=0; /* n is the size of the sample */
8949:
1.220 brouard 8950: for (i=1;i<=imx ; i++) {
1.126 brouard 8951: sump=sump+weight[i];
8952: /* sump=sump+1;*/
8953: num=num+1;
8954: }
8955:
8956:
8957: /* for (i=0; i<=imx; i++)
8958: 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]);*/
8959:
8960: for (i=1;i<=imx ; i++)
8961: {
8962: if (cens[i] == 1 && wav[i]>1)
8963: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
8964:
8965: if (cens[i] == 0 && wav[i]>1)
8966: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
8967: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
8968:
8969: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
8970: if (wav[i] > 1 ) { /* ??? */
8971: L=L+A*weight[i];
8972: /* 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]);*/
8973: }
8974: }
8975:
8976: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
8977:
8978: return -2*L*num/sump;
8979: }
8980:
1.136 brouard 8981: #ifdef GSL
8982: /******************* Gompertz_f Likelihood ******************************/
8983: double gompertz_f(const gsl_vector *v, void *params)
8984: {
8985: double A,B,LL=0.0,sump=0.,num=0.;
8986: double *x= (double *) v->data;
8987: int i,n=0; /* n is the size of the sample */
8988:
8989: for (i=0;i<=imx-1 ; i++) {
8990: sump=sump+weight[i];
8991: /* sump=sump+1;*/
8992: num=num+1;
8993: }
8994:
8995:
8996: /* for (i=0; i<=imx; i++)
8997: 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]);*/
8998: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
8999: for (i=1;i<=imx ; i++)
9000: {
9001: if (cens[i] == 1 && wav[i]>1)
9002: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9003:
9004: if (cens[i] == 0 && wav[i]>1)
9005: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9006: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9007:
9008: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9009: if (wav[i] > 1 ) { /* ??? */
9010: LL=LL+A*weight[i];
9011: /* 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]);*/
9012: }
9013: }
9014:
9015: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9016: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9017:
9018: return -2*LL*num/sump;
9019: }
9020: #endif
9021:
1.126 brouard 9022: /******************* Printing html file ***********/
1.201 brouard 9023: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9024: int lastpass, int stepm, int weightopt, char model[],\
9025: int imx, double p[],double **matcov,double agemortsup){
9026: int i,k;
9027:
9028: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9029: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9030: for (i=1;i<=2;i++)
9031: 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 9032: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9033: fprintf(fichtm,"</ul>");
9034:
9035: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9036:
9037: 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>");
9038:
9039: for (k=agegomp;k<(agemortsup-2);k++)
9040: 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]);
9041:
9042:
9043: fflush(fichtm);
9044: }
9045:
9046: /******************* Gnuplot file **************/
1.201 brouard 9047: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9048:
9049: char dirfileres[132],optfileres[132];
1.164 brouard 9050:
1.126 brouard 9051: int ng;
9052:
9053:
9054: /*#ifdef windows */
9055: fprintf(ficgp,"cd \"%s\" \n",pathc);
9056: /*#endif */
9057:
9058:
9059: strcpy(dirfileres,optionfilefiname);
9060: strcpy(optfileres,"vpl");
1.199 brouard 9061: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9062: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9063: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9064: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9065: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9066:
9067: }
9068:
1.136 brouard 9069: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9070: {
1.126 brouard 9071:
1.136 brouard 9072: /*-------- data file ----------*/
9073: FILE *fic;
9074: char dummy[]=" ";
1.240 brouard 9075: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9076: int lstra;
1.136 brouard 9077: int linei, month, year,iout;
9078: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9079: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9080: char *stratrunc;
1.223 brouard 9081:
1.240 brouard 9082: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9083: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9084:
1.240 brouard 9085: for(v=1; v <=ncovcol;v++){
9086: DummyV[v]=0;
9087: FixedV[v]=0;
9088: }
9089: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9090: DummyV[v]=1;
9091: FixedV[v]=0;
9092: }
9093: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9094: DummyV[v]=0;
9095: FixedV[v]=1;
9096: }
9097: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9098: DummyV[v]=1;
9099: FixedV[v]=1;
9100: }
9101: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9102: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9103: 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]);
9104: }
1.126 brouard 9105:
1.136 brouard 9106: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9107: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9108: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9109: }
1.126 brouard 9110:
1.136 brouard 9111: i=1;
9112: linei=0;
9113: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9114: linei=linei+1;
9115: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9116: if(line[j] == '\t')
9117: line[j] = ' ';
9118: }
9119: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9120: ;
9121: };
9122: line[j+1]=0; /* Trims blanks at end of line */
9123: if(line[0]=='#'){
9124: fprintf(ficlog,"Comment line\n%s\n",line);
9125: printf("Comment line\n%s\n",line);
9126: continue;
9127: }
9128: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9129: strcpy(line, linetmp);
1.223 brouard 9130:
9131: /* Loops on waves */
9132: for (j=maxwav;j>=1;j--){
9133: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9134: cutv(stra, strb, line, ' ');
9135: if(strb[0]=='.') { /* Missing value */
9136: lval=-1;
9137: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9138: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9139: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9140: 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);
9141: 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);
9142: return 1;
9143: }
9144: }else{
9145: errno=0;
9146: /* what_kind_of_number(strb); */
9147: dval=strtod(strb,&endptr);
9148: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9149: /* if(strb != endptr && *endptr == '\0') */
9150: /* dval=dlval; */
9151: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9152: if( strb[0]=='\0' || (*endptr != '\0')){
9153: 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);
9154: 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);
9155: return 1;
9156: }
9157: cotqvar[j][iv][i]=dval;
9158: cotvar[j][ntv+iv][i]=dval;
9159: }
9160: strcpy(line,stra);
1.223 brouard 9161: }/* end loop ntqv */
1.225 brouard 9162:
1.223 brouard 9163: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9164: cutv(stra, strb, line, ' ');
9165: if(strb[0]=='.') { /* Missing value */
9166: lval=-1;
9167: }else{
9168: errno=0;
9169: lval=strtol(strb,&endptr,10);
9170: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9171: if( strb[0]=='\0' || (*endptr != '\0')){
9172: 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);
9173: 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);
9174: return 1;
9175: }
9176: }
9177: if(lval <-1 || lval >1){
9178: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9179: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9180: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9181: For example, for multinomial values like 1, 2 and 3,\n \
9182: build V1=0 V2=0 for the reference value (1),\n \
9183: V1=1 V2=0 for (2) \n \
1.223 brouard 9184: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9185: output of IMaCh is often meaningless.\n \
1.223 brouard 9186: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9187: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9188: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9189: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9190: For example, for multinomial values like 1, 2 and 3,\n \
9191: build V1=0 V2=0 for the reference value (1),\n \
9192: V1=1 V2=0 for (2) \n \
1.223 brouard 9193: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9194: output of IMaCh is often meaningless.\n \
1.223 brouard 9195: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 9196: return 1;
9197: }
9198: cotvar[j][iv][i]=(double)(lval);
9199: strcpy(line,stra);
1.223 brouard 9200: }/* end loop ntv */
1.225 brouard 9201:
1.223 brouard 9202: /* Statuses at wave */
1.137 brouard 9203: cutv(stra, strb, line, ' ');
1.223 brouard 9204: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9205: lval=-1;
1.136 brouard 9206: }else{
1.238 brouard 9207: errno=0;
9208: lval=strtol(strb,&endptr,10);
9209: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9210: if( strb[0]=='\0' || (*endptr != '\0')){
9211: 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);
9212: 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);
9213: return 1;
9214: }
1.136 brouard 9215: }
1.225 brouard 9216:
1.136 brouard 9217: s[j][i]=lval;
1.225 brouard 9218:
1.223 brouard 9219: /* Date of Interview */
1.136 brouard 9220: strcpy(line,stra);
9221: cutv(stra, strb,line,' ');
1.169 brouard 9222: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9223: }
1.169 brouard 9224: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9225: month=99;
9226: year=9999;
1.136 brouard 9227: }else{
1.225 brouard 9228: 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);
9229: 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);
9230: return 1;
1.136 brouard 9231: }
9232: anint[j][i]= (double) year;
9233: mint[j][i]= (double)month;
9234: strcpy(line,stra);
1.223 brouard 9235: } /* End loop on waves */
1.225 brouard 9236:
1.223 brouard 9237: /* Date of death */
1.136 brouard 9238: cutv(stra, strb,line,' ');
1.169 brouard 9239: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9240: }
1.169 brouard 9241: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9242: month=99;
9243: year=9999;
9244: }else{
1.141 brouard 9245: 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 9246: 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);
9247: return 1;
1.136 brouard 9248: }
9249: andc[i]=(double) year;
9250: moisdc[i]=(double) month;
9251: strcpy(line,stra);
9252:
1.223 brouard 9253: /* Date of birth */
1.136 brouard 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){
1.136 brouard 9258: month=99;
9259: year=9999;
9260: }else{
1.141 brouard 9261: 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);
9262: 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 9263: return 1;
1.136 brouard 9264: }
9265: if (year==9999) {
1.141 brouard 9266: 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);
9267: 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 9268: return 1;
9269:
1.136 brouard 9270: }
9271: annais[i]=(double)(year);
9272: moisnais[i]=(double)(month);
9273: strcpy(line,stra);
1.225 brouard 9274:
1.223 brouard 9275: /* Sample weight */
1.136 brouard 9276: cutv(stra, strb,line,' ');
9277: errno=0;
9278: dval=strtod(strb,&endptr);
9279: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9280: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9281: 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 9282: fflush(ficlog);
9283: return 1;
9284: }
9285: weight[i]=dval;
9286: strcpy(line,stra);
1.225 brouard 9287:
1.223 brouard 9288: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9289: cutv(stra, strb, line, ' ');
9290: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9291: lval=-1;
1.223 brouard 9292: }else{
1.225 brouard 9293: errno=0;
9294: /* what_kind_of_number(strb); */
9295: dval=strtod(strb,&endptr);
9296: /* if(strb != endptr && *endptr == '\0') */
9297: /* dval=dlval; */
9298: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9299: if( strb[0]=='\0' || (*endptr != '\0')){
9300: 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);
9301: 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);
9302: return 1;
9303: }
9304: coqvar[iv][i]=dval;
1.226 brouard 9305: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9306: }
9307: strcpy(line,stra);
9308: }/* end loop nqv */
1.136 brouard 9309:
1.223 brouard 9310: /* Covariate values */
1.136 brouard 9311: for (j=ncovcol;j>=1;j--){
9312: cutv(stra, strb,line,' ');
1.223 brouard 9313: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9314: lval=-1;
1.136 brouard 9315: }else{
1.225 brouard 9316: errno=0;
9317: lval=strtol(strb,&endptr,10);
9318: if( strb[0]=='\0' || (*endptr != '\0')){
9319: 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);
9320: 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);
9321: return 1;
9322: }
1.136 brouard 9323: }
9324: if(lval <-1 || lval >1){
1.225 brouard 9325: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9326: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9327: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9328: For example, for multinomial values like 1, 2 and 3,\n \
9329: build V1=0 V2=0 for the reference value (1),\n \
9330: V1=1 V2=0 for (2) \n \
1.136 brouard 9331: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9332: output of IMaCh is often meaningless.\n \
1.136 brouard 9333: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9334: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9335: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9336: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9337: For example, for multinomial values like 1, 2 and 3,\n \
9338: build V1=0 V2=0 for the reference value (1),\n \
9339: V1=1 V2=0 for (2) \n \
1.136 brouard 9340: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9341: output of IMaCh is often meaningless.\n \
1.136 brouard 9342: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9343: return 1;
1.136 brouard 9344: }
9345: covar[j][i]=(double)(lval);
9346: strcpy(line,stra);
9347: }
9348: lstra=strlen(stra);
1.225 brouard 9349:
1.136 brouard 9350: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9351: stratrunc = &(stra[lstra-9]);
9352: num[i]=atol(stratrunc);
9353: }
9354: else
9355: num[i]=atol(stra);
9356: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9357: 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;}*/
9358:
9359: i=i+1;
9360: } /* End loop reading data */
1.225 brouard 9361:
1.136 brouard 9362: *imax=i-1; /* Number of individuals */
9363: fclose(fic);
1.225 brouard 9364:
1.136 brouard 9365: return (0);
1.164 brouard 9366: /* endread: */
1.225 brouard 9367: printf("Exiting readdata: ");
9368: fclose(fic);
9369: return (1);
1.223 brouard 9370: }
1.126 brouard 9371:
1.234 brouard 9372: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9373: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9374: while (*p2 == ' ')
1.234 brouard 9375: p2++;
9376: /* while ((*p1++ = *p2++) !=0) */
9377: /* ; */
9378: /* do */
9379: /* while (*p2 == ' ') */
9380: /* p2++; */
9381: /* while (*p1++ == *p2++); */
9382: *stri=p2;
1.145 brouard 9383: }
9384:
1.235 brouard 9385: int decoderesult ( char resultline[], int nres)
1.230 brouard 9386: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9387: {
1.235 brouard 9388: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9389: char resultsav[MAXLINE];
1.234 brouard 9390: int resultmodel[MAXLINE];
9391: int modelresult[MAXLINE];
1.230 brouard 9392: char stra[80], strb[80], strc[80], strd[80],stre[80];
9393:
1.234 brouard 9394: removefirstspace(&resultline);
1.233 brouard 9395: printf("decoderesult:%s\n",resultline);
1.230 brouard 9396:
9397: if (strstr(resultline,"v") !=0){
9398: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9399: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9400: return 1;
9401: }
9402: trimbb(resultsav, resultline);
9403: if (strlen(resultsav) >1){
9404: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9405: }
1.253 brouard 9406: if(j == 0){ /* Resultline but no = */
9407: TKresult[nres]=0; /* Combination for the nresult and the model */
9408: return (0);
9409: }
9410:
1.234 brouard 9411: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
9412: 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);
9413: 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);
9414: }
9415: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9416: if(nbocc(resultsav,'=') >1){
9417: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
9418: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
9419: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9420: }else
9421: cutl(strc,strd,resultsav,'=');
1.230 brouard 9422: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9423:
1.230 brouard 9424: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9425: Tvarsel[k]=atoi(strc);
9426: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9427: /* cptcovsel++; */
9428: if (nbocc(stra,'=') >0)
9429: strcpy(resultsav,stra); /* and analyzes it */
9430: }
1.235 brouard 9431: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9432: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9433: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9434: match=0;
1.236 brouard 9435: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9436: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9437: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9438: match=1;
9439: break;
9440: }
9441: }
9442: if(match == 0){
9443: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9444: }
9445: }
9446: }
1.235 brouard 9447: /* Checking for missing or useless values in comparison of current model needs */
9448: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9449: match=0;
1.235 brouard 9450: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9451: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9452: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9453: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9454: ++match;
9455: }
9456: }
9457: }
9458: if(match == 0){
9459: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9460: }else if(match > 1){
9461: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9462: }
9463: }
1.235 brouard 9464:
1.234 brouard 9465: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9466: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9467: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9468: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9469: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9470: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9471: /* 1 0 0 0 */
9472: /* 2 1 0 0 */
9473: /* 3 0 1 0 */
9474: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9475: /* 5 0 0 1 */
9476: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9477: /* 7 0 1 1 */
9478: /* 8 1 1 1 */
1.237 brouard 9479: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9480: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9481: /* V5*age V5 known which value for nres? */
9482: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9483: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9484: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9485: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9486: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9487: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9488: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9489: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9490: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9491: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9492: k4++;;
9493: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9494: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9495: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9496: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9497: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9498: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9499: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9500: k4q++;;
9501: }
9502: }
1.234 brouard 9503:
1.235 brouard 9504: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9505: return (0);
9506: }
1.235 brouard 9507:
1.230 brouard 9508: int decodemodel( char model[], int lastobs)
9509: /**< This routine decodes the model and returns:
1.224 brouard 9510: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9511: * - nagesqr = 1 if age*age in the model, otherwise 0.
9512: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9513: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9514: * - cptcovage number of covariates with age*products =2
9515: * - cptcovs number of simple covariates
9516: * - 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
9517: * which is a new column after the 9 (ncovcol) variables.
9518: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9519: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9520: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9521: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9522: */
1.136 brouard 9523: {
1.238 brouard 9524: int i, j, k, ks, v;
1.227 brouard 9525: int j1, k1, k2, k3, k4;
1.136 brouard 9526: char modelsav[80];
1.145 brouard 9527: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9528: char *strpt;
1.136 brouard 9529:
1.145 brouard 9530: /*removespace(model);*/
1.136 brouard 9531: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9532: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9533: if (strstr(model,"AGE") !=0){
1.192 brouard 9534: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9535: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9536: return 1;
9537: }
1.141 brouard 9538: if (strstr(model,"v") !=0){
9539: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9540: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9541: return 1;
9542: }
1.187 brouard 9543: strcpy(modelsav,model);
9544: if ((strpt=strstr(model,"age*age")) !=0){
9545: printf(" strpt=%s, model=%s\n",strpt, model);
9546: if(strpt != model){
1.234 brouard 9547: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9548: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9549: corresponding column of parameters.\n",model);
1.234 brouard 9550: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9551: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9552: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9553: return 1;
1.225 brouard 9554: }
1.187 brouard 9555: nagesqr=1;
9556: if (strstr(model,"+age*age") !=0)
1.234 brouard 9557: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9558: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9559: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9560: else
1.234 brouard 9561: substrchaine(modelsav, model, "age*age");
1.187 brouard 9562: }else
9563: nagesqr=0;
9564: if (strlen(modelsav) >1){
9565: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9566: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9567: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9568: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9569: * cst, age and age*age
9570: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9571: /* including age products which are counted in cptcovage.
9572: * but the covariates which are products must be treated
9573: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9574: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9575: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9576:
9577:
1.187 brouard 9578: /* Design
9579: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9580: * < ncovcol=8 >
9581: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9582: * k= 1 2 3 4 5 6 7 8
9583: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9584: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9585: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9586: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9587: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9588: * Tage[++cptcovage]=k
9589: * if products, new covar are created after ncovcol with k1
9590: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9591: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9592: * 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
9593: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9594: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9595: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9596: * < ncovcol=8 >
9597: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9598: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9599: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9600: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9601: * p Tprod[1]@2={ 6, 5}
9602: *p Tvard[1][1]@4= {7, 8, 5, 6}
9603: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9604: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9605: *How to reorganize?
9606: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9607: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9608: * {2, 1, 4, 8, 5, 6, 3, 7}
9609: * Struct []
9610: */
1.225 brouard 9611:
1.187 brouard 9612: /* This loop fills the array Tvar from the string 'model'.*/
9613: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9614: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9615: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9616: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9617: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9618: /* k=1 Tvar[1]=2 (from V2) */
9619: /* k=5 Tvar[5] */
9620: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9621: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9622: /* } */
1.198 brouard 9623: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9624: /*
9625: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9626: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9627: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9628: }
1.187 brouard 9629: cptcovage=0;
9630: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9631: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9632: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9633: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9634: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9635: /*scanf("%d",i);*/
9636: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9637: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9638: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9639: /* covar is not filled and then is empty */
9640: cptcovprod--;
9641: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9642: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9643: Typevar[k]=1; /* 1 for age product */
9644: cptcovage++; /* Sums the number of covariates which include age as a product */
9645: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9646: /*printf("stre=%s ", stre);*/
9647: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9648: cptcovprod--;
9649: cutl(stre,strb,strc,'V');
9650: Tvar[k]=atoi(stre);
9651: Typevar[k]=1; /* 1 for age product */
9652: cptcovage++;
9653: Tage[cptcovage]=k;
9654: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9655: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9656: cptcovn++;
9657: cptcovprodnoage++;k1++;
9658: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9659: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9660: because this model-covariate is a construction we invent a new column
9661: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9662: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9663: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9664: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9665: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9666: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9667: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9668: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9669: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9670: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9671: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9672: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9673: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9674: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9675: for (i=1; i<=lastobs;i++){
9676: /* Computes the new covariate which is a product of
9677: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9678: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9679: }
9680: } /* End age is not in the model */
9681: } /* End if model includes a product */
9682: else { /* no more sum */
9683: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9684: /* scanf("%d",i);*/
9685: cutl(strd,strc,strb,'V');
9686: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9687: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9688: Tvar[k]=atoi(strd);
9689: Typevar[k]=0; /* 0 for simple covariates */
9690: }
9691: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9692: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9693: scanf("%d",i);*/
1.187 brouard 9694: } /* end of loop + on total covariates */
9695: } /* end if strlen(modelsave == 0) age*age might exist */
9696: } /* end if strlen(model == 0) */
1.136 brouard 9697:
9698: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9699: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9700:
1.136 brouard 9701: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9702: printf("cptcovprod=%d ", cptcovprod);
9703: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9704: scanf("%d ",i);*/
9705:
9706:
1.230 brouard 9707: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9708: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9709: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9710: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9711: k = 1 2 3 4 5 6 7 8 9
9712: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9713: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9714: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9715: Dummy[k] 1 0 0 0 3 1 1 2 3
9716: Tmodelind[combination of covar]=k;
1.225 brouard 9717: */
9718: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9719: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9720: /* 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 9721: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9722: printf("Model=%s\n\
9723: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9724: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9725: 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);
9726: fprintf(ficlog,"Model=%s\n\
9727: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9728: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9729: 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);
1.240 brouard 9730: for(k=1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9731: 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 */
9732: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9733: Fixed[k]= 0;
9734: Dummy[k]= 0;
1.225 brouard 9735: ncoveff++;
1.232 brouard 9736: ncovf++;
1.234 brouard 9737: nsd++;
9738: modell[k].maintype= FTYPE;
9739: TvarsD[nsd]=Tvar[k];
9740: TvarsDind[nsd]=k;
9741: TvarF[ncovf]=Tvar[k];
9742: TvarFind[ncovf]=k;
9743: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9744: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9745: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
9746: Fixed[k]= 0;
9747: Dummy[k]= 0;
9748: ncoveff++;
9749: ncovf++;
9750: modell[k].maintype= FTYPE;
9751: TvarF[ncovf]=Tvar[k];
9752: TvarFind[ncovf]=k;
1.230 brouard 9753: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 9754: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 9755: }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 9756: Fixed[k]= 0;
9757: Dummy[k]= 1;
1.230 brouard 9758: nqfveff++;
1.234 brouard 9759: modell[k].maintype= FTYPE;
9760: modell[k].subtype= FQ;
9761: nsq++;
9762: TvarsQ[nsq]=Tvar[k];
9763: TvarsQind[nsq]=k;
1.232 brouard 9764: ncovf++;
1.234 brouard 9765: TvarF[ncovf]=Tvar[k];
9766: TvarFind[ncovf]=k;
1.231 brouard 9767: 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 9768: 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 9769: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 9770: Fixed[k]= 1;
9771: Dummy[k]= 0;
1.225 brouard 9772: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 9773: modell[k].maintype= VTYPE;
9774: modell[k].subtype= VD;
9775: nsd++;
9776: TvarsD[nsd]=Tvar[k];
9777: TvarsDind[nsd]=k;
9778: ncovv++; /* Only simple time varying variables */
9779: TvarV[ncovv]=Tvar[k];
1.242 brouard 9780: 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 9781: 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 */
9782: 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 9783: 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);
9784: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 9785: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 9786: Fixed[k]= 1;
9787: Dummy[k]= 1;
9788: nqtveff++;
9789: modell[k].maintype= VTYPE;
9790: modell[k].subtype= VQ;
9791: ncovv++; /* Only simple time varying variables */
9792: nsq++;
9793: TvarsQ[nsq]=Tvar[k];
9794: TvarsQind[nsq]=k;
9795: TvarV[ncovv]=Tvar[k];
1.242 brouard 9796: 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 9797: 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 */
9798: 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 9799: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9800: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9801: 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 9802: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9803: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9804: ncova++;
9805: TvarA[ncova]=Tvar[k];
9806: TvarAind[ncova]=k;
1.231 brouard 9807: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9808: Fixed[k]= 2;
9809: Dummy[k]= 2;
9810: modell[k].maintype= ATYPE;
9811: modell[k].subtype= APFD;
9812: /* ncoveff++; */
1.227 brouard 9813: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 9814: Fixed[k]= 2;
9815: Dummy[k]= 3;
9816: modell[k].maintype= ATYPE;
9817: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
9818: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 9819: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 9820: Fixed[k]= 3;
9821: Dummy[k]= 2;
9822: modell[k].maintype= ATYPE;
9823: modell[k].subtype= APVD; /* Product age * varying dummy */
9824: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 9825: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9826: Fixed[k]= 3;
9827: Dummy[k]= 3;
9828: modell[k].maintype= ATYPE;
9829: modell[k].subtype= APVQ; /* Product age * varying quantitative */
9830: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 9831: }
9832: }else if (Typevar[k] == 2) { /* product without age */
9833: k1=Tposprod[k];
9834: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 9835: if(Tvard[k1][2] <=ncovcol){
9836: Fixed[k]= 1;
9837: Dummy[k]= 0;
9838: modell[k].maintype= FTYPE;
9839: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
9840: ncovf++; /* Fixed variables without age */
9841: TvarF[ncovf]=Tvar[k];
9842: TvarFind[ncovf]=k;
9843: }else if(Tvard[k1][2] <=ncovcol+nqv){
9844: Fixed[k]= 0; /* or 2 ?*/
9845: Dummy[k]= 1;
9846: modell[k].maintype= FTYPE;
9847: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
9848: ncovf++; /* Varying variables without age */
9849: TvarF[ncovf]=Tvar[k];
9850: TvarFind[ncovf]=k;
9851: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9852: Fixed[k]= 1;
9853: Dummy[k]= 0;
9854: modell[k].maintype= VTYPE;
9855: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
9856: ncovv++; /* Varying variables without age */
9857: TvarV[ncovv]=Tvar[k];
9858: TvarVind[ncovv]=k;
9859: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9860: Fixed[k]= 1;
9861: Dummy[k]= 1;
9862: modell[k].maintype= VTYPE;
9863: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
9864: ncovv++; /* Varying variables without age */
9865: TvarV[ncovv]=Tvar[k];
9866: TvarVind[ncovv]=k;
9867: }
1.227 brouard 9868: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 9869: if(Tvard[k1][2] <=ncovcol){
9870: Fixed[k]= 0; /* or 2 ?*/
9871: Dummy[k]= 1;
9872: modell[k].maintype= FTYPE;
9873: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
9874: ncovf++; /* Fixed variables without age */
9875: TvarF[ncovf]=Tvar[k];
9876: TvarFind[ncovf]=k;
9877: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9878: Fixed[k]= 1;
9879: Dummy[k]= 1;
9880: modell[k].maintype= VTYPE;
9881: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
9882: ncovv++; /* Varying variables without age */
9883: TvarV[ncovv]=Tvar[k];
9884: TvarVind[ncovv]=k;
9885: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9886: Fixed[k]= 1;
9887: Dummy[k]= 1;
9888: modell[k].maintype= VTYPE;
9889: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
9890: ncovv++; /* Varying variables without age */
9891: TvarV[ncovv]=Tvar[k];
9892: TvarVind[ncovv]=k;
9893: ncovv++; /* Varying variables without age */
9894: TvarV[ncovv]=Tvar[k];
9895: TvarVind[ncovv]=k;
9896: }
1.227 brouard 9897: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 9898: if(Tvard[k1][2] <=ncovcol){
9899: Fixed[k]= 1;
9900: Dummy[k]= 1;
9901: modell[k].maintype= VTYPE;
9902: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
9903: ncovv++; /* Varying variables without age */
9904: TvarV[ncovv]=Tvar[k];
9905: TvarVind[ncovv]=k;
9906: }else if(Tvard[k1][2] <=ncovcol+nqv){
9907: Fixed[k]= 1;
9908: Dummy[k]= 1;
9909: modell[k].maintype= VTYPE;
9910: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
9911: ncovv++; /* Varying variables without age */
9912: TvarV[ncovv]=Tvar[k];
9913: TvarVind[ncovv]=k;
9914: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9915: Fixed[k]= 1;
9916: Dummy[k]= 0;
9917: modell[k].maintype= VTYPE;
9918: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
9919: ncovv++; /* Varying variables without age */
9920: TvarV[ncovv]=Tvar[k];
9921: TvarVind[ncovv]=k;
9922: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9923: Fixed[k]= 1;
9924: Dummy[k]= 1;
9925: modell[k].maintype= VTYPE;
9926: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
9927: ncovv++; /* Varying variables without age */
9928: TvarV[ncovv]=Tvar[k];
9929: TvarVind[ncovv]=k;
9930: }
1.227 brouard 9931: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9932: if(Tvard[k1][2] <=ncovcol){
9933: Fixed[k]= 1;
9934: Dummy[k]= 1;
9935: modell[k].maintype= VTYPE;
9936: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
9937: ncovv++; /* Varying variables without age */
9938: TvarV[ncovv]=Tvar[k];
9939: TvarVind[ncovv]=k;
9940: }else if(Tvard[k1][2] <=ncovcol+nqv){
9941: Fixed[k]= 1;
9942: Dummy[k]= 1;
9943: modell[k].maintype= VTYPE;
9944: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
9945: ncovv++; /* Varying variables without age */
9946: TvarV[ncovv]=Tvar[k];
9947: TvarVind[ncovv]=k;
9948: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9949: Fixed[k]= 1;
9950: Dummy[k]= 1;
9951: modell[k].maintype= VTYPE;
9952: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
9953: ncovv++; /* Varying variables without age */
9954: TvarV[ncovv]=Tvar[k];
9955: TvarVind[ncovv]=k;
9956: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9957: Fixed[k]= 1;
9958: Dummy[k]= 1;
9959: modell[k].maintype= VTYPE;
9960: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
9961: ncovv++; /* Varying variables without age */
9962: TvarV[ncovv]=Tvar[k];
9963: TvarVind[ncovv]=k;
9964: }
1.227 brouard 9965: }else{
1.240 brouard 9966: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9967: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9968: } /*end k1*/
1.225 brouard 9969: }else{
1.226 brouard 9970: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
9971: 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 9972: }
1.227 brouard 9973: 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 9974: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 9975: 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]);
9976: }
9977: /* Searching for doublons in the model */
9978: for(k1=1; k1<= cptcovt;k1++){
9979: for(k2=1; k2 <k1;k2++){
9980: if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){
1.234 brouard 9981: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
9982: if(Tvar[k1]==Tvar[k2]){
9983: 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[Tvar[k1]],Dummy[Tvar[k1]]);
9984: 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[Tvar[k1]],Dummy[Tvar[k1]]); fflush(ficlog);
9985: return(1);
9986: }
9987: }else if (Typevar[k1] ==2){
9988: k3=Tposprod[k1];
9989: k4=Tposprod[k2];
9990: 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])) ){
9991: 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]]);
9992: 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);
9993: return(1);
9994: }
9995: }
1.227 brouard 9996: }
9997: }
1.225 brouard 9998: }
9999: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10000: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10001: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10002: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10003: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10004: /*endread:*/
1.225 brouard 10005: printf("Exiting decodemodel: ");
10006: return (1);
1.136 brouard 10007: }
10008:
1.169 brouard 10009: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10010: {/* Check ages at death */
1.136 brouard 10011: int i, m;
1.218 brouard 10012: int firstone=0;
10013:
1.136 brouard 10014: for (i=1; i<=imx; i++) {
10015: for(m=2; (m<= maxwav); m++) {
10016: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10017: anint[m][i]=9999;
1.216 brouard 10018: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10019: s[m][i]=-1;
1.136 brouard 10020: }
10021: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10022: *nberr = *nberr + 1;
1.218 brouard 10023: if(firstone == 0){
10024: firstone=1;
1.260 brouard 10025: 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 10026: }
1.262 brouard 10027: 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 10028: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10029: }
10030: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10031: (*nberr)++;
1.259 brouard 10032: 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 10033: 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 10034: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10035: }
10036: }
10037: }
10038:
10039: for (i=1; i<=imx; i++) {
10040: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10041: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10042: 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 10043: if (s[m][i] >= nlstate+1) {
1.169 brouard 10044: if(agedc[i]>0){
10045: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10046: agev[m][i]=agedc[i];
1.214 brouard 10047: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10048: }else {
1.136 brouard 10049: if ((int)andc[i]!=9999){
10050: nbwarn++;
10051: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10052: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10053: agev[m][i]=-1;
10054: }
10055: }
1.169 brouard 10056: } /* agedc > 0 */
1.214 brouard 10057: } /* end if */
1.136 brouard 10058: else if(s[m][i] !=9){ /* Standard case, age in fractional
10059: years but with the precision of a month */
10060: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10061: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10062: agev[m][i]=1;
10063: else if(agev[m][i] < *agemin){
10064: *agemin=agev[m][i];
10065: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10066: }
10067: else if(agev[m][i] >*agemax){
10068: *agemax=agev[m][i];
1.156 brouard 10069: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10070: }
10071: /*agev[m][i]=anint[m][i]-annais[i];*/
10072: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10073: } /* en if 9*/
1.136 brouard 10074: else { /* =9 */
1.214 brouard 10075: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10076: agev[m][i]=1;
10077: s[m][i]=-1;
10078: }
10079: }
1.214 brouard 10080: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10081: agev[m][i]=1;
1.214 brouard 10082: else{
10083: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10084: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10085: agev[m][i]=0;
10086: }
10087: } /* End for lastpass */
10088: }
1.136 brouard 10089:
10090: for (i=1; i<=imx; i++) {
10091: for(m=firstpass; (m<=lastpass); m++){
10092: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10093: (*nberr)++;
1.136 brouard 10094: 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);
10095: 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);
10096: return 1;
10097: }
10098: }
10099: }
10100:
10101: /*for (i=1; i<=imx; i++){
10102: for (m=firstpass; (m<lastpass); m++){
10103: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10104: }
10105:
10106: }*/
10107:
10108:
1.139 brouard 10109: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10110: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10111:
10112: return (0);
1.164 brouard 10113: /* endread:*/
1.136 brouard 10114: printf("Exiting calandcheckages: ");
10115: return (1);
10116: }
10117:
1.172 brouard 10118: #if defined(_MSC_VER)
10119: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10120: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10121: //#include "stdafx.h"
10122: //#include <stdio.h>
10123: //#include <tchar.h>
10124: //#include <windows.h>
10125: //#include <iostream>
10126: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10127:
10128: LPFN_ISWOW64PROCESS fnIsWow64Process;
10129:
10130: BOOL IsWow64()
10131: {
10132: BOOL bIsWow64 = FALSE;
10133:
10134: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10135: // (HANDLE, PBOOL);
10136:
10137: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10138:
10139: HMODULE module = GetModuleHandle(_T("kernel32"));
10140: const char funcName[] = "IsWow64Process";
10141: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10142: GetProcAddress(module, funcName);
10143:
10144: if (NULL != fnIsWow64Process)
10145: {
10146: if (!fnIsWow64Process(GetCurrentProcess(),
10147: &bIsWow64))
10148: //throw std::exception("Unknown error");
10149: printf("Unknown error\n");
10150: }
10151: return bIsWow64 != FALSE;
10152: }
10153: #endif
1.177 brouard 10154:
1.191 brouard 10155: void syscompilerinfo(int logged)
1.167 brouard 10156: {
10157: /* #include "syscompilerinfo.h"*/
1.185 brouard 10158: /* command line Intel compiler 32bit windows, XP compatible:*/
10159: /* /GS /W3 /Gy
10160: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10161: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10162: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10163: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10164: */
10165: /* 64 bits */
1.185 brouard 10166: /*
10167: /GS /W3 /Gy
10168: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10169: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10170: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10171: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10172: /* Optimization are useless and O3 is slower than O2 */
10173: /*
10174: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10175: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10176: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10177: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10178: */
1.186 brouard 10179: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10180: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10181: /PDB:"visual studio
10182: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10183: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10184: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10185: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10186: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10187: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10188: uiAccess='false'"
10189: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10190: /NOLOGO /TLBID:1
10191: */
1.177 brouard 10192: #if defined __INTEL_COMPILER
1.178 brouard 10193: #if defined(__GNUC__)
10194: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10195: #endif
1.177 brouard 10196: #elif defined(__GNUC__)
1.179 brouard 10197: #ifndef __APPLE__
1.174 brouard 10198: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10199: #endif
1.177 brouard 10200: struct utsname sysInfo;
1.178 brouard 10201: int cross = CROSS;
10202: if (cross){
10203: printf("Cross-");
1.191 brouard 10204: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10205: }
1.174 brouard 10206: #endif
10207:
1.171 brouard 10208: #include <stdint.h>
1.178 brouard 10209:
1.191 brouard 10210: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10211: #if defined(__clang__)
1.191 brouard 10212: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10213: #endif
10214: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10215: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10216: #endif
10217: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10218: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10219: #endif
10220: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10221: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10222: #endif
10223: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10224: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10225: #endif
10226: #if defined(_MSC_VER)
1.191 brouard 10227: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10228: #endif
10229: #if defined(__PGI)
1.191 brouard 10230: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10231: #endif
10232: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10233: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10234: #endif
1.191 brouard 10235: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10236:
1.167 brouard 10237: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10238: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10239: // Windows (x64 and x86)
1.191 brouard 10240: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10241: #elif __unix__ // all unices, not all compilers
10242: // Unix
1.191 brouard 10243: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10244: #elif __linux__
10245: // linux
1.191 brouard 10246: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10247: #elif __APPLE__
1.174 brouard 10248: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10249: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10250: #endif
10251:
10252: /* __MINGW32__ */
10253: /* __CYGWIN__ */
10254: /* __MINGW64__ */
10255: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10256: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10257: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10258: /* _WIN64 // Defined for applications for Win64. */
10259: /* _M_X64 // Defined for compilations that target x64 processors. */
10260: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10261:
1.167 brouard 10262: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10263: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10264: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10265: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10266: #else
1.191 brouard 10267: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10268: #endif
10269:
1.169 brouard 10270: #if defined(__GNUC__)
10271: # if defined(__GNUC_PATCHLEVEL__)
10272: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10273: + __GNUC_MINOR__ * 100 \
10274: + __GNUC_PATCHLEVEL__)
10275: # else
10276: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10277: + __GNUC_MINOR__ * 100)
10278: # endif
1.174 brouard 10279: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10280: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10281:
10282: if (uname(&sysInfo) != -1) {
10283: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10284: 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 10285: }
10286: else
10287: perror("uname() error");
1.179 brouard 10288: //#ifndef __INTEL_COMPILER
10289: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10290: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10291: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10292: #endif
1.169 brouard 10293: #endif
1.172 brouard 10294:
10295: // void main()
10296: // {
1.169 brouard 10297: #if defined(_MSC_VER)
1.174 brouard 10298: if (IsWow64()){
1.191 brouard 10299: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10300: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10301: }
10302: else{
1.191 brouard 10303: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10304: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10305: }
1.172 brouard 10306: // printf("\nPress Enter to continue...");
10307: // getchar();
10308: // }
10309:
1.169 brouard 10310: #endif
10311:
1.167 brouard 10312:
1.219 brouard 10313: }
1.136 brouard 10314:
1.219 brouard 10315: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.180 brouard 10316: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.235 brouard 10317: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10318: /* double ftolpl = 1.e-10; */
1.180 brouard 10319: double age, agebase, agelim;
1.203 brouard 10320: double tot;
1.180 brouard 10321:
1.202 brouard 10322: strcpy(filerespl,"PL_");
10323: strcat(filerespl,fileresu);
10324: if((ficrespl=fopen(filerespl,"w"))==NULL) {
10325: printf("Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10326: fprintf(ficlog,"Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10327: }
1.227 brouard 10328: printf("\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
10329: fprintf(ficlog,"\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10330: pstamp(ficrespl);
1.203 brouard 10331: fprintf(ficrespl,"# Period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10332: fprintf(ficrespl,"#Age ");
10333: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10334: fprintf(ficrespl,"\n");
1.180 brouard 10335:
1.219 brouard 10336: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10337:
1.219 brouard 10338: agebase=ageminpar;
10339: agelim=agemaxpar;
1.180 brouard 10340:
1.227 brouard 10341: /* i1=pow(2,ncoveff); */
1.234 brouard 10342: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10343: if (cptcovn < 1){i1=1;}
1.180 brouard 10344:
1.238 brouard 10345: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10346: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10347: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10348: continue;
1.235 brouard 10349:
1.238 brouard 10350: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10351: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10352: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10353: /* k=k+1; */
10354: /* to clean */
10355: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10356: fprintf(ficrespl,"#******");
10357: printf("#******");
10358: fprintf(ficlog,"#******");
10359: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10360: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10361: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10362: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10363: }
10364: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10365: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10366: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10367: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10368: }
10369: fprintf(ficrespl,"******\n");
10370: printf("******\n");
10371: fprintf(ficlog,"******\n");
10372: if(invalidvarcomb[k]){
10373: printf("\nCombination (%d) ignored because no case \n",k);
10374: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10375: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10376: continue;
10377: }
1.219 brouard 10378:
1.238 brouard 10379: fprintf(ficrespl,"#Age ");
10380: for(j=1;j<=cptcoveff;j++) {
10381: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10382: }
10383: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10384: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10385:
1.238 brouard 10386: for (age=agebase; age<=agelim; age++){
10387: /* for (age=agebase; age<=agebase; age++){ */
10388: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10389: fprintf(ficrespl,"%.0f ",age );
10390: for(j=1;j<=cptcoveff;j++)
10391: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10392: tot=0.;
10393: for(i=1; i<=nlstate;i++){
10394: tot += prlim[i][i];
10395: fprintf(ficrespl," %.5f", prlim[i][i]);
10396: }
10397: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10398: } /* Age */
10399: /* was end of cptcod */
10400: } /* cptcov */
10401: } /* nres */
1.219 brouard 10402: return 0;
1.180 brouard 10403: }
10404:
1.218 brouard 10405: 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){
10406: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
10407:
10408: /* Computes the back prevalence limit for any combination of covariate values
10409: * at any age between ageminpar and agemaxpar
10410: */
1.235 brouard 10411: int i, j, k, i1, nres=0 ;
1.217 brouard 10412: /* double ftolpl = 1.e-10; */
10413: double age, agebase, agelim;
10414: double tot;
1.218 brouard 10415: /* double ***mobaverage; */
10416: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10417:
10418: strcpy(fileresplb,"PLB_");
10419: strcat(fileresplb,fileresu);
10420: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
10421: printf("Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
10422: fprintf(ficlog,"Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
10423: }
10424: printf("Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
10425: fprintf(ficlog,"Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
10426: pstamp(ficresplb);
10427: fprintf(ficresplb,"# Period (stable) back prevalence. Precision given by ftolpl=%g \n", ftolpl);
10428: fprintf(ficresplb,"#Age ");
10429: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10430: fprintf(ficresplb,"\n");
10431:
1.218 brouard 10432:
10433: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10434:
10435: agebase=ageminpar;
10436: agelim=agemaxpar;
10437:
10438:
1.227 brouard 10439: i1=pow(2,cptcoveff);
1.218 brouard 10440: if (cptcovn < 1){i1=1;}
1.227 brouard 10441:
1.238 brouard 10442: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10443: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10444: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10445: continue;
10446: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10447: fprintf(ficresplb,"#******");
10448: printf("#******");
10449: fprintf(ficlog,"#******");
10450: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10451: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10452: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10453: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10454: }
10455: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10456: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10457: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10458: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10459: }
10460: fprintf(ficresplb,"******\n");
10461: printf("******\n");
10462: fprintf(ficlog,"******\n");
10463: if(invalidvarcomb[k]){
10464: printf("\nCombination (%d) ignored because no cases \n",k);
10465: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10466: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10467: continue;
10468: }
1.218 brouard 10469:
1.238 brouard 10470: fprintf(ficresplb,"#Age ");
10471: for(j=1;j<=cptcoveff;j++) {
10472: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10473: }
10474: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10475: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10476:
10477:
1.238 brouard 10478: for (age=agebase; age<=agelim; age++){
10479: /* for (age=agebase; age<=agebase; age++){ */
10480: if(mobilavproj > 0){
10481: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10482: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10483: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10484: }else if (mobilavproj == 0){
10485: 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);
10486: 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);
10487: exit(1);
10488: }else{
10489: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10490: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10491: /* printf("TOTOT\n"); */
10492: /* exit(1); */
1.238 brouard 10493: }
10494: fprintf(ficresplb,"%.0f ",age );
10495: for(j=1;j<=cptcoveff;j++)
10496: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10497: tot=0.;
10498: for(i=1; i<=nlstate;i++){
10499: tot += bprlim[i][i];
10500: fprintf(ficresplb," %.5f", bprlim[i][i]);
10501: }
10502: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10503: } /* Age */
10504: /* was end of cptcod */
1.255 brouard 10505: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10506: } /* end of any combination */
10507: } /* end of nres */
1.218 brouard 10508: /* hBijx(p, bage, fage); */
10509: /* fclose(ficrespijb); */
10510:
10511: return 0;
1.217 brouard 10512: }
1.218 brouard 10513:
1.180 brouard 10514: int hPijx(double *p, int bage, int fage){
10515: /*------------- h Pij x at various ages ------------*/
10516:
10517: int stepsize;
10518: int agelim;
10519: int hstepm;
10520: int nhstepm;
1.235 brouard 10521: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10522:
10523: double agedeb;
10524: double ***p3mat;
10525:
1.201 brouard 10526: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10527: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10528: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10529: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10530: }
10531: printf("Computing pij: result on file '%s' \n", filerespij);
10532: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10533:
10534: stepsize=(int) (stepm+YEARM-1)/YEARM;
10535: /*if (stepm<=24) stepsize=2;*/
10536:
10537: agelim=AGESUP;
10538: hstepm=stepsize*YEARM; /* Every year of age */
10539: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10540:
1.180 brouard 10541: /* hstepm=1; aff par mois*/
10542: pstamp(ficrespij);
10543: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10544: i1= pow(2,cptcoveff);
1.218 brouard 10545: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10546: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10547: /* k=k+1; */
1.235 brouard 10548: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10549: for(k=1; k<=i1;k++){
1.253 brouard 10550: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10551: continue;
1.183 brouard 10552: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10553: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10554: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10555: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10556: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10557: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10558: }
1.183 brouard 10559: fprintf(ficrespij,"******\n");
10560:
10561: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10562: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10563: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10564:
10565: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10566:
1.183 brouard 10567: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10568: oldm=oldms;savm=savms;
1.235 brouard 10569: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10570: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10571: for(i=1; i<=nlstate;i++)
10572: for(j=1; j<=nlstate+ndeath;j++)
10573: fprintf(ficrespij," %1d-%1d",i,j);
10574: fprintf(ficrespij,"\n");
10575: for (h=0; h<=nhstepm; h++){
10576: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10577: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10578: for(i=1; i<=nlstate;i++)
10579: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10580: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10581: fprintf(ficrespij,"\n");
10582: }
1.183 brouard 10583: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10584: fprintf(ficrespij,"\n");
10585: }
1.180 brouard 10586: /*}*/
10587: }
1.218 brouard 10588: return 0;
1.180 brouard 10589: }
1.218 brouard 10590:
10591: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10592: /*------------- h Bij x at various ages ------------*/
10593:
10594: int stepsize;
1.218 brouard 10595: /* int agelim; */
10596: int ageminl;
1.217 brouard 10597: int hstepm;
10598: int nhstepm;
1.238 brouard 10599: int h, i, i1, j, k, nres;
1.218 brouard 10600:
1.217 brouard 10601: double agedeb;
10602: double ***p3mat;
1.218 brouard 10603:
10604: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10605: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10606: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10607: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10608: }
10609: printf("Computing pij back: result on file '%s' \n", filerespijb);
10610: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10611:
10612: stepsize=(int) (stepm+YEARM-1)/YEARM;
10613: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10614:
1.218 brouard 10615: /* agelim=AGESUP; */
10616: ageminl=30;
10617: hstepm=stepsize*YEARM; /* Every year of age */
10618: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10619:
10620: /* hstepm=1; aff par mois*/
10621: pstamp(ficrespijb);
1.255 brouard 10622: 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 10623: i1= pow(2,cptcoveff);
1.218 brouard 10624: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10625: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10626: /* k=k+1; */
1.238 brouard 10627: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10628: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10629: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10630: continue;
10631: fprintf(ficrespijb,"\n#****** ");
10632: for(j=1;j<=cptcoveff;j++)
10633: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10634: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10635: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10636: }
10637: fprintf(ficrespijb,"******\n");
1.264 brouard 10638: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10639: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10640: continue;
10641: }
10642:
10643: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10644: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10645: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
10646: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10647: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
10648:
10649: /* nhstepm=nhstepm*YEARM; aff par mois*/
10650:
1.266 brouard 10651: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10652: /* and memory limitations if stepm is small */
10653:
1.238 brouard 10654: /* oldm=oldms;savm=savms; */
10655: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10656: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10657: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10658: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10659: for(i=1; i<=nlstate;i++)
10660: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10661: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10662: fprintf(ficrespijb,"\n");
1.238 brouard 10663: for (h=0; h<=nhstepm; h++){
10664: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10665: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10666: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10667: for(i=1; i<=nlstate;i++)
10668: for(j=1; j<=nlstate+ndeath;j++)
10669: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10670: fprintf(ficrespijb,"\n");
10671: }
10672: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10673: fprintf(ficrespijb,"\n");
10674: } /* end age deb */
10675: } /* end combination */
10676: } /* end nres */
1.218 brouard 10677: return 0;
10678: } /* hBijx */
1.217 brouard 10679:
1.180 brouard 10680:
1.136 brouard 10681: /***********************************************/
10682: /**************** Main Program *****************/
10683: /***********************************************/
10684:
10685: int main(int argc, char *argv[])
10686: {
10687: #ifdef GSL
10688: const gsl_multimin_fminimizer_type *T;
10689: size_t iteri = 0, it;
10690: int rval = GSL_CONTINUE;
10691: int status = GSL_SUCCESS;
10692: double ssval;
10693: #endif
10694: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.164 brouard 10695: int i,j, k, n=MAXN,iter=0,m,size=100, cptcod;
1.209 brouard 10696: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10697: int jj, ll, li, lj, lk;
1.136 brouard 10698: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10699: int num_filled;
1.136 brouard 10700: int itimes;
10701: int NDIM=2;
10702: int vpopbased=0;
1.235 brouard 10703: int nres=0;
1.258 brouard 10704: int endishere=0;
1.277 brouard 10705: int noffset=0;
1.274 brouard 10706: int ncurrv=0; /* Temporary variable */
10707:
1.164 brouard 10708: char ca[32], cb[32];
1.136 brouard 10709: /* FILE *fichtm; *//* Html File */
10710: /* FILE *ficgp;*/ /*Gnuplot File */
10711: struct stat info;
1.191 brouard 10712: double agedeb=0.;
1.194 brouard 10713:
10714: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10715: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10716:
1.165 brouard 10717: double fret;
1.191 brouard 10718: double dum=0.; /* Dummy variable */
1.136 brouard 10719: double ***p3mat;
1.218 brouard 10720: /* double ***mobaverage; */
1.164 brouard 10721:
10722: char line[MAXLINE];
1.197 brouard 10723: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10724:
1.234 brouard 10725: char modeltemp[MAXLINE];
1.230 brouard 10726: char resultline[MAXLINE];
10727:
1.136 brouard 10728: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10729: char *tok, *val; /* pathtot */
1.136 brouard 10730: int firstobs=1, lastobs=10;
1.195 brouard 10731: int c, h , cpt, c2;
1.191 brouard 10732: int jl=0;
10733: int i1, j1, jk, stepsize=0;
1.194 brouard 10734: int count=0;
10735:
1.164 brouard 10736: int *tab;
1.136 brouard 10737: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.217 brouard 10738: int backcast=0;
1.136 brouard 10739: int mobilav=0,popforecast=0;
1.191 brouard 10740: int hstepm=0, nhstepm=0;
1.136 brouard 10741: int agemortsup;
10742: float sumlpop=0.;
10743: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
10744: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
10745:
1.191 brouard 10746: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 10747: double ftolpl=FTOL;
10748: double **prlim;
1.217 brouard 10749: double **bprlim;
1.136 brouard 10750: double ***param; /* Matrix of parameters */
1.251 brouard 10751: double ***paramstart; /* Matrix of starting parameter values */
10752: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 10753: double **matcov; /* Matrix of covariance */
1.203 brouard 10754: double **hess; /* Hessian matrix */
1.136 brouard 10755: double ***delti3; /* Scale */
10756: double *delti; /* Scale */
10757: double ***eij, ***vareij;
10758: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 10759:
1.136 brouard 10760: double *epj, vepp;
1.164 brouard 10761:
1.273 brouard 10762: double dateprev1, dateprev2;
10763: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0;
10764: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0;
1.217 brouard 10765:
1.136 brouard 10766: double **ximort;
1.145 brouard 10767: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 10768: int *dcwave;
10769:
1.164 brouard 10770: char z[1]="c";
1.136 brouard 10771:
10772: /*char *strt;*/
10773: char strtend[80];
1.126 brouard 10774:
1.164 brouard 10775:
1.126 brouard 10776: /* setlocale (LC_ALL, ""); */
10777: /* bindtextdomain (PACKAGE, LOCALEDIR); */
10778: /* textdomain (PACKAGE); */
10779: /* setlocale (LC_CTYPE, ""); */
10780: /* setlocale (LC_MESSAGES, ""); */
10781:
10782: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 10783: rstart_time = time(NULL);
10784: /* (void) gettimeofday(&start_time,&tzp);*/
10785: start_time = *localtime(&rstart_time);
1.126 brouard 10786: curr_time=start_time;
1.157 brouard 10787: /*tml = *localtime(&start_time.tm_sec);*/
10788: /* strcpy(strstart,asctime(&tml)); */
10789: strcpy(strstart,asctime(&start_time));
1.126 brouard 10790:
10791: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 10792: /* tp.tm_sec = tp.tm_sec +86400; */
10793: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 10794: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
10795: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
10796: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 10797: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 10798: /* strt=asctime(&tmg); */
10799: /* printf("Time(after) =%s",strstart); */
10800: /* (void) time (&time_value);
10801: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
10802: * tm = *localtime(&time_value);
10803: * strstart=asctime(&tm);
10804: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
10805: */
10806:
10807: nberr=0; /* Number of errors and warnings */
10808: nbwarn=0;
1.184 brouard 10809: #ifdef WIN32
10810: _getcwd(pathcd, size);
10811: #else
1.126 brouard 10812: getcwd(pathcd, size);
1.184 brouard 10813: #endif
1.191 brouard 10814: syscompilerinfo(0);
1.196 brouard 10815: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 10816: if(argc <=1){
10817: printf("\nEnter the parameter file name: ");
1.205 brouard 10818: if(!fgets(pathr,FILENAMELENGTH,stdin)){
10819: printf("ERROR Empty parameter file name\n");
10820: goto end;
10821: }
1.126 brouard 10822: i=strlen(pathr);
10823: if(pathr[i-1]=='\n')
10824: pathr[i-1]='\0';
1.156 brouard 10825: i=strlen(pathr);
1.205 brouard 10826: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 10827: pathr[i-1]='\0';
1.205 brouard 10828: }
10829: i=strlen(pathr);
10830: if( i==0 ){
10831: printf("ERROR Empty parameter file name\n");
10832: goto end;
10833: }
10834: for (tok = pathr; tok != NULL; ){
1.126 brouard 10835: printf("Pathr |%s|\n",pathr);
10836: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
10837: printf("val= |%s| pathr=%s\n",val,pathr);
10838: strcpy (pathtot, val);
10839: if(pathr[0] == '\0') break; /* Dirty */
10840: }
10841: }
1.281 brouard 10842: else if (argc<=2){
10843: strcpy(pathtot,argv[1]);
10844: }
1.126 brouard 10845: else{
10846: strcpy(pathtot,argv[1]);
1.281 brouard 10847: strcpy(z,argv[2]);
10848: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 10849: }
10850: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
10851: /*cygwin_split_path(pathtot,path,optionfile);
10852: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
10853: /* cutv(path,optionfile,pathtot,'\\');*/
10854:
10855: /* Split argv[0], imach program to get pathimach */
10856: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
10857: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10858: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10859: /* strcpy(pathimach,argv[0]); */
10860: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
10861: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
10862: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 10863: #ifdef WIN32
10864: _chdir(path); /* Can be a relative path */
10865: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
10866: #else
1.126 brouard 10867: chdir(path); /* Can be a relative path */
1.184 brouard 10868: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
10869: #endif
10870: printf("Current directory %s!\n",pathcd);
1.126 brouard 10871: strcpy(command,"mkdir ");
10872: strcat(command,optionfilefiname);
10873: if((outcmd=system(command)) != 0){
1.169 brouard 10874: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 10875: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
10876: /* fclose(ficlog); */
10877: /* exit(1); */
10878: }
10879: /* if((imk=mkdir(optionfilefiname))<0){ */
10880: /* perror("mkdir"); */
10881: /* } */
10882:
10883: /*-------- arguments in the command line --------*/
10884:
1.186 brouard 10885: /* Main Log file */
1.126 brouard 10886: strcat(filelog, optionfilefiname);
10887: strcat(filelog,".log"); /* */
10888: if((ficlog=fopen(filelog,"w"))==NULL) {
10889: printf("Problem with logfile %s\n",filelog);
10890: goto end;
10891: }
10892: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 10893: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 10894: fprintf(ficlog,"\nEnter the parameter file name: \n");
10895: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
10896: path=%s \n\
10897: optionfile=%s\n\
10898: optionfilext=%s\n\
1.156 brouard 10899: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 10900:
1.197 brouard 10901: syscompilerinfo(1);
1.167 brouard 10902:
1.126 brouard 10903: printf("Local time (at start):%s",strstart);
10904: fprintf(ficlog,"Local time (at start): %s",strstart);
10905: fflush(ficlog);
10906: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 10907: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 10908:
10909: /* */
10910: strcpy(fileres,"r");
10911: strcat(fileres, optionfilefiname);
1.201 brouard 10912: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 10913: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 10914: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 10915:
1.186 brouard 10916: /* Main ---------arguments file --------*/
1.126 brouard 10917:
10918: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 10919: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
10920: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 10921: fflush(ficlog);
1.149 brouard 10922: /* goto end; */
10923: exit(70);
1.126 brouard 10924: }
10925:
10926: strcpy(filereso,"o");
1.201 brouard 10927: strcat(filereso,fileresu);
1.126 brouard 10928: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
10929: printf("Problem with Output resultfile: %s\n", filereso);
10930: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
10931: fflush(ficlog);
10932: goto end;
10933: }
1.278 brouard 10934: /*-------- Rewriting parameter file ----------*/
10935: strcpy(rfileres,"r"); /* "Rparameterfile */
10936: strcat(rfileres,optionfilefiname); /* Parameter file first name */
10937: strcat(rfileres,"."); /* */
10938: strcat(rfileres,optionfilext); /* Other files have txt extension */
10939: if((ficres =fopen(rfileres,"w"))==NULL) {
10940: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
10941: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
10942: fflush(ficlog);
10943: goto end;
10944: }
10945: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 10946:
1.278 brouard 10947:
1.126 brouard 10948: /* Reads comments: lines beginning with '#' */
10949: numlinepar=0;
1.277 brouard 10950: /* Is it a BOM UTF-8 Windows file? */
10951: /* First parameter line */
1.197 brouard 10952: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 10953: noffset=0;
10954: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10955: {
10956: noffset=noffset+3;
10957: printf("# File is an UTF8 Bom.\n"); // 0xBF
10958: }
10959: else if( line[0] == (char)0xFE && line[1] == (char)0xFF)
10960: {
10961: noffset=noffset+2;
10962: printf("# File is an UTF16BE BOM file\n");
10963: }
10964: else if( line[0] == 0 && line[1] == 0)
10965: {
10966: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10967: noffset=noffset+4;
10968: printf("# File is an UTF16BE BOM file\n");
10969: }
10970: } else{
10971: ;/*printf(" Not a BOM file\n");*/
10972: }
10973:
1.197 brouard 10974: /* If line starts with a # it is a comment */
1.277 brouard 10975: if (line[noffset] == '#') {
1.197 brouard 10976: numlinepar++;
10977: fputs(line,stdout);
10978: fputs(line,ficparo);
1.278 brouard 10979: fputs(line,ficres);
1.197 brouard 10980: fputs(line,ficlog);
10981: continue;
10982: }else
10983: break;
10984: }
10985: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
10986: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
10987: if (num_filled != 5) {
10988: printf("Should be 5 parameters\n");
1.283 brouard 10989: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 10990: }
1.126 brouard 10991: numlinepar++;
1.197 brouard 10992: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 10993: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
10994: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
10995: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 10996: }
10997: /* Second parameter line */
10998: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 10999: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11000: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11001: if (line[0] == '#') {
11002: numlinepar++;
1.283 brouard 11003: printf("%s",line);
11004: fprintf(ficres,"%s",line);
11005: fprintf(ficparo,"%s",line);
11006: fprintf(ficlog,"%s",line);
1.197 brouard 11007: continue;
11008: }else
11009: break;
11010: }
1.223 brouard 11011: 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", \
11012: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11013: if (num_filled != 11) {
11014: 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 11015: printf("but line=%s\n",line);
1.283 brouard 11016: 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");
11017: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11018: }
1.223 brouard 11019: 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 11020: 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);
11021: 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, mle, weightopt);
11022: 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 11023: }
1.203 brouard 11024: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11025: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11026: /* Third parameter line */
11027: while(fgets(line, MAXLINE, ficpar)) {
11028: /* If line starts with a # it is a comment */
11029: if (line[0] == '#') {
11030: numlinepar++;
1.283 brouard 11031: printf("%s",line);
11032: fprintf(ficres,"%s",line);
11033: fprintf(ficparo,"%s",line);
11034: fprintf(ficlog,"%s",line);
1.197 brouard 11035: continue;
11036: }else
11037: break;
11038: }
1.201 brouard 11039: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11040: if (num_filled != 1){
11041: printf("ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
11042: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
1.197 brouard 11043: model[0]='\0';
11044: goto end;
11045: }
11046: else{
11047: if (model[0]=='+'){
11048: for(i=1; i<=strlen(model);i++)
11049: modeltemp[i-1]=model[i];
1.201 brouard 11050: strcpy(model,modeltemp);
1.197 brouard 11051: }
11052: }
1.199 brouard 11053: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11054: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11055: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11056: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11057: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11058: }
11059: /* 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); */
11060: /* numlinepar=numlinepar+3; /\* In general *\/ */
11061: /* 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 11062: /* 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); */
11063: /* 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 11064: fflush(ficlog);
1.190 brouard 11065: /* if(model[0]=='#'|| model[0]== '\0'){ */
11066: if(model[0]=='#'){
1.279 brouard 11067: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11068: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11069: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11070: if(mle != -1){
1.279 brouard 11071: 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 11072: exit(1);
11073: }
11074: }
1.126 brouard 11075: while((c=getc(ficpar))=='#' && c!= EOF){
11076: ungetc(c,ficpar);
11077: fgets(line, MAXLINE, ficpar);
11078: numlinepar++;
1.195 brouard 11079: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11080: z[0]=line[1];
11081: }
11082: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11083: fputs(line, stdout);
11084: //puts(line);
1.126 brouard 11085: fputs(line,ficparo);
11086: fputs(line,ficlog);
11087: }
11088: ungetc(c,ficpar);
11089:
11090:
1.145 brouard 11091: covar=matrix(0,NCOVMAX,1,n); /**< used in readdata */
1.268 brouard 11092: if(nqv>=1)coqvar=matrix(1,nqv,1,n); /**< Fixed quantitative covariate */
11093: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,1,n); /**< Time varying quantitative covariate */
11094: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,1,n); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11095: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11096: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11097: v1+v2*age+v2*v3 makes cptcovn = 3
11098: */
11099: if (strlen(model)>1)
1.187 brouard 11100: 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 11101: else
1.187 brouard 11102: ncovmodel=2; /* Constant and age */
1.133 brouard 11103: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11104: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11105: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11106: 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);
11107: 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);
11108: fflush(stdout);
11109: fclose (ficlog);
11110: goto end;
11111: }
1.126 brouard 11112: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11113: delti=delti3[1][1];
11114: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11115: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11116: /* We could also provide initial parameters values giving by simple logistic regression
11117: * only one way, that is without matrix product. We will have nlstate maximizations */
11118: /* for(i=1;i<nlstate;i++){ */
11119: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11120: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11121: /* } */
1.126 brouard 11122: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11123: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11124: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11125: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11126: fclose (ficparo);
11127: fclose (ficlog);
11128: goto end;
11129: exit(0);
1.220 brouard 11130: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11131: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11132: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11133: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11134: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11135: matcov=matrix(1,npar,1,npar);
1.203 brouard 11136: hess=matrix(1,npar,1,npar);
1.220 brouard 11137: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11138: /* Read guessed parameters */
1.126 brouard 11139: /* Reads comments: lines beginning with '#' */
11140: while((c=getc(ficpar))=='#' && c!= EOF){
11141: ungetc(c,ficpar);
11142: fgets(line, MAXLINE, ficpar);
11143: numlinepar++;
1.141 brouard 11144: fputs(line,stdout);
1.126 brouard 11145: fputs(line,ficparo);
11146: fputs(line,ficlog);
11147: }
11148: ungetc(c,ficpar);
11149:
11150: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11151: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11152: for(i=1; i <=nlstate; i++){
1.234 brouard 11153: j=0;
1.126 brouard 11154: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11155: if(jj==i) continue;
11156: j++;
11157: fscanf(ficpar,"%1d%1d",&i1,&j1);
11158: if ((i1 != i) || (j1 != jj)){
11159: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11160: It might be a problem of design; if ncovcol and the model are correct\n \
11161: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11162: exit(1);
11163: }
11164: fprintf(ficparo,"%1d%1d",i1,j1);
11165: if(mle==1)
11166: printf("%1d%1d",i,jj);
11167: fprintf(ficlog,"%1d%1d",i,jj);
11168: for(k=1; k<=ncovmodel;k++){
11169: fscanf(ficpar," %lf",¶m[i][j][k]);
11170: if(mle==1){
11171: printf(" %lf",param[i][j][k]);
11172: fprintf(ficlog," %lf",param[i][j][k]);
11173: }
11174: else
11175: fprintf(ficlog," %lf",param[i][j][k]);
11176: fprintf(ficparo," %lf",param[i][j][k]);
11177: }
11178: fscanf(ficpar,"\n");
11179: numlinepar++;
11180: if(mle==1)
11181: printf("\n");
11182: fprintf(ficlog,"\n");
11183: fprintf(ficparo,"\n");
1.126 brouard 11184: }
11185: }
11186: fflush(ficlog);
1.234 brouard 11187:
1.251 brouard 11188: /* Reads parameters values */
1.126 brouard 11189: p=param[1][1];
1.251 brouard 11190: pstart=paramstart[1][1];
1.126 brouard 11191:
11192: /* Reads comments: lines beginning with '#' */
11193: while((c=getc(ficpar))=='#' && c!= EOF){
11194: ungetc(c,ficpar);
11195: fgets(line, MAXLINE, ficpar);
11196: numlinepar++;
1.141 brouard 11197: fputs(line,stdout);
1.126 brouard 11198: fputs(line,ficparo);
11199: fputs(line,ficlog);
11200: }
11201: ungetc(c,ficpar);
11202:
11203: for(i=1; i <=nlstate; i++){
11204: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11205: fscanf(ficpar,"%1d%1d",&i1,&j1);
11206: if ( (i1-i) * (j1-j) != 0){
11207: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11208: exit(1);
11209: }
11210: printf("%1d%1d",i,j);
11211: fprintf(ficparo,"%1d%1d",i1,j1);
11212: fprintf(ficlog,"%1d%1d",i1,j1);
11213: for(k=1; k<=ncovmodel;k++){
11214: fscanf(ficpar,"%le",&delti3[i][j][k]);
11215: printf(" %le",delti3[i][j][k]);
11216: fprintf(ficparo," %le",delti3[i][j][k]);
11217: fprintf(ficlog," %le",delti3[i][j][k]);
11218: }
11219: fscanf(ficpar,"\n");
11220: numlinepar++;
11221: printf("\n");
11222: fprintf(ficparo,"\n");
11223: fprintf(ficlog,"\n");
1.126 brouard 11224: }
11225: }
11226: fflush(ficlog);
1.234 brouard 11227:
1.145 brouard 11228: /* Reads covariance matrix */
1.126 brouard 11229: delti=delti3[1][1];
1.220 brouard 11230:
11231:
1.126 brouard 11232: /* 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 11233:
1.126 brouard 11234: /* Reads comments: lines beginning with '#' */
11235: while((c=getc(ficpar))=='#' && c!= EOF){
11236: ungetc(c,ficpar);
11237: fgets(line, MAXLINE, ficpar);
11238: numlinepar++;
1.141 brouard 11239: fputs(line,stdout);
1.126 brouard 11240: fputs(line,ficparo);
11241: fputs(line,ficlog);
11242: }
11243: ungetc(c,ficpar);
1.220 brouard 11244:
1.126 brouard 11245: matcov=matrix(1,npar,1,npar);
1.203 brouard 11246: hess=matrix(1,npar,1,npar);
1.131 brouard 11247: for(i=1; i <=npar; i++)
11248: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11249:
1.194 brouard 11250: /* Scans npar lines */
1.126 brouard 11251: for(i=1; i <=npar; i++){
1.226 brouard 11252: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11253: if(count != 3){
1.226 brouard 11254: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11255: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11256: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11257: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11258: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11259: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11260: exit(1);
1.220 brouard 11261: }else{
1.226 brouard 11262: if(mle==1)
11263: printf("%1d%1d%d",i1,j1,jk);
11264: }
11265: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11266: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11267: for(j=1; j <=i; j++){
1.226 brouard 11268: fscanf(ficpar," %le",&matcov[i][j]);
11269: if(mle==1){
11270: printf(" %.5le",matcov[i][j]);
11271: }
11272: fprintf(ficlog," %.5le",matcov[i][j]);
11273: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11274: }
11275: fscanf(ficpar,"\n");
11276: numlinepar++;
11277: if(mle==1)
1.220 brouard 11278: printf("\n");
1.126 brouard 11279: fprintf(ficlog,"\n");
11280: fprintf(ficparo,"\n");
11281: }
1.194 brouard 11282: /* End of read covariance matrix npar lines */
1.126 brouard 11283: for(i=1; i <=npar; i++)
11284: for(j=i+1;j<=npar;j++)
1.226 brouard 11285: matcov[i][j]=matcov[j][i];
1.126 brouard 11286:
11287: if(mle==1)
11288: printf("\n");
11289: fprintf(ficlog,"\n");
11290:
11291: fflush(ficlog);
11292:
11293: } /* End of mle != -3 */
1.218 brouard 11294:
1.186 brouard 11295: /* Main data
11296: */
1.126 brouard 11297: n= lastobs;
11298: num=lvector(1,n);
11299: moisnais=vector(1,n);
11300: annais=vector(1,n);
11301: moisdc=vector(1,n);
11302: andc=vector(1,n);
1.220 brouard 11303: weight=vector(1,n);
1.126 brouard 11304: agedc=vector(1,n);
11305: cod=ivector(1,n);
1.220 brouard 11306: for(i=1;i<=n;i++){
1.234 brouard 11307: num[i]=0;
11308: moisnais[i]=0;
11309: annais[i]=0;
11310: moisdc[i]=0;
11311: andc[i]=0;
11312: agedc[i]=0;
11313: cod[i]=0;
11314: weight[i]=1.0; /* Equal weights, 1 by default */
11315: }
1.126 brouard 11316: mint=matrix(1,maxwav,1,n);
11317: anint=matrix(1,maxwav,1,n);
1.131 brouard 11318: s=imatrix(1,maxwav+1,1,n); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11319: tab=ivector(1,NCOVMAX);
1.144 brouard 11320: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11321: 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 11322:
1.136 brouard 11323: /* Reads data from file datafile */
11324: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11325: goto end;
11326:
11327: /* Calculation of the number of parameters from char model */
1.234 brouard 11328: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11329: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11330: k=3 V4 Tvar[k=3]= 4 (from V4)
11331: k=2 V1 Tvar[k=2]= 1 (from V1)
11332: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11333: */
11334:
11335: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11336: TvarsDind=ivector(1,NCOVMAX); /* */
11337: TvarsD=ivector(1,NCOVMAX); /* */
11338: TvarsQind=ivector(1,NCOVMAX); /* */
11339: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11340: TvarF=ivector(1,NCOVMAX); /* */
11341: TvarFind=ivector(1,NCOVMAX); /* */
11342: TvarV=ivector(1,NCOVMAX); /* */
11343: TvarVind=ivector(1,NCOVMAX); /* */
11344: TvarA=ivector(1,NCOVMAX); /* */
11345: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11346: TvarFD=ivector(1,NCOVMAX); /* */
11347: TvarFDind=ivector(1,NCOVMAX); /* */
11348: TvarFQ=ivector(1,NCOVMAX); /* */
11349: TvarFQind=ivector(1,NCOVMAX); /* */
11350: TvarVD=ivector(1,NCOVMAX); /* */
11351: TvarVDind=ivector(1,NCOVMAX); /* */
11352: TvarVQ=ivector(1,NCOVMAX); /* */
11353: TvarVQind=ivector(1,NCOVMAX); /* */
11354:
1.230 brouard 11355: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11356: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11357: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11358: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11359: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11360: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11361: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11362: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11363: */
11364: /* For model-covariate k tells which data-covariate to use but
11365: because this model-covariate is a construction we invent a new column
11366: ncovcol + k1
11367: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11368: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11369: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11370: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11371: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11372: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11373: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11374: */
1.145 brouard 11375: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11376: 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 11377: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11378: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11379: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11380: 4 covariates (3 plus signs)
11381: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11382: */
1.230 brouard 11383: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11384: * individual dummy, fixed or varying:
11385: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11386: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11387: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11388: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11389: * Tmodelind[1]@9={9,0,3,2,}*/
11390: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11391: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11392: * individual quantitative, fixed or varying:
11393: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11394: * 3, 1, 0, 0, 0, 0, 0, 0},
11395: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11396: /* Main decodemodel */
11397:
1.187 brouard 11398:
1.223 brouard 11399: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11400: goto end;
11401:
1.137 brouard 11402: if((double)(lastobs-imx)/(double)imx > 1.10){
11403: nbwarn++;
11404: 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);
11405: 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);
11406: }
1.136 brouard 11407: /* if(mle==1){*/
1.137 brouard 11408: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11409: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11410: }
11411:
11412: /*-calculation of age at interview from date of interview and age at death -*/
11413: agev=matrix(1,maxwav,1,imx);
11414:
11415: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11416: goto end;
11417:
1.126 brouard 11418:
1.136 brouard 11419: agegomp=(int)agemin;
11420: free_vector(moisnais,1,n);
11421: free_vector(annais,1,n);
1.126 brouard 11422: /* free_matrix(mint,1,maxwav,1,n);
11423: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11424: /* free_vector(moisdc,1,n); */
11425: /* free_vector(andc,1,n); */
1.145 brouard 11426: /* */
11427:
1.126 brouard 11428: wav=ivector(1,imx);
1.214 brouard 11429: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11430: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11431: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11432: 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.*/
11433: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11434: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11435:
11436: /* Concatenates waves */
1.214 brouard 11437: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11438: Death is a valid wave (if date is known).
11439: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11440: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11441: and mw[mi+1][i]. dh depends on stepm.
11442: */
11443:
1.126 brouard 11444: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11445: /* Concatenates waves */
1.145 brouard 11446:
1.215 brouard 11447: free_vector(moisdc,1,n);
11448: free_vector(andc,1,n);
11449:
1.126 brouard 11450: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11451: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11452: ncodemax[1]=1;
1.145 brouard 11453: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11454: cptcoveff=0;
1.220 brouard 11455: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11456: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11457: }
11458:
11459: ncovcombmax=pow(2,cptcoveff);
11460: invalidvarcomb=ivector(1, ncovcombmax);
11461: for(i=1;i<ncovcombmax;i++)
11462: invalidvarcomb[i]=0;
11463:
1.211 brouard 11464: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11465: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11466: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11467:
1.200 brouard 11468: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11469: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11470: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11471: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11472: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11473: * (currently 0 or 1) in the data.
11474: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11475: * corresponding modality (h,j).
11476: */
11477:
1.145 brouard 11478: h=0;
11479: /*if (cptcovn > 0) */
1.126 brouard 11480: m=pow(2,cptcoveff);
11481:
1.144 brouard 11482: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11483: * For k=4 covariates, h goes from 1 to m=2**k
11484: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11485: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11486: * h\k 1 2 3 4
1.143 brouard 11487: *______________________________
11488: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11489: * 2 2 1 1 1
11490: * 3 i=2 1 2 1 1
11491: * 4 2 2 1 1
11492: * 5 i=3 1 i=2 1 2 1
11493: * 6 2 1 2 1
11494: * 7 i=4 1 2 2 1
11495: * 8 2 2 2 1
1.197 brouard 11496: * 9 i=5 1 i=3 1 i=2 1 2
11497: * 10 2 1 1 2
11498: * 11 i=6 1 2 1 2
11499: * 12 2 2 1 2
11500: * 13 i=7 1 i=4 1 2 2
11501: * 14 2 1 2 2
11502: * 15 i=8 1 2 2 2
11503: * 16 2 2 2 2
1.143 brouard 11504: */
1.212 brouard 11505: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11506: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11507: * and the value of each covariate?
11508: * V1=1, V2=1, V3=2, V4=1 ?
11509: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11510: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11511: * In order to get the real value in the data, we use nbcode
11512: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11513: * We are keeping this crazy system in order to be able (in the future?)
11514: * to have more than 2 values (0 or 1) for a covariate.
11515: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11516: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11517: * bbbbbbbb
11518: * 76543210
11519: * h-1 00000101 (6-1=5)
1.219 brouard 11520: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11521: * &
11522: * 1 00000001 (1)
1.219 brouard 11523: * 00000000 = 1 & ((h-1) >> (k-1))
11524: * +1= 00000001 =1
1.211 brouard 11525: *
11526: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11527: * h' 1101 =2^3+2^2+0x2^1+2^0
11528: * >>k' 11
11529: * & 00000001
11530: * = 00000001
11531: * +1 = 00000010=2 = codtabm(14,3)
11532: * Reverse h=6 and m=16?
11533: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11534: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11535: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11536: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11537: * V3=decodtabm(14,3,2**4)=2
11538: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11539: *(h-1) >> (j-1) 0011 =13 >> 2
11540: * &1 000000001
11541: * = 000000001
11542: * +1= 000000010 =2
11543: * 2211
11544: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11545: * V3=2
1.220 brouard 11546: * codtabm and decodtabm are identical
1.211 brouard 11547: */
11548:
1.145 brouard 11549:
11550: free_ivector(Ndum,-1,NCOVMAX);
11551:
11552:
1.126 brouard 11553:
1.186 brouard 11554: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11555: strcpy(optionfilegnuplot,optionfilefiname);
11556: if(mle==-3)
1.201 brouard 11557: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11558: strcat(optionfilegnuplot,".gp");
11559:
11560: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11561: printf("Problem with file %s",optionfilegnuplot);
11562: }
11563: else{
1.204 brouard 11564: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11565: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11566: //fprintf(ficgp,"set missing 'NaNq'\n");
11567: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11568: }
11569: /* fclose(ficgp);*/
1.186 brouard 11570:
11571:
11572: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11573:
11574: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11575: if(mle==-3)
1.201 brouard 11576: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11577: strcat(optionfilehtm,".htm");
11578: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11579: printf("Problem with %s \n",optionfilehtm);
11580: exit(0);
1.126 brouard 11581: }
11582:
11583: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11584: strcat(optionfilehtmcov,"-cov.htm");
11585: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11586: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11587: }
11588: else{
11589: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11590: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11591: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11592: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11593: }
11594:
1.213 brouard 11595: 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 11596: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11597: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11598: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11599: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11600: \n\
11601: <hr size=\"2\" color=\"#EC5E5E\">\
11602: <ul><li><h4>Parameter files</h4>\n\
11603: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11604: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11605: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11606: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11607: - Date and time at start: %s</ul>\n",\
11608: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11609: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11610: fileres,fileres,\
11611: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11612: fflush(fichtm);
11613:
11614: strcpy(pathr,path);
11615: strcat(pathr,optionfilefiname);
1.184 brouard 11616: #ifdef WIN32
11617: _chdir(optionfilefiname); /* Move to directory named optionfile */
11618: #else
1.126 brouard 11619: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11620: #endif
11621:
1.126 brouard 11622:
1.220 brouard 11623: /* Calculates basic frequencies. Computes observed prevalence at single age
11624: and for any valid combination of covariates
1.126 brouard 11625: and prints on file fileres'p'. */
1.251 brouard 11626: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11627: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11628:
11629: fprintf(fichtm,"\n");
1.274 brouard 11630: fprintf(fichtm,"<h4>Parameter line 2</h4><ul><li>Tolerance for the convergence of the likelihood: ftol=%f \n<li>Interval for the elementary matrix (in month): stepm=%d",\
11631: ftol, stepm);
11632: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
11633: ncurrv=1;
11634: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
11635: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
11636: ncurrv=i;
11637: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
11638: fprintf(fichtm,"\n<li> Number of time varying (wave varying) covariates: ntv=%d ", ntv);
11639: ncurrv=i;
11640: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
11641: fprintf(fichtm,"\n<li>Number of quantitative time varying covariates: nqtv=%d ", nqtv);
11642: ncurrv=i;
11643: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
11644: 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", \
11645: nlstate, ndeath, maxwav, mle, weightopt);
11646:
11647: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
11648: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
11649:
11650:
11651: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Total number of observations=%d <br>\n\
1.126 brouard 11652: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11653: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 11654: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 11655: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 11656: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11657: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11658: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11659: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11660:
1.126 brouard 11661: /* For Powell, parameters are in a vector p[] starting at p[1]
11662: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11663: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11664:
11665: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11666: /* For mortality only */
1.126 brouard 11667: if (mle==-3){
1.136 brouard 11668: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11669: for(i=1;i<=NDIM;i++)
11670: for(j=1;j<=NDIM;j++)
11671: ximort[i][j]=0.;
1.186 brouard 11672: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.126 brouard 11673: cens=ivector(1,n);
11674: ageexmed=vector(1,n);
11675: agecens=vector(1,n);
11676: dcwave=ivector(1,n);
1.223 brouard 11677:
1.126 brouard 11678: for (i=1; i<=imx; i++){
11679: dcwave[i]=-1;
11680: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11681: if (s[m][i]>nlstate) {
11682: dcwave[i]=m;
11683: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11684: break;
11685: }
1.126 brouard 11686: }
1.226 brouard 11687:
1.126 brouard 11688: for (i=1; i<=imx; i++) {
11689: if (wav[i]>0){
1.226 brouard 11690: ageexmed[i]=agev[mw[1][i]][i];
11691: j=wav[i];
11692: agecens[i]=1.;
11693:
11694: if (ageexmed[i]> 1 && wav[i] > 0){
11695: agecens[i]=agev[mw[j][i]][i];
11696: cens[i]= 1;
11697: }else if (ageexmed[i]< 1)
11698: cens[i]= -1;
11699: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11700: cens[i]=0 ;
1.126 brouard 11701: }
11702: else cens[i]=-1;
11703: }
11704:
11705: for (i=1;i<=NDIM;i++) {
11706: for (j=1;j<=NDIM;j++)
1.226 brouard 11707: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 11708: }
11709:
1.145 brouard 11710: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 11711: /*printf("%lf %lf", p[1], p[2]);*/
11712:
11713:
1.136 brouard 11714: #ifdef GSL
11715: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 11716: #else
1.126 brouard 11717: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 11718: #endif
1.201 brouard 11719: strcpy(filerespow,"POW-MORT_");
11720: strcat(filerespow,fileresu);
1.126 brouard 11721: if((ficrespow=fopen(filerespow,"w"))==NULL) {
11722: printf("Problem with resultfile: %s\n", filerespow);
11723: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
11724: }
1.136 brouard 11725: #ifdef GSL
11726: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 11727: #else
1.126 brouard 11728: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 11729: #endif
1.126 brouard 11730: /* for (i=1;i<=nlstate;i++)
11731: for(j=1;j<=nlstate+ndeath;j++)
11732: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
11733: */
11734: fprintf(ficrespow,"\n");
1.136 brouard 11735: #ifdef GSL
11736: /* gsl starts here */
11737: T = gsl_multimin_fminimizer_nmsimplex;
11738: gsl_multimin_fminimizer *sfm = NULL;
11739: gsl_vector *ss, *x;
11740: gsl_multimin_function minex_func;
11741:
11742: /* Initial vertex size vector */
11743: ss = gsl_vector_alloc (NDIM);
11744:
11745: if (ss == NULL){
11746: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
11747: }
11748: /* Set all step sizes to 1 */
11749: gsl_vector_set_all (ss, 0.001);
11750:
11751: /* Starting point */
1.126 brouard 11752:
1.136 brouard 11753: x = gsl_vector_alloc (NDIM);
11754:
11755: if (x == NULL){
11756: gsl_vector_free(ss);
11757: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
11758: }
11759:
11760: /* Initialize method and iterate */
11761: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 11762: /* gsl_vector_set(x, 0, 0.0268); */
11763: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 11764: gsl_vector_set(x, 0, p[1]);
11765: gsl_vector_set(x, 1, p[2]);
11766:
11767: minex_func.f = &gompertz_f;
11768: minex_func.n = NDIM;
11769: minex_func.params = (void *)&p; /* ??? */
11770:
11771: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
11772: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
11773:
11774: printf("Iterations beginning .....\n\n");
11775: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
11776:
11777: iteri=0;
11778: while (rval == GSL_CONTINUE){
11779: iteri++;
11780: status = gsl_multimin_fminimizer_iterate(sfm);
11781:
11782: if (status) printf("error: %s\n", gsl_strerror (status));
11783: fflush(0);
11784:
11785: if (status)
11786: break;
11787:
11788: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
11789: ssval = gsl_multimin_fminimizer_size (sfm);
11790:
11791: if (rval == GSL_SUCCESS)
11792: printf ("converged to a local maximum at\n");
11793:
11794: printf("%5d ", iteri);
11795: for (it = 0; it < NDIM; it++){
11796: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
11797: }
11798: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
11799: }
11800:
11801: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
11802:
11803: gsl_vector_free(x); /* initial values */
11804: gsl_vector_free(ss); /* inital step size */
11805: for (it=0; it<NDIM; it++){
11806: p[it+1]=gsl_vector_get(sfm->x,it);
11807: fprintf(ficrespow," %.12lf", p[it]);
11808: }
11809: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
11810: #endif
11811: #ifdef POWELL
11812: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
11813: #endif
1.126 brouard 11814: fclose(ficrespow);
11815:
1.203 brouard 11816: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 11817:
11818: for(i=1; i <=NDIM; i++)
11819: for(j=i+1;j<=NDIM;j++)
1.220 brouard 11820: matcov[i][j]=matcov[j][i];
1.126 brouard 11821:
11822: printf("\nCovariance matrix\n ");
1.203 brouard 11823: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 11824: for(i=1; i <=NDIM; i++) {
11825: for(j=1;j<=NDIM;j++){
1.220 brouard 11826: printf("%f ",matcov[i][j]);
11827: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 11828: }
1.203 brouard 11829: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 11830: }
11831:
11832: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 11833: for (i=1;i<=NDIM;i++) {
1.126 brouard 11834: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 11835: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
11836: }
1.126 brouard 11837: lsurv=vector(1,AGESUP);
11838: lpop=vector(1,AGESUP);
11839: tpop=vector(1,AGESUP);
11840: lsurv[agegomp]=100000;
11841:
11842: for (k=agegomp;k<=AGESUP;k++) {
11843: agemortsup=k;
11844: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
11845: }
11846:
11847: for (k=agegomp;k<agemortsup;k++)
11848: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
11849:
11850: for (k=agegomp;k<agemortsup;k++){
11851: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
11852: sumlpop=sumlpop+lpop[k];
11853: }
11854:
11855: tpop[agegomp]=sumlpop;
11856: for (k=agegomp;k<(agemortsup-3);k++){
11857: /* tpop[k+1]=2;*/
11858: tpop[k+1]=tpop[k]-lpop[k];
11859: }
11860:
11861:
11862: printf("\nAge lx qx dx Lx Tx e(x)\n");
11863: for (k=agegomp;k<(agemortsup-2);k++)
11864: 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]);
11865:
11866:
11867: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 11868: ageminpar=50;
11869: agemaxpar=100;
1.194 brouard 11870: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
11871: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11872: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11873: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
11874: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11875: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11876: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 11877: }else{
11878: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
11879: 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 11880: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 11881: }
1.201 brouard 11882: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 11883: stepm, weightopt,\
11884: model,imx,p,matcov,agemortsup);
11885:
11886: free_vector(lsurv,1,AGESUP);
11887: free_vector(lpop,1,AGESUP);
11888: free_vector(tpop,1,AGESUP);
1.220 brouard 11889: free_matrix(ximort,1,NDIM,1,NDIM);
1.136 brouard 11890: free_ivector(cens,1,n);
11891: free_vector(agecens,1,n);
11892: free_ivector(dcwave,1,n);
1.220 brouard 11893: #ifdef GSL
1.136 brouard 11894: #endif
1.186 brouard 11895: } /* Endof if mle==-3 mortality only */
1.205 brouard 11896: /* Standard */
11897: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
11898: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11899: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 11900: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 11901: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11902: for (k=1; k<=npar;k++)
11903: printf(" %d %8.5f",k,p[k]);
11904: printf("\n");
1.205 brouard 11905: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
11906: /* mlikeli uses func not funcone */
1.247 brouard 11907: /* for(i=1;i<nlstate;i++){ */
11908: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11909: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11910: /* } */
1.205 brouard 11911: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
11912: }
11913: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
11914: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11915: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
11916: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11917: }
11918: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 11919: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11920: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11921: for (k=1; k<=npar;k++)
11922: printf(" %d %8.5f",k,p[k]);
11923: printf("\n");
11924:
11925: /*--------- results files --------------*/
1.283 brouard 11926: /* 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 11927:
11928:
11929: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11930: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11931: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11932: for(i=1,jk=1; i <=nlstate; i++){
11933: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 11934: if (k != i) {
11935: printf("%d%d ",i,k);
11936: fprintf(ficlog,"%d%d ",i,k);
11937: fprintf(ficres,"%1d%1d ",i,k);
11938: for(j=1; j <=ncovmodel; j++){
11939: printf("%12.7f ",p[jk]);
11940: fprintf(ficlog,"%12.7f ",p[jk]);
11941: fprintf(ficres,"%12.7f ",p[jk]);
11942: jk++;
11943: }
11944: printf("\n");
11945: fprintf(ficlog,"\n");
11946: fprintf(ficres,"\n");
11947: }
1.126 brouard 11948: }
11949: }
1.203 brouard 11950: if(mle != 0){
11951: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 11952: ftolhess=ftol; /* Usually correct */
1.203 brouard 11953: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
11954: 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");
11955: 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");
11956: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 11957: for(k=1; k <=(nlstate+ndeath); k++){
11958: if (k != i) {
11959: printf("%d%d ",i,k);
11960: fprintf(ficlog,"%d%d ",i,k);
11961: for(j=1; j <=ncovmodel; j++){
11962: 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]));
11963: 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]));
11964: jk++;
11965: }
11966: printf("\n");
11967: fprintf(ficlog,"\n");
11968: }
11969: }
1.193 brouard 11970: }
1.203 brouard 11971: } /* end of hesscov and Wald tests */
1.225 brouard 11972:
1.203 brouard 11973: /* */
1.126 brouard 11974: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
11975: printf("# Scales (for hessian or gradient estimation)\n");
11976: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
11977: for(i=1,jk=1; i <=nlstate; i++){
11978: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 11979: if (j!=i) {
11980: fprintf(ficres,"%1d%1d",i,j);
11981: printf("%1d%1d",i,j);
11982: fprintf(ficlog,"%1d%1d",i,j);
11983: for(k=1; k<=ncovmodel;k++){
11984: printf(" %.5e",delti[jk]);
11985: fprintf(ficlog," %.5e",delti[jk]);
11986: fprintf(ficres," %.5e",delti[jk]);
11987: jk++;
11988: }
11989: printf("\n");
11990: fprintf(ficlog,"\n");
11991: fprintf(ficres,"\n");
11992: }
1.126 brouard 11993: }
11994: }
11995:
11996: 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 11997: if(mle >= 1) /* To big for the screen */
1.126 brouard 11998: 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");
11999: 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");
12000: /* # 121 Var(a12)\n\ */
12001: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12002: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12003: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12004: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12005: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12006: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12007: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12008:
12009:
12010: /* Just to have a covariance matrix which will be more understandable
12011: even is we still don't want to manage dictionary of variables
12012: */
12013: for(itimes=1;itimes<=2;itimes++){
12014: jj=0;
12015: for(i=1; i <=nlstate; i++){
1.225 brouard 12016: for(j=1; j <=nlstate+ndeath; j++){
12017: if(j==i) continue;
12018: for(k=1; k<=ncovmodel;k++){
12019: jj++;
12020: ca[0]= k+'a'-1;ca[1]='\0';
12021: if(itimes==1){
12022: if(mle>=1)
12023: printf("#%1d%1d%d",i,j,k);
12024: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12025: fprintf(ficres,"#%1d%1d%d",i,j,k);
12026: }else{
12027: if(mle>=1)
12028: printf("%1d%1d%d",i,j,k);
12029: fprintf(ficlog,"%1d%1d%d",i,j,k);
12030: fprintf(ficres,"%1d%1d%d",i,j,k);
12031: }
12032: ll=0;
12033: for(li=1;li <=nlstate; li++){
12034: for(lj=1;lj <=nlstate+ndeath; lj++){
12035: if(lj==li) continue;
12036: for(lk=1;lk<=ncovmodel;lk++){
12037: ll++;
12038: if(ll<=jj){
12039: cb[0]= lk +'a'-1;cb[1]='\0';
12040: if(ll<jj){
12041: if(itimes==1){
12042: if(mle>=1)
12043: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12044: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12045: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12046: }else{
12047: if(mle>=1)
12048: printf(" %.5e",matcov[jj][ll]);
12049: fprintf(ficlog," %.5e",matcov[jj][ll]);
12050: fprintf(ficres," %.5e",matcov[jj][ll]);
12051: }
12052: }else{
12053: if(itimes==1){
12054: if(mle>=1)
12055: printf(" Var(%s%1d%1d)",ca,i,j);
12056: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12057: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12058: }else{
12059: if(mle>=1)
12060: printf(" %.7e",matcov[jj][ll]);
12061: fprintf(ficlog," %.7e",matcov[jj][ll]);
12062: fprintf(ficres," %.7e",matcov[jj][ll]);
12063: }
12064: }
12065: }
12066: } /* end lk */
12067: } /* end lj */
12068: } /* end li */
12069: if(mle>=1)
12070: printf("\n");
12071: fprintf(ficlog,"\n");
12072: fprintf(ficres,"\n");
12073: numlinepar++;
12074: } /* end k*/
12075: } /*end j */
1.126 brouard 12076: } /* end i */
12077: } /* end itimes */
12078:
12079: fflush(ficlog);
12080: fflush(ficres);
1.225 brouard 12081: while(fgets(line, MAXLINE, ficpar)) {
12082: /* If line starts with a # it is a comment */
12083: if (line[0] == '#') {
12084: numlinepar++;
12085: fputs(line,stdout);
12086: fputs(line,ficparo);
12087: fputs(line,ficlog);
12088: continue;
12089: }else
12090: break;
12091: }
12092:
1.209 brouard 12093: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12094: /* ungetc(c,ficpar); */
12095: /* fgets(line, MAXLINE, ficpar); */
12096: /* fputs(line,stdout); */
12097: /* fputs(line,ficparo); */
12098: /* } */
12099: /* ungetc(c,ficpar); */
1.126 brouard 12100:
12101: estepm=0;
1.209 brouard 12102: 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 12103:
12104: if (num_filled != 6) {
12105: 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);
12106: 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);
12107: goto end;
12108: }
12109: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12110: }
12111: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12112: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12113:
1.209 brouard 12114: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12115: if (estepm==0 || estepm < stepm) estepm=stepm;
12116: if (fage <= 2) {
12117: bage = ageminpar;
12118: fage = agemaxpar;
12119: }
12120:
12121: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12122: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12123: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12124:
1.186 brouard 12125: /* Other stuffs, more or less useful */
1.254 brouard 12126: while(fgets(line, MAXLINE, ficpar)) {
12127: /* If line starts with a # it is a comment */
12128: if (line[0] == '#') {
12129: numlinepar++;
12130: fputs(line,stdout);
12131: fputs(line,ficparo);
12132: fputs(line,ficlog);
12133: continue;
12134: }else
12135: break;
12136: }
12137:
12138: 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){
12139:
12140: if (num_filled != 7) {
12141: 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);
12142: 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);
12143: goto end;
12144: }
12145: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12146: 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);
12147: 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);
12148: 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 12149: }
1.254 brouard 12150:
12151: while(fgets(line, MAXLINE, ficpar)) {
12152: /* If line starts with a # it is a comment */
12153: if (line[0] == '#') {
12154: numlinepar++;
12155: fputs(line,stdout);
12156: fputs(line,ficparo);
12157: fputs(line,ficlog);
12158: continue;
12159: }else
12160: break;
1.126 brouard 12161: }
12162:
12163:
12164: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12165: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12166:
1.254 brouard 12167: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12168: if (num_filled != 1) {
12169: 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);
12170: 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);
12171: goto end;
12172: }
12173: printf("pop_based=%d\n",popbased);
12174: fprintf(ficlog,"pop_based=%d\n",popbased);
12175: fprintf(ficparo,"pop_based=%d\n",popbased);
12176: fprintf(ficres,"pop_based=%d\n",popbased);
12177: }
12178:
1.258 brouard 12179: /* Results */
12180: nresult=0;
12181: do{
12182: if(!fgets(line, MAXLINE, ficpar)){
12183: endishere=1;
12184: parameterline=14;
12185: }else if (line[0] == '#') {
12186: /* If line starts with a # it is a comment */
1.254 brouard 12187: numlinepar++;
12188: fputs(line,stdout);
12189: fputs(line,ficparo);
12190: fputs(line,ficlog);
12191: continue;
1.258 brouard 12192: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12193: parameterline=11;
12194: else if(sscanf(line,"backcast=%[^\n]\n",modeltemp))
12195: parameterline=12;
12196: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
12197: parameterline=13;
12198: else{
12199: parameterline=14;
1.254 brouard 12200: }
1.258 brouard 12201: switch (parameterline){
12202: case 11:
12203: 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){
12204: if (num_filled != 8) {
12205: 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);
12206: 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);
12207: goto end;
12208: }
12209: 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);
12210: 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);
12211: 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);
12212: 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);
12213: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12214: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12215: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
12216:
1.258 brouard 12217: }
1.254 brouard 12218: break;
1.258 brouard 12219: case 12:
12220: /*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);*/
12221: 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){
12222: if (num_filled != 8) {
1.262 brouard 12223: 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);
12224: 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 12225: goto end;
12226: }
12227: 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);
12228: 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);
12229: 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);
12230: 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);
12231: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12232: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12233: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.258 brouard 12234: }
1.230 brouard 12235: break;
1.258 brouard 12236: case 13:
12237: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
12238: if (num_filled == 0){
12239: resultline[0]='\0';
12240: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12241: 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);
12242: break;
12243: } else if (num_filled != 1){
12244: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12245: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12246: }
12247: nresult++; /* Sum of resultlines */
12248: printf("Result %d: result=%s\n",nresult, resultline);
12249: if(nresult > MAXRESULTLINES){
12250: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12251: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12252: goto end;
12253: }
12254: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
12255: fprintf(ficparo,"result: %s\n",resultline);
12256: fprintf(ficres,"result: %s\n",resultline);
12257: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 12258: break;
1.258 brouard 12259: case 14:
1.259 brouard 12260: if(ncovmodel >2 && nresult==0 ){
12261: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12262: goto end;
12263: }
1.259 brouard 12264: break;
1.258 brouard 12265: default:
12266: nresult=1;
12267: decoderesult(".",nresult ); /* No covariate */
12268: }
12269: } /* End switch parameterline */
12270: }while(endishere==0); /* End do */
1.126 brouard 12271:
1.230 brouard 12272: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12273: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12274:
12275: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12276: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12277: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12278: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12279: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12280: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12281: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12282: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12283: }else{
1.270 brouard 12284: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
12285: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, backcast, pathc,p, (int)anproj1-bage, (int)anback1-fage);
1.220 brouard 12286: }
12287: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.258 brouard 12288: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,backcast, estepm, \
1.273 brouard 12289: jprev1,mprev1,anprev1,dateprev1, dateproj1, dateback1,jprev2,mprev2,anprev2,dateprev2,dateproj2, dateback2);
1.220 brouard 12290:
1.225 brouard 12291: /*------------ free_vector -------------*/
12292: /* chdir(path); */
1.220 brouard 12293:
1.215 brouard 12294: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12295: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12296: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12297: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.126 brouard 12298: free_lvector(num,1,n);
12299: free_vector(agedc,1,n);
12300: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12301: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12302: fclose(ficparo);
12303: fclose(ficres);
1.220 brouard 12304:
12305:
1.186 brouard 12306: /* Other results (useful)*/
1.220 brouard 12307:
12308:
1.126 brouard 12309: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12310: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12311: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12312: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12313: fclose(ficrespl);
12314:
12315: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12316: /*#include "hpijx.h"*/
12317: hPijx(p, bage, fage);
1.145 brouard 12318: fclose(ficrespij);
1.227 brouard 12319:
1.220 brouard 12320: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12321: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12322: k=1;
1.126 brouard 12323: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12324:
1.269 brouard 12325: /* Prevalence for each covariate combination in probs[age][status][cov] */
12326: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12327: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12328: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12329: for(k=1;k<=ncovcombmax;k++)
12330: probs[i][j][k]=0.;
1.269 brouard 12331: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
12332: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12333: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 12334: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12335: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12336: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12337: for(k=1;k<=ncovcombmax;k++)
12338: mobaverages[i][j][k]=0.;
1.219 brouard 12339: mobaverage=mobaverages;
12340: if (mobilav!=0) {
1.235 brouard 12341: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12342: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12343: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12344: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12345: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12346: }
1.269 brouard 12347: } else if (mobilavproj !=0) {
1.235 brouard 12348: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12349: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12350: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12351: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12352: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12353: }
1.269 brouard 12354: }else{
12355: printf("Internal error moving average\n");
12356: fflush(stdout);
12357: exit(1);
1.219 brouard 12358: }
12359: }/* end if moving average */
1.227 brouard 12360:
1.126 brouard 12361: /*---------- Forecasting ------------------*/
12362: if(prevfcast==1){
12363: /* if(stepm ==1){*/
1.269 brouard 12364: prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
1.126 brouard 12365: }
1.269 brouard 12366:
12367: /* Backcasting */
1.217 brouard 12368: if(backcast==1){
1.219 brouard 12369: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12370: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12371: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12372:
12373: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12374:
12375: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 12376:
1.219 brouard 12377: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12378: fclose(ficresplb);
12379:
1.222 brouard 12380: hBijx(p, bage, fage, mobaverage);
12381: fclose(ficrespijb);
1.219 brouard 12382:
1.269 brouard 12383: prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2,
12384: mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff);
12385: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12386:
12387:
1.269 brouard 12388: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12389: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12390: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12391: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.269 brouard 12392: } /* end Backcasting */
1.268 brouard 12393:
1.186 brouard 12394:
12395: /* ------ Other prevalence ratios------------ */
1.126 brouard 12396:
1.215 brouard 12397: free_ivector(wav,1,imx);
12398: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12399: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12400: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12401:
12402:
1.127 brouard 12403: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12404:
1.201 brouard 12405: strcpy(filerese,"E_");
12406: strcat(filerese,fileresu);
1.126 brouard 12407: if((ficreseij=fopen(filerese,"w"))==NULL) {
12408: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12409: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12410: }
1.208 brouard 12411: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12412: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12413:
12414: pstamp(ficreseij);
1.219 brouard 12415:
1.235 brouard 12416: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12417: if (cptcovn < 1){i1=1;}
12418:
12419: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12420: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12421: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12422: continue;
1.219 brouard 12423: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12424: printf("\n#****** ");
1.225 brouard 12425: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12426: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12427: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12428: }
12429: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12430: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12431: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12432: }
12433: fprintf(ficreseij,"******\n");
1.235 brouard 12434: printf("******\n");
1.219 brouard 12435:
12436: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12437: oldm=oldms;savm=savms;
1.235 brouard 12438: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12439:
1.219 brouard 12440: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12441: }
12442: fclose(ficreseij);
1.208 brouard 12443: printf("done evsij\n");fflush(stdout);
12444: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 12445:
1.218 brouard 12446:
1.227 brouard 12447: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12448:
1.201 brouard 12449: strcpy(filerest,"T_");
12450: strcat(filerest,fileresu);
1.127 brouard 12451: if((ficrest=fopen(filerest,"w"))==NULL) {
12452: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12453: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12454: }
1.208 brouard 12455: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12456: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12457: strcpy(fileresstde,"STDE_");
12458: strcat(fileresstde,fileresu);
1.126 brouard 12459: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12460: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12461: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12462: }
1.227 brouard 12463: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12464: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12465:
1.201 brouard 12466: strcpy(filerescve,"CVE_");
12467: strcat(filerescve,fileresu);
1.126 brouard 12468: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12469: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12470: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12471: }
1.227 brouard 12472: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12473: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12474:
1.201 brouard 12475: strcpy(fileresv,"V_");
12476: strcat(fileresv,fileresu);
1.126 brouard 12477: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12478: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12479: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12480: }
1.227 brouard 12481: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12482: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12483:
1.235 brouard 12484: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12485: if (cptcovn < 1){i1=1;}
12486:
12487: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12488: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12489: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12490: continue;
1.242 brouard 12491: printf("\n#****** Result for:");
12492: fprintf(ficrest,"\n#****** Result for:");
12493: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12494: for(j=1;j<=cptcoveff;j++){
12495: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12496: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12497: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12498: }
1.235 brouard 12499: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12500: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12501: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12502: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12503: }
1.208 brouard 12504: fprintf(ficrest,"******\n");
1.227 brouard 12505: fprintf(ficlog,"******\n");
12506: printf("******\n");
1.208 brouard 12507:
12508: fprintf(ficresstdeij,"\n#****** ");
12509: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12510: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12511: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12512: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12513: }
1.235 brouard 12514: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12515: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12516: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12517: }
1.208 brouard 12518: fprintf(ficresstdeij,"******\n");
12519: fprintf(ficrescveij,"******\n");
12520:
12521: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12522: /* pstamp(ficresvij); */
1.225 brouard 12523: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12524: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12525: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12526: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12527: }
1.208 brouard 12528: fprintf(ficresvij,"******\n");
12529:
12530: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12531: oldm=oldms;savm=savms;
1.235 brouard 12532: printf(" cvevsij ");
12533: fprintf(ficlog, " cvevsij ");
12534: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12535: printf(" end cvevsij \n ");
12536: fprintf(ficlog, " end cvevsij \n ");
12537:
12538: /*
12539: */
12540: /* goto endfree; */
12541:
12542: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12543: pstamp(ficrest);
12544:
1.269 brouard 12545: epj=vector(1,nlstate+1);
1.208 brouard 12546: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12547: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12548: cptcod= 0; /* To be deleted */
12549: printf("varevsij vpopbased=%d \n",vpopbased);
12550: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12551: 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 12552: 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 ");
12553: if(vpopbased==1)
12554: 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);
12555: else
12556: fprintf(ficrest,"the age specific period (stable) prevalences in each health state \n");
12557: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12558: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12559: fprintf(ficrest,"\n");
12560: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
12561: printf("Computing age specific period (stable) prevalences in each health state \n");
12562: fprintf(ficlog,"Computing age specific period (stable) prevalences in each health state \n");
12563: for(age=bage; age <=fage ;age++){
1.235 brouard 12564: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12565: if (vpopbased==1) {
12566: if(mobilav ==0){
12567: for(i=1; i<=nlstate;i++)
12568: prlim[i][i]=probs[(int)age][i][k];
12569: }else{ /* mobilav */
12570: for(i=1; i<=nlstate;i++)
12571: prlim[i][i]=mobaverage[(int)age][i][k];
12572: }
12573: }
1.219 brouard 12574:
1.227 brouard 12575: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12576: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12577: /* printf(" age %4.0f ",age); */
12578: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12579: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12580: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12581: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12582: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12583: }
12584: epj[nlstate+1] +=epj[j];
12585: }
12586: /* printf(" age %4.0f \n",age); */
1.219 brouard 12587:
1.227 brouard 12588: for(i=1, vepp=0.;i <=nlstate;i++)
12589: for(j=1;j <=nlstate;j++)
12590: vepp += vareij[i][j][(int)age];
12591: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12592: for(j=1;j <=nlstate;j++){
12593: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12594: }
12595: fprintf(ficrest,"\n");
12596: }
1.208 brouard 12597: } /* End vpopbased */
1.269 brouard 12598: free_vector(epj,1,nlstate+1);
1.208 brouard 12599: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12600: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 12601: printf("done selection\n");fflush(stdout);
12602: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12603:
1.235 brouard 12604: } /* End k selection */
1.227 brouard 12605:
12606: printf("done State-specific expectancies\n");fflush(stdout);
12607: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12608:
1.269 brouard 12609: /* variance-covariance of period prevalence*/
12610: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12611:
1.227 brouard 12612:
12613: free_vector(weight,1,n);
12614: free_imatrix(Tvard,1,NCOVMAX,1,2);
12615: free_imatrix(s,1,maxwav+1,1,n);
12616: free_matrix(anint,1,maxwav,1,n);
12617: free_matrix(mint,1,maxwav,1,n);
12618: free_ivector(cod,1,n);
12619: free_ivector(tab,1,NCOVMAX);
12620: fclose(ficresstdeij);
12621: fclose(ficrescveij);
12622: fclose(ficresvij);
12623: fclose(ficrest);
12624: fclose(ficpar);
12625:
12626:
1.126 brouard 12627: /*---------- End : free ----------------*/
1.219 brouard 12628: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 12629: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
12630: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12631: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12632: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12633: } /* mle==-3 arrives here for freeing */
1.227 brouard 12634: /* endfree:*/
12635: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12636: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12637: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.268 brouard 12638: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,1,n);
12639: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,1,n);
12640: if(nqv>=1)free_matrix(coqvar,1,nqv,1,n);
1.227 brouard 12641: free_matrix(covar,0,NCOVMAX,1,n);
12642: free_matrix(matcov,1,npar,1,npar);
12643: free_matrix(hess,1,npar,1,npar);
12644: /*free_vector(delti,1,npar);*/
12645: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12646: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 12647: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 12648: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12649:
12650: free_ivector(ncodemax,1,NCOVMAX);
12651: free_ivector(ncodemaxwundef,1,NCOVMAX);
12652: free_ivector(Dummy,-1,NCOVMAX);
12653: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 12654: free_ivector(DummyV,1,NCOVMAX);
12655: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 12656: free_ivector(Typevar,-1,NCOVMAX);
12657: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 12658: free_ivector(TvarsQ,1,NCOVMAX);
12659: free_ivector(TvarsQind,1,NCOVMAX);
12660: free_ivector(TvarsD,1,NCOVMAX);
12661: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 12662: free_ivector(TvarFD,1,NCOVMAX);
12663: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 12664: free_ivector(TvarF,1,NCOVMAX);
12665: free_ivector(TvarFind,1,NCOVMAX);
12666: free_ivector(TvarV,1,NCOVMAX);
12667: free_ivector(TvarVind,1,NCOVMAX);
12668: free_ivector(TvarA,1,NCOVMAX);
12669: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 12670: free_ivector(TvarFQ,1,NCOVMAX);
12671: free_ivector(TvarFQind,1,NCOVMAX);
12672: free_ivector(TvarVD,1,NCOVMAX);
12673: free_ivector(TvarVDind,1,NCOVMAX);
12674: free_ivector(TvarVQ,1,NCOVMAX);
12675: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 12676: free_ivector(Tvarsel,1,NCOVMAX);
12677: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 12678: free_ivector(Tposprod,1,NCOVMAX);
12679: free_ivector(Tprod,1,NCOVMAX);
12680: free_ivector(Tvaraff,1,NCOVMAX);
12681: free_ivector(invalidvarcomb,1,ncovcombmax);
12682: free_ivector(Tage,1,NCOVMAX);
12683: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 12684: free_ivector(TmodelInvind,1,NCOVMAX);
12685: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 12686:
12687: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
12688: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 12689: fflush(fichtm);
12690: fflush(ficgp);
12691:
1.227 brouard 12692:
1.126 brouard 12693: if((nberr >0) || (nbwarn>0)){
1.216 brouard 12694: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
12695: 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 12696: }else{
12697: printf("End of Imach\n");
12698: fprintf(ficlog,"End of Imach\n");
12699: }
12700: printf("See log file on %s\n",filelog);
12701: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 12702: /*(void) gettimeofday(&end_time,&tzp);*/
12703: rend_time = time(NULL);
12704: end_time = *localtime(&rend_time);
12705: /* tml = *localtime(&end_time.tm_sec); */
12706: strcpy(strtend,asctime(&end_time));
1.126 brouard 12707: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
12708: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 12709: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 12710:
1.157 brouard 12711: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
12712: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
12713: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 12714: /* printf("Total time was %d uSec.\n", total_usecs);*/
12715: /* if(fileappend(fichtm,optionfilehtm)){ */
12716: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12717: fclose(fichtm);
12718: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12719: fclose(fichtmcov);
12720: fclose(ficgp);
12721: fclose(ficlog);
12722: /*------ End -----------*/
1.227 brouard 12723:
1.281 brouard 12724:
12725: /* Executes gnuplot */
1.227 brouard 12726:
12727: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 12728: #ifdef WIN32
1.227 brouard 12729: if (_chdir(pathcd) != 0)
12730: printf("Can't move to directory %s!\n",path);
12731: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 12732: #else
1.227 brouard 12733: if(chdir(pathcd) != 0)
12734: printf("Can't move to directory %s!\n", path);
12735: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 12736: #endif
1.126 brouard 12737: printf("Current directory %s!\n",pathcd);
12738: /*strcat(plotcmd,CHARSEPARATOR);*/
12739: sprintf(plotcmd,"gnuplot");
1.157 brouard 12740: #ifdef _WIN32
1.126 brouard 12741: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
12742: #endif
12743: if(!stat(plotcmd,&info)){
1.158 brouard 12744: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12745: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 12746: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 12747: }else
12748: strcpy(pplotcmd,plotcmd);
1.157 brouard 12749: #ifdef __unix
1.126 brouard 12750: strcpy(plotcmd,GNUPLOTPROGRAM);
12751: if(!stat(plotcmd,&info)){
1.158 brouard 12752: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12753: }else
12754: strcpy(pplotcmd,plotcmd);
12755: #endif
12756: }else
12757: strcpy(pplotcmd,plotcmd);
12758:
12759: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 12760: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.227 brouard 12761:
1.126 brouard 12762: if((outcmd=system(plotcmd)) != 0){
1.158 brouard 12763: printf("gnuplot command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 12764: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 12765: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.150 brouard 12766: if((outcmd=system(plotcmd)) != 0)
1.153 brouard 12767: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.126 brouard 12768: }
1.158 brouard 12769: printf(" Successful, please wait...");
1.126 brouard 12770: while (z[0] != 'q') {
12771: /* chdir(path); */
1.154 brouard 12772: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 12773: scanf("%s",z);
12774: /* if (z[0] == 'c') system("./imach"); */
12775: if (z[0] == 'e') {
1.158 brouard 12776: #ifdef __APPLE__
1.152 brouard 12777: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 12778: #elif __linux
12779: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 12780: #else
1.152 brouard 12781: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 12782: #endif
12783: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
12784: system(pplotcmd);
1.126 brouard 12785: }
12786: else if (z[0] == 'g') system(plotcmd);
12787: else if (z[0] == 'q') exit(0);
12788: }
1.227 brouard 12789: end:
1.126 brouard 12790: while (z[0] != 'q') {
1.195 brouard 12791: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 12792: scanf("%s",z);
12793: }
1.283 brouard 12794: printf("End\n");
1.282 brouard 12795: exit(0);
1.126 brouard 12796: }
FreeBSD-CVSweb <freebsd-cvsweb@FreeBSD.org>
![[BACK]](/icons/small/back.gif){kind=icon}
Return to imach.c CVS log ![[TXT]](/icons/small/text.gif){kind=icon}
![[DIR]](/icons/small/dir.gif){kind=icon}
Up to [Local Repository] / imach / src