Annotation of imach/src/imach.c, revision 1.288
1.288 ! brouard 1: /* $Id: imach.c,v 1.287 2018/05/01 17:57:25 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.288 ! brouard 4: Revision 1.287 2018/05/01 17:57:25 brouard
! 5: Summary: Bug fixed by providing frequencies only for non missing covariates
! 6:
1.287 brouard 7: Revision 1.286 2018/04/27 14:27:04 brouard
8: Summary: some minor bugs
9:
1.286 brouard 10: Revision 1.285 2018/04/21 21:02:16 brouard
11: Summary: Some bugs fixed, valgrind tested
12:
1.285 brouard 13: Revision 1.284 2018/04/20 05:22:13 brouard
14: Summary: Computing mean and stdeviation of fixed quantitative variables
15:
1.284 brouard 16: Revision 1.283 2018/04/19 14:49:16 brouard
17: Summary: Some minor bugs fixed
18:
1.283 brouard 19: Revision 1.282 2018/02/27 22:50:02 brouard
20: *** empty log message ***
21:
1.282 brouard 22: Revision 1.281 2018/02/27 19:25:23 brouard
23: Summary: Adding second argument for quitting
24:
1.281 brouard 25: Revision 1.280 2018/02/21 07:58:13 brouard
26: Summary: 0.99r15
27:
28: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
29:
1.280 brouard 30: Revision 1.279 2017/07/20 13:35:01 brouard
31: Summary: temporary working
32:
1.279 brouard 33: Revision 1.278 2017/07/19 14:09:02 brouard
34: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
35:
1.278 brouard 36: Revision 1.277 2017/07/17 08:53:49 brouard
37: Summary: BOM files can be read now
38:
1.277 brouard 39: Revision 1.276 2017/06/30 15:48:31 brouard
40: Summary: Graphs improvements
41:
1.276 brouard 42: Revision 1.275 2017/06/30 13:39:33 brouard
43: Summary: Saito's color
44:
1.275 brouard 45: Revision 1.274 2017/06/29 09:47:08 brouard
46: Summary: Version 0.99r14
47:
1.274 brouard 48: Revision 1.273 2017/06/27 11:06:02 brouard
49: Summary: More documentation on projections
50:
1.273 brouard 51: Revision 1.272 2017/06/27 10:22:40 brouard
52: Summary: Color of backprojection changed from 6 to 5(yellow)
53:
1.272 brouard 54: Revision 1.271 2017/06/27 10:17:50 brouard
55: Summary: Some bug with rint
56:
1.271 brouard 57: Revision 1.270 2017/05/24 05:45:29 brouard
58: *** empty log message ***
59:
1.270 brouard 60: Revision 1.269 2017/05/23 08:39:25 brouard
61: Summary: Code into subroutine, cleanings
62:
1.269 brouard 63: Revision 1.268 2017/05/18 20:09:32 brouard
64: Summary: backprojection and confidence intervals of backprevalence
65:
1.268 brouard 66: Revision 1.267 2017/05/13 10:25:05 brouard
67: Summary: temporary save for backprojection
68:
1.267 brouard 69: Revision 1.266 2017/05/13 07:26:12 brouard
70: Summary: Version 0.99r13 (improvements and bugs fixed)
71:
1.266 brouard 72: Revision 1.265 2017/04/26 16:22:11 brouard
73: Summary: imach 0.99r13 Some bugs fixed
74:
1.265 brouard 75: Revision 1.264 2017/04/26 06:01:29 brouard
76: Summary: Labels in graphs
77:
1.264 brouard 78: Revision 1.263 2017/04/24 15:23:15 brouard
79: Summary: to save
80:
1.263 brouard 81: Revision 1.262 2017/04/18 16:48:12 brouard
82: *** empty log message ***
83:
1.262 brouard 84: Revision 1.261 2017/04/05 10:14:09 brouard
85: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
86:
1.261 brouard 87: Revision 1.260 2017/04/04 17:46:59 brouard
88: Summary: Gnuplot indexations fixed (humm)
89:
1.260 brouard 90: Revision 1.259 2017/04/04 13:01:16 brouard
91: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
92:
1.259 brouard 93: Revision 1.258 2017/04/03 10:17:47 brouard
94: Summary: Version 0.99r12
95:
96: Some cleanings, conformed with updated documentation.
97:
1.258 brouard 98: Revision 1.257 2017/03/29 16:53:30 brouard
99: Summary: Temp
100:
1.257 brouard 101: Revision 1.256 2017/03/27 05:50:23 brouard
102: Summary: Temporary
103:
1.256 brouard 104: Revision 1.255 2017/03/08 16:02:28 brouard
105: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
106:
1.255 brouard 107: Revision 1.254 2017/03/08 07:13:00 brouard
108: Summary: Fixing data parameter line
109:
1.254 brouard 110: Revision 1.253 2016/12/15 11:59:41 brouard
111: Summary: 0.99 in progress
112:
1.253 brouard 113: Revision 1.252 2016/09/15 21:15:37 brouard
114: *** empty log message ***
115:
1.252 brouard 116: Revision 1.251 2016/09/15 15:01:13 brouard
117: Summary: not working
118:
1.251 brouard 119: Revision 1.250 2016/09/08 16:07:27 brouard
120: Summary: continue
121:
1.250 brouard 122: Revision 1.249 2016/09/07 17:14:18 brouard
123: Summary: Starting values from frequencies
124:
1.249 brouard 125: Revision 1.248 2016/09/07 14:10:18 brouard
126: *** empty log message ***
127:
1.248 brouard 128: Revision 1.247 2016/09/02 11:11:21 brouard
129: *** empty log message ***
130:
1.247 brouard 131: Revision 1.246 2016/09/02 08:49:22 brouard
132: *** empty log message ***
133:
1.246 brouard 134: Revision 1.245 2016/09/02 07:25:01 brouard
135: *** empty log message ***
136:
1.245 brouard 137: Revision 1.244 2016/09/02 07:17:34 brouard
138: *** empty log message ***
139:
1.244 brouard 140: Revision 1.243 2016/09/02 06:45:35 brouard
141: *** empty log message ***
142:
1.243 brouard 143: Revision 1.242 2016/08/30 15:01:20 brouard
144: Summary: Fixing a lots
145:
1.242 brouard 146: Revision 1.241 2016/08/29 17:17:25 brouard
147: Summary: gnuplot problem in Back projection to fix
148:
1.241 brouard 149: Revision 1.240 2016/08/29 07:53:18 brouard
150: Summary: Better
151:
1.240 brouard 152: Revision 1.239 2016/08/26 15:51:03 brouard
153: Summary: Improvement in Powell output in order to copy and paste
154:
155: Author:
156:
1.239 brouard 157: Revision 1.238 2016/08/26 14:23:35 brouard
158: Summary: Starting tests of 0.99
159:
1.238 brouard 160: Revision 1.237 2016/08/26 09:20:19 brouard
161: Summary: to valgrind
162:
1.237 brouard 163: Revision 1.236 2016/08/25 10:50:18 brouard
164: *** empty log message ***
165:
1.236 brouard 166: Revision 1.235 2016/08/25 06:59:23 brouard
167: *** empty log message ***
168:
1.235 brouard 169: Revision 1.234 2016/08/23 16:51:20 brouard
170: *** empty log message ***
171:
1.234 brouard 172: Revision 1.233 2016/08/23 07:40:50 brouard
173: Summary: not working
174:
1.233 brouard 175: Revision 1.232 2016/08/22 14:20:21 brouard
176: Summary: not working
177:
1.232 brouard 178: Revision 1.231 2016/08/22 07:17:15 brouard
179: Summary: not working
180:
1.231 brouard 181: Revision 1.230 2016/08/22 06:55:53 brouard
182: Summary: Not working
183:
1.230 brouard 184: Revision 1.229 2016/07/23 09:45:53 brouard
185: Summary: Completing for func too
186:
1.229 brouard 187: Revision 1.228 2016/07/22 17:45:30 brouard
188: Summary: Fixing some arrays, still debugging
189:
1.227 brouard 190: Revision 1.226 2016/07/12 18:42:34 brouard
191: Summary: temp
192:
1.226 brouard 193: Revision 1.225 2016/07/12 08:40:03 brouard
194: Summary: saving but not running
195:
1.225 brouard 196: Revision 1.224 2016/07/01 13:16:01 brouard
197: Summary: Fixes
198:
1.224 brouard 199: Revision 1.223 2016/02/19 09:23:35 brouard
200: Summary: temporary
201:
1.223 brouard 202: Revision 1.222 2016/02/17 08:14:50 brouard
203: Summary: Probably last 0.98 stable version 0.98r6
204:
1.222 brouard 205: Revision 1.221 2016/02/15 23:35:36 brouard
206: Summary: minor bug
207:
1.220 brouard 208: Revision 1.219 2016/02/15 00:48:12 brouard
209: *** empty log message ***
210:
1.219 brouard 211: Revision 1.218 2016/02/12 11:29:23 brouard
212: Summary: 0.99 Back projections
213:
1.218 brouard 214: Revision 1.217 2015/12/23 17:18:31 brouard
215: Summary: Experimental backcast
216:
1.217 brouard 217: Revision 1.216 2015/12/18 17:32:11 brouard
218: Summary: 0.98r4 Warning and status=-2
219:
220: Version 0.98r4 is now:
221: - displaying an error when status is -1, date of interview unknown and date of death known;
222: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
223: Older changes concerning s=-2, dating from 2005 have been supersed.
224:
1.216 brouard 225: Revision 1.215 2015/12/16 08:52:24 brouard
226: Summary: 0.98r4 working
227:
1.215 brouard 228: Revision 1.214 2015/12/16 06:57:54 brouard
229: Summary: temporary not working
230:
1.214 brouard 231: Revision 1.213 2015/12/11 18:22:17 brouard
232: Summary: 0.98r4
233:
1.213 brouard 234: Revision 1.212 2015/11/21 12:47:24 brouard
235: Summary: minor typo
236:
1.212 brouard 237: Revision 1.211 2015/11/21 12:41:11 brouard
238: Summary: 0.98r3 with some graph of projected cross-sectional
239:
240: Author: Nicolas Brouard
241:
1.211 brouard 242: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 243: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 244: Summary: Adding ftolpl parameter
245: Author: N Brouard
246:
247: We had difficulties to get smoothed confidence intervals. It was due
248: to the period prevalence which wasn't computed accurately. The inner
249: parameter ftolpl is now an outer parameter of the .imach parameter
250: file after estepm. If ftolpl is small 1.e-4 and estepm too,
251: computation are long.
252:
1.209 brouard 253: Revision 1.208 2015/11/17 14:31:57 brouard
254: Summary: temporary
255:
1.208 brouard 256: Revision 1.207 2015/10/27 17:36:57 brouard
257: *** empty log message ***
258:
1.207 brouard 259: Revision 1.206 2015/10/24 07:14:11 brouard
260: *** empty log message ***
261:
1.206 brouard 262: Revision 1.205 2015/10/23 15:50:53 brouard
263: Summary: 0.98r3 some clarification for graphs on likelihood contributions
264:
1.205 brouard 265: Revision 1.204 2015/10/01 16:20:26 brouard
266: Summary: Some new graphs of contribution to likelihood
267:
1.204 brouard 268: Revision 1.203 2015/09/30 17:45:14 brouard
269: Summary: looking at better estimation of the hessian
270:
271: Also a better criteria for convergence to the period prevalence And
272: therefore adding the number of years needed to converge. (The
273: prevalence in any alive state shold sum to one
274:
1.203 brouard 275: Revision 1.202 2015/09/22 19:45:16 brouard
276: Summary: Adding some overall graph on contribution to likelihood. Might change
277:
1.202 brouard 278: Revision 1.201 2015/09/15 17:34:58 brouard
279: Summary: 0.98r0
280:
281: - Some new graphs like suvival functions
282: - Some bugs fixed like model=1+age+V2.
283:
1.201 brouard 284: Revision 1.200 2015/09/09 16:53:55 brouard
285: Summary: Big bug thanks to Flavia
286:
287: Even model=1+age+V2. did not work anymore
288:
1.200 brouard 289: Revision 1.199 2015/09/07 14:09:23 brouard
290: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
291:
1.199 brouard 292: Revision 1.198 2015/09/03 07:14:39 brouard
293: Summary: 0.98q5 Flavia
294:
1.198 brouard 295: Revision 1.197 2015/09/01 18:24:39 brouard
296: *** empty log message ***
297:
1.197 brouard 298: Revision 1.196 2015/08/18 23:17:52 brouard
299: Summary: 0.98q5
300:
1.196 brouard 301: Revision 1.195 2015/08/18 16:28:39 brouard
302: Summary: Adding a hack for testing purpose
303:
304: After reading the title, ftol and model lines, if the comment line has
305: a q, starting with #q, the answer at the end of the run is quit. It
306: permits to run test files in batch with ctest. The former workaround was
307: $ echo q | imach foo.imach
308:
1.195 brouard 309: Revision 1.194 2015/08/18 13:32:00 brouard
310: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
311:
1.194 brouard 312: Revision 1.193 2015/08/04 07:17:42 brouard
313: Summary: 0.98q4
314:
1.193 brouard 315: Revision 1.192 2015/07/16 16:49:02 brouard
316: Summary: Fixing some outputs
317:
1.192 brouard 318: Revision 1.191 2015/07/14 10:00:33 brouard
319: Summary: Some fixes
320:
1.191 brouard 321: Revision 1.190 2015/05/05 08:51:13 brouard
322: Summary: Adding digits in output parameters (7 digits instead of 6)
323:
324: Fix 1+age+.
325:
1.190 brouard 326: Revision 1.189 2015/04/30 14:45:16 brouard
327: Summary: 0.98q2
328:
1.189 brouard 329: Revision 1.188 2015/04/30 08:27:53 brouard
330: *** empty log message ***
331:
1.188 brouard 332: Revision 1.187 2015/04/29 09:11:15 brouard
333: *** empty log message ***
334:
1.187 brouard 335: Revision 1.186 2015/04/23 12:01:52 brouard
336: Summary: V1*age is working now, version 0.98q1
337:
338: Some codes had been disabled in order to simplify and Vn*age was
339: working in the optimization phase, ie, giving correct MLE parameters,
340: but, as usual, outputs were not correct and program core dumped.
341:
1.186 brouard 342: Revision 1.185 2015/03/11 13:26:42 brouard
343: Summary: Inclusion of compile and links command line for Intel Compiler
344:
1.185 brouard 345: Revision 1.184 2015/03/11 11:52:39 brouard
346: Summary: Back from Windows 8. Intel Compiler
347:
1.184 brouard 348: Revision 1.183 2015/03/10 20:34:32 brouard
349: Summary: 0.98q0, trying with directest, mnbrak fixed
350:
351: We use directest instead of original Powell test; probably no
352: incidence on the results, but better justifications;
353: We fixed Numerical Recipes mnbrak routine which was wrong and gave
354: wrong results.
355:
1.183 brouard 356: Revision 1.182 2015/02/12 08:19:57 brouard
357: Summary: Trying to keep directest which seems simpler and more general
358: Author: Nicolas Brouard
359:
1.182 brouard 360: Revision 1.181 2015/02/11 23:22:24 brouard
361: Summary: Comments on Powell added
362:
363: Author:
364:
1.181 brouard 365: Revision 1.180 2015/02/11 17:33:45 brouard
366: Summary: Finishing move from main to function (hpijx and prevalence_limit)
367:
1.180 brouard 368: Revision 1.179 2015/01/04 09:57:06 brouard
369: Summary: back to OS/X
370:
1.179 brouard 371: Revision 1.178 2015/01/04 09:35:48 brouard
372: *** empty log message ***
373:
1.178 brouard 374: Revision 1.177 2015/01/03 18:40:56 brouard
375: Summary: Still testing ilc32 on OSX
376:
1.177 brouard 377: Revision 1.176 2015/01/03 16:45:04 brouard
378: *** empty log message ***
379:
1.176 brouard 380: Revision 1.175 2015/01/03 16:33:42 brouard
381: *** empty log message ***
382:
1.175 brouard 383: Revision 1.174 2015/01/03 16:15:49 brouard
384: Summary: Still in cross-compilation
385:
1.174 brouard 386: Revision 1.173 2015/01/03 12:06:26 brouard
387: Summary: trying to detect cross-compilation
388:
1.173 brouard 389: Revision 1.172 2014/12/27 12:07:47 brouard
390: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
391:
1.172 brouard 392: Revision 1.171 2014/12/23 13:26:59 brouard
393: Summary: Back from Visual C
394:
395: Still problem with utsname.h on Windows
396:
1.171 brouard 397: Revision 1.170 2014/12/23 11:17:12 brouard
398: Summary: Cleaning some \%% back to %%
399:
400: The escape was mandatory for a specific compiler (which one?), but too many warnings.
401:
1.170 brouard 402: Revision 1.169 2014/12/22 23:08:31 brouard
403: Summary: 0.98p
404:
405: Outputs some informations on compiler used, OS etc. Testing on different platforms.
406:
1.169 brouard 407: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 408: Summary: update
1.169 brouard 409:
1.168 brouard 410: Revision 1.167 2014/12/22 13:50:56 brouard
411: Summary: Testing uname and compiler version and if compiled 32 or 64
412:
413: Testing on Linux 64
414:
1.167 brouard 415: Revision 1.166 2014/12/22 11:40:47 brouard
416: *** empty log message ***
417:
1.166 brouard 418: Revision 1.165 2014/12/16 11:20:36 brouard
419: Summary: After compiling on Visual C
420:
421: * imach.c (Module): Merging 1.61 to 1.162
422:
1.165 brouard 423: Revision 1.164 2014/12/16 10:52:11 brouard
424: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
425:
426: * imach.c (Module): Merging 1.61 to 1.162
427:
1.164 brouard 428: Revision 1.163 2014/12/16 10:30:11 brouard
429: * imach.c (Module): Merging 1.61 to 1.162
430:
1.163 brouard 431: Revision 1.162 2014/09/25 11:43:39 brouard
432: Summary: temporary backup 0.99!
433:
1.162 brouard 434: Revision 1.1 2014/09/16 11:06:58 brouard
435: Summary: With some code (wrong) for nlopt
436:
437: Author:
438:
439: Revision 1.161 2014/09/15 20:41:41 brouard
440: Summary: Problem with macro SQR on Intel compiler
441:
1.161 brouard 442: Revision 1.160 2014/09/02 09:24:05 brouard
443: *** empty log message ***
444:
1.160 brouard 445: Revision 1.159 2014/09/01 10:34:10 brouard
446: Summary: WIN32
447: Author: Brouard
448:
1.159 brouard 449: Revision 1.158 2014/08/27 17:11:51 brouard
450: *** empty log message ***
451:
1.158 brouard 452: Revision 1.157 2014/08/27 16:26:55 brouard
453: Summary: Preparing windows Visual studio version
454: Author: Brouard
455:
456: In order to compile on Visual studio, time.h is now correct and time_t
457: and tm struct should be used. difftime should be used but sometimes I
458: just make the differences in raw time format (time(&now).
459: Trying to suppress #ifdef LINUX
460: Add xdg-open for __linux in order to open default browser.
461:
1.157 brouard 462: Revision 1.156 2014/08/25 20:10:10 brouard
463: *** empty log message ***
464:
1.156 brouard 465: Revision 1.155 2014/08/25 18:32:34 brouard
466: Summary: New compile, minor changes
467: Author: Brouard
468:
1.155 brouard 469: Revision 1.154 2014/06/20 17:32:08 brouard
470: Summary: Outputs now all graphs of convergence to period prevalence
471:
1.154 brouard 472: Revision 1.153 2014/06/20 16:45:46 brouard
473: Summary: If 3 live state, convergence to period prevalence on same graph
474: Author: Brouard
475:
1.153 brouard 476: Revision 1.152 2014/06/18 17:54:09 brouard
477: Summary: open browser, use gnuplot on same dir than imach if not found in the path
478:
1.152 brouard 479: Revision 1.151 2014/06/18 16:43:30 brouard
480: *** empty log message ***
481:
1.151 brouard 482: Revision 1.150 2014/06/18 16:42:35 brouard
483: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
484: Author: brouard
485:
1.150 brouard 486: Revision 1.149 2014/06/18 15:51:14 brouard
487: Summary: Some fixes in parameter files errors
488: Author: Nicolas Brouard
489:
1.149 brouard 490: Revision 1.148 2014/06/17 17:38:48 brouard
491: Summary: Nothing new
492: Author: Brouard
493:
494: Just a new packaging for OS/X version 0.98nS
495:
1.148 brouard 496: Revision 1.147 2014/06/16 10:33:11 brouard
497: *** empty log message ***
498:
1.147 brouard 499: Revision 1.146 2014/06/16 10:20:28 brouard
500: Summary: Merge
501: Author: Brouard
502:
503: Merge, before building revised version.
504:
1.146 brouard 505: Revision 1.145 2014/06/10 21:23:15 brouard
506: Summary: Debugging with valgrind
507: Author: Nicolas Brouard
508:
509: Lot of changes in order to output the results with some covariates
510: After the Edimburgh REVES conference 2014, it seems mandatory to
511: improve the code.
512: No more memory valgrind error but a lot has to be done in order to
513: continue the work of splitting the code into subroutines.
514: Also, decodemodel has been improved. Tricode is still not
515: optimal. nbcode should be improved. Documentation has been added in
516: the source code.
517:
1.144 brouard 518: Revision 1.143 2014/01/26 09:45:38 brouard
519: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
520:
521: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
522: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
523:
1.143 brouard 524: Revision 1.142 2014/01/26 03:57:36 brouard
525: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
526:
527: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
528:
1.142 brouard 529: Revision 1.141 2014/01/26 02:42:01 brouard
530: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
531:
1.141 brouard 532: Revision 1.140 2011/09/02 10:37:54 brouard
533: Summary: times.h is ok with mingw32 now.
534:
1.140 brouard 535: Revision 1.139 2010/06/14 07:50:17 brouard
536: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
537: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
538:
1.139 brouard 539: Revision 1.138 2010/04/30 18:19:40 brouard
540: *** empty log message ***
541:
1.138 brouard 542: Revision 1.137 2010/04/29 18:11:38 brouard
543: (Module): Checking covariates for more complex models
544: than V1+V2. A lot of change to be done. Unstable.
545:
1.137 brouard 546: Revision 1.136 2010/04/26 20:30:53 brouard
547: (Module): merging some libgsl code. Fixing computation
548: of likelione (using inter/intrapolation if mle = 0) in order to
549: get same likelihood as if mle=1.
550: Some cleaning of code and comments added.
551:
1.136 brouard 552: Revision 1.135 2009/10/29 15:33:14 brouard
553: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
554:
1.135 brouard 555: Revision 1.134 2009/10/29 13:18:53 brouard
556: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
557:
1.134 brouard 558: Revision 1.133 2009/07/06 10:21:25 brouard
559: just nforces
560:
1.133 brouard 561: Revision 1.132 2009/07/06 08:22:05 brouard
562: Many tings
563:
1.132 brouard 564: Revision 1.131 2009/06/20 16:22:47 brouard
565: Some dimensions resccaled
566:
1.131 brouard 567: Revision 1.130 2009/05/26 06:44:34 brouard
568: (Module): Max Covariate is now set to 20 instead of 8. A
569: lot of cleaning with variables initialized to 0. Trying to make
570: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
571:
1.130 brouard 572: Revision 1.129 2007/08/31 13:49:27 lievre
573: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
574:
1.129 lievre 575: Revision 1.128 2006/06/30 13:02:05 brouard
576: (Module): Clarifications on computing e.j
577:
1.128 brouard 578: Revision 1.127 2006/04/28 18:11:50 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: (Module): In order to speed up (in case of numerous covariates) we
583: compute health expectancies (without variances) in a first step
584: and then all the health expectancies with variances or standard
585: deviation (needs data from the Hessian matrices) which slows the
586: computation.
587: In the future we should be able to stop the program is only health
588: expectancies and graph are needed without standard deviations.
589:
1.127 brouard 590: Revision 1.126 2006/04/28 17:23:28 brouard
591: (Module): Yes the sum of survivors was wrong since
592: imach-114 because nhstepm was no more computed in the age
593: loop. Now we define nhstepma in the age loop.
594: Version 0.98h
595:
1.126 brouard 596: Revision 1.125 2006/04/04 15:20:31 lievre
597: Errors in calculation of health expectancies. Age was not initialized.
598: Forecasting file added.
599:
600: Revision 1.124 2006/03/22 17:13:53 lievre
601: Parameters are printed with %lf instead of %f (more numbers after the comma).
602: The log-likelihood is printed in the log file
603:
604: Revision 1.123 2006/03/20 10:52:43 brouard
605: * imach.c (Module): <title> changed, corresponds to .htm file
606: name. <head> headers where missing.
607:
608: * imach.c (Module): Weights can have a decimal point as for
609: English (a comma might work with a correct LC_NUMERIC environment,
610: otherwise the weight is truncated).
611: Modification of warning when the covariates values are not 0 or
612: 1.
613: Version 0.98g
614:
615: Revision 1.122 2006/03/20 09:45:41 brouard
616: (Module): Weights can have a decimal point as for
617: English (a comma might work with a correct LC_NUMERIC environment,
618: otherwise the weight is truncated).
619: Modification of warning when the covariates values are not 0 or
620: 1.
621: Version 0.98g
622:
623: Revision 1.121 2006/03/16 17:45:01 lievre
624: * imach.c (Module): Comments concerning covariates added
625:
626: * imach.c (Module): refinements in the computation of lli if
627: status=-2 in order to have more reliable computation if stepm is
628: not 1 month. Version 0.98f
629:
630: Revision 1.120 2006/03/16 15:10:38 lievre
631: (Module): refinements in the computation of lli if
632: status=-2 in order to have more reliable computation if stepm is
633: not 1 month. Version 0.98f
634:
635: Revision 1.119 2006/03/15 17:42:26 brouard
636: (Module): Bug if status = -2, the loglikelihood was
637: computed as likelihood omitting the logarithm. Version O.98e
638:
639: Revision 1.118 2006/03/14 18:20:07 brouard
640: (Module): varevsij Comments added explaining the second
641: table of variances if popbased=1 .
642: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
643: (Module): Function pstamp added
644: (Module): Version 0.98d
645:
646: Revision 1.117 2006/03/14 17:16:22 brouard
647: (Module): varevsij Comments added explaining the second
648: table of variances if popbased=1 .
649: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
650: (Module): Function pstamp added
651: (Module): Version 0.98d
652:
653: Revision 1.116 2006/03/06 10:29:27 brouard
654: (Module): Variance-covariance wrong links and
655: varian-covariance of ej. is needed (Saito).
656:
657: Revision 1.115 2006/02/27 12:17:45 brouard
658: (Module): One freematrix added in mlikeli! 0.98c
659:
660: Revision 1.114 2006/02/26 12:57:58 brouard
661: (Module): Some improvements in processing parameter
662: filename with strsep.
663:
664: Revision 1.113 2006/02/24 14:20:24 brouard
665: (Module): Memory leaks checks with valgrind and:
666: datafile was not closed, some imatrix were not freed and on matrix
667: allocation too.
668:
669: Revision 1.112 2006/01/30 09:55:26 brouard
670: (Module): Back to gnuplot.exe instead of wgnuplot.exe
671:
672: Revision 1.111 2006/01/25 20:38:18 brouard
673: (Module): Lots of cleaning and bugs added (Gompertz)
674: (Module): Comments can be added in data file. Missing date values
675: can be a simple dot '.'.
676:
677: Revision 1.110 2006/01/25 00:51:50 brouard
678: (Module): Lots of cleaning and bugs added (Gompertz)
679:
680: Revision 1.109 2006/01/24 19:37:15 brouard
681: (Module): Comments (lines starting with a #) are allowed in data.
682:
683: Revision 1.108 2006/01/19 18:05:42 lievre
684: Gnuplot problem appeared...
685: To be fixed
686:
687: Revision 1.107 2006/01/19 16:20:37 brouard
688: Test existence of gnuplot in imach path
689:
690: Revision 1.106 2006/01/19 13:24:36 brouard
691: Some cleaning and links added in html output
692:
693: Revision 1.105 2006/01/05 20:23:19 lievre
694: *** empty log message ***
695:
696: Revision 1.104 2005/09/30 16:11:43 lievre
697: (Module): sump fixed, loop imx fixed, and simplifications.
698: (Module): If the status is missing at the last wave but we know
699: that the person is alive, then we can code his/her status as -2
700: (instead of missing=-1 in earlier versions) and his/her
701: contributions to the likelihood is 1 - Prob of dying from last
702: health status (= 1-p13= p11+p12 in the easiest case of somebody in
703: the healthy state at last known wave). Version is 0.98
704:
705: Revision 1.103 2005/09/30 15:54:49 lievre
706: (Module): sump fixed, loop imx fixed, and simplifications.
707:
708: Revision 1.102 2004/09/15 17:31:30 brouard
709: Add the possibility to read data file including tab characters.
710:
711: Revision 1.101 2004/09/15 10:38:38 brouard
712: Fix on curr_time
713:
714: Revision 1.100 2004/07/12 18:29:06 brouard
715: Add version for Mac OS X. Just define UNIX in Makefile
716:
717: Revision 1.99 2004/06/05 08:57:40 brouard
718: *** empty log message ***
719:
720: Revision 1.98 2004/05/16 15:05:56 brouard
721: New version 0.97 . First attempt to estimate force of mortality
722: directly from the data i.e. without the need of knowing the health
723: state at each age, but using a Gompertz model: log u =a + b*age .
724: This is the basic analysis of mortality and should be done before any
725: other analysis, in order to test if the mortality estimated from the
726: cross-longitudinal survey is different from the mortality estimated
727: from other sources like vital statistic data.
728:
729: The same imach parameter file can be used but the option for mle should be -3.
730:
1.133 brouard 731: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 732: former routines in order to include the new code within the former code.
733:
734: The output is very simple: only an estimate of the intercept and of
735: the slope with 95% confident intervals.
736:
737: Current limitations:
738: A) Even if you enter covariates, i.e. with the
739: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
740: B) There is no computation of Life Expectancy nor Life Table.
741:
742: Revision 1.97 2004/02/20 13:25:42 lievre
743: Version 0.96d. Population forecasting command line is (temporarily)
744: suppressed.
745:
746: Revision 1.96 2003/07/15 15:38:55 brouard
747: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
748: rewritten within the same printf. Workaround: many printfs.
749:
750: Revision 1.95 2003/07/08 07:54:34 brouard
751: * imach.c (Repository):
752: (Repository): Using imachwizard code to output a more meaningful covariance
753: matrix (cov(a12,c31) instead of numbers.
754:
755: Revision 1.94 2003/06/27 13:00:02 brouard
756: Just cleaning
757:
758: Revision 1.93 2003/06/25 16:33:55 brouard
759: (Module): On windows (cygwin) function asctime_r doesn't
760: exist so I changed back to asctime which exists.
761: (Module): Version 0.96b
762:
763: Revision 1.92 2003/06/25 16:30:45 brouard
764: (Module): On windows (cygwin) function asctime_r doesn't
765: exist so I changed back to asctime which exists.
766:
767: Revision 1.91 2003/06/25 15:30:29 brouard
768: * imach.c (Repository): Duplicated warning errors corrected.
769: (Repository): Elapsed time after each iteration is now output. It
770: helps to forecast when convergence will be reached. Elapsed time
771: is stamped in powell. We created a new html file for the graphs
772: concerning matrix of covariance. It has extension -cov.htm.
773:
774: Revision 1.90 2003/06/24 12:34:15 brouard
775: (Module): Some bugs corrected for windows. Also, when
776: mle=-1 a template is output in file "or"mypar.txt with the design
777: of the covariance matrix to be input.
778:
779: Revision 1.89 2003/06/24 12:30:52 brouard
780: (Module): Some bugs corrected for windows. Also, when
781: mle=-1 a template is output in file "or"mypar.txt with the design
782: of the covariance matrix to be input.
783:
784: Revision 1.88 2003/06/23 17:54:56 brouard
785: * 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.
786:
787: Revision 1.87 2003/06/18 12:26:01 brouard
788: Version 0.96
789:
790: Revision 1.86 2003/06/17 20:04:08 brouard
791: (Module): Change position of html and gnuplot routines and added
792: routine fileappend.
793:
794: Revision 1.85 2003/06/17 13:12:43 brouard
795: * imach.c (Repository): Check when date of death was earlier that
796: current date of interview. It may happen when the death was just
797: prior to the death. In this case, dh was negative and likelihood
798: was wrong (infinity). We still send an "Error" but patch by
799: assuming that the date of death was just one stepm after the
800: interview.
801: (Repository): Because some people have very long ID (first column)
802: we changed int to long in num[] and we added a new lvector for
803: memory allocation. But we also truncated to 8 characters (left
804: truncation)
805: (Repository): No more line truncation errors.
806:
807: Revision 1.84 2003/06/13 21:44:43 brouard
808: * imach.c (Repository): Replace "freqsummary" at a correct
809: place. It differs from routine "prevalence" which may be called
810: many times. Probs is memory consuming and must be used with
811: parcimony.
812: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
813:
814: Revision 1.83 2003/06/10 13:39:11 lievre
815: *** empty log message ***
816:
817: Revision 1.82 2003/06/05 15:57:20 brouard
818: Add log in imach.c and fullversion number is now printed.
819:
820: */
821: /*
822: Interpolated Markov Chain
823:
824: Short summary of the programme:
825:
1.227 brouard 826: This program computes Healthy Life Expectancies or State-specific
827: (if states aren't health statuses) Expectancies from
828: cross-longitudinal data. Cross-longitudinal data consist in:
829:
830: -1- a first survey ("cross") where individuals from different ages
831: are interviewed on their health status or degree of disability (in
832: the case of a health survey which is our main interest)
833:
834: -2- at least a second wave of interviews ("longitudinal") which
835: measure each change (if any) in individual health status. Health
836: expectancies are computed from the time spent in each health state
837: according to a model. More health states you consider, more time is
838: necessary to reach the Maximum Likelihood of the parameters involved
839: in the model. The simplest model is the multinomial logistic model
840: where pij is the probability to be observed in state j at the second
841: wave conditional to be observed in state i at the first
842: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
843: etc , where 'age' is age and 'sex' is a covariate. If you want to
844: have a more complex model than "constant and age", you should modify
845: the program where the markup *Covariates have to be included here
846: again* invites you to do it. More covariates you add, slower the
1.126 brouard 847: convergence.
848:
849: The advantage of this computer programme, compared to a simple
850: multinomial logistic model, is clear when the delay between waves is not
851: identical for each individual. Also, if a individual missed an
852: intermediate interview, the information is lost, but taken into
853: account using an interpolation or extrapolation.
854:
855: hPijx is the probability to be observed in state i at age x+h
856: conditional to the observed state i at age x. The delay 'h' can be
857: split into an exact number (nh*stepm) of unobserved intermediate
858: states. This elementary transition (by month, quarter,
859: semester or year) is modelled as a multinomial logistic. The hPx
860: matrix is simply the matrix product of nh*stepm elementary matrices
861: and the contribution of each individual to the likelihood is simply
862: hPijx.
863:
864: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 865: of the life expectancies. It also computes the period (stable) prevalence.
866:
867: Back prevalence and projections:
1.227 brouard 868:
869: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
870: double agemaxpar, double ftolpl, int *ncvyearp, double
871: dateprev1,double dateprev2, int firstpass, int lastpass, int
872: mobilavproj)
873:
874: Computes the back prevalence limit for any combination of
875: covariate values k at any age between ageminpar and agemaxpar and
876: returns it in **bprlim. In the loops,
877:
878: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
879: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
880:
881: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 882: Computes for any combination of covariates k and any age between bage and fage
883: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
884: oldm=oldms;savm=savms;
1.227 brouard 885:
1.267 brouard 886: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 887: Computes the transition matrix starting at age 'age' over
888: 'nhstepm*hstepm*stepm' months (i.e. until
889: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 890: nhstepm*hstepm matrices.
891:
892: Returns p3mat[i][j][h] after calling
893: p3mat[i][j][h]=matprod2(newm,
894: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
895: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
896: oldm);
1.226 brouard 897:
898: Important routines
899:
900: - func (or funcone), computes logit (pij) distinguishing
901: o fixed variables (single or product dummies or quantitative);
902: o varying variables by:
903: (1) wave (single, product dummies, quantitative),
904: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
905: % fixed dummy (treated) or quantitative (not done because time-consuming);
906: % varying dummy (not done) or quantitative (not done);
907: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
908: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
909: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
910: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
911: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 912:
1.226 brouard 913:
914:
1.133 brouard 915: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
916: Institut national d'études démographiques, Paris.
1.126 brouard 917: This software have been partly granted by Euro-REVES, a concerted action
918: from the European Union.
919: It is copyrighted identically to a GNU software product, ie programme and
920: software can be distributed freely for non commercial use. Latest version
921: can be accessed at http://euroreves.ined.fr/imach .
922:
923: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
924: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
925:
926: **********************************************************************/
927: /*
928: main
929: read parameterfile
930: read datafile
931: concatwav
932: freqsummary
933: if (mle >= 1)
934: mlikeli
935: print results files
936: if mle==1
937: computes hessian
938: read end of parameter file: agemin, agemax, bage, fage, estepm
939: begin-prev-date,...
940: open gnuplot file
941: open html file
1.145 brouard 942: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
943: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
944: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
945: freexexit2 possible for memory heap.
946:
947: h Pij x | pij_nom ficrestpij
948: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
949: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
950: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
951:
952: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
953: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
954: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
955: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
956: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
957:
1.126 brouard 958: forecasting if prevfcast==1 prevforecast call prevalence()
959: health expectancies
960: Variance-covariance of DFLE
961: prevalence()
962: movingaverage()
963: varevsij()
964: if popbased==1 varevsij(,popbased)
965: total life expectancies
966: Variance of period (stable) prevalence
967: end
968: */
969:
1.187 brouard 970: /* #define DEBUG */
971: /* #define DEBUGBRENT */
1.203 brouard 972: /* #define DEBUGLINMIN */
973: /* #define DEBUGHESS */
974: #define DEBUGHESSIJ
1.224 brouard 975: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 976: #define POWELL /* Instead of NLOPT */
1.224 brouard 977: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 978: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
979: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 980:
981: #include <math.h>
982: #include <stdio.h>
983: #include <stdlib.h>
984: #include <string.h>
1.226 brouard 985: #include <ctype.h>
1.159 brouard 986:
987: #ifdef _WIN32
988: #include <io.h>
1.172 brouard 989: #include <windows.h>
990: #include <tchar.h>
1.159 brouard 991: #else
1.126 brouard 992: #include <unistd.h>
1.159 brouard 993: #endif
1.126 brouard 994:
995: #include <limits.h>
996: #include <sys/types.h>
1.171 brouard 997:
998: #if defined(__GNUC__)
999: #include <sys/utsname.h> /* Doesn't work on Windows */
1000: #endif
1001:
1.126 brouard 1002: #include <sys/stat.h>
1003: #include <errno.h>
1.159 brouard 1004: /* extern int errno; */
1.126 brouard 1005:
1.157 brouard 1006: /* #ifdef LINUX */
1007: /* #include <time.h> */
1008: /* #include "timeval.h" */
1009: /* #else */
1010: /* #include <sys/time.h> */
1011: /* #endif */
1012:
1.126 brouard 1013: #include <time.h>
1014:
1.136 brouard 1015: #ifdef GSL
1016: #include <gsl/gsl_errno.h>
1017: #include <gsl/gsl_multimin.h>
1018: #endif
1019:
1.167 brouard 1020:
1.162 brouard 1021: #ifdef NLOPT
1022: #include <nlopt.h>
1023: typedef struct {
1024: double (* function)(double [] );
1025: } myfunc_data ;
1026: #endif
1027:
1.126 brouard 1028: /* #include <libintl.h> */
1029: /* #define _(String) gettext (String) */
1030:
1.251 brouard 1031: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1032:
1033: #define GNUPLOTPROGRAM "gnuplot"
1034: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1035: #define FILENAMELENGTH 132
1036:
1037: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1038: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1039:
1.144 brouard 1040: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
1041: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1042:
1043: #define NINTERVMAX 8
1.144 brouard 1044: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1045: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1046: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 1047: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1048: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1049: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.126 brouard 1050: #define MAXN 20000
1.144 brouard 1051: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1052: /* #define AGESUP 130 */
1.288 ! brouard 1053: /* #define AGESUP 150 */
! 1054: #define AGESUP 200
1.268 brouard 1055: #define AGEINF 0
1.218 brouard 1056: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1057: #define AGEBASE 40
1.194 brouard 1058: #define AGEOVERFLOW 1.e20
1.164 brouard 1059: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1060: #ifdef _WIN32
1061: #define DIRSEPARATOR '\\'
1062: #define CHARSEPARATOR "\\"
1063: #define ODIRSEPARATOR '/'
1064: #else
1.126 brouard 1065: #define DIRSEPARATOR '/'
1066: #define CHARSEPARATOR "/"
1067: #define ODIRSEPARATOR '\\'
1068: #endif
1069:
1.288 ! brouard 1070: /* $Id: imach.c,v 1.287 2018/05/01 17:57:25 brouard Exp $ */
1.126 brouard 1071: /* $State: Exp $ */
1.196 brouard 1072: #include "version.h"
1073: char version[]=__IMACH_VERSION__;
1.283 brouard 1074: 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";
1.288 ! brouard 1075: char fullversion[]="$Revision: 1.287 $ $Date: 2018/05/01 17:57:25 $";
1.126 brouard 1076: char strstart[80];
1077: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1078: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1079: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1080: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1081: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1082: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1083: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1084: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1085: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1086: int cptcovprodnoage=0; /**< Number of covariate products without age */
1087: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1088: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1089: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1090: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1091: int nsd=0; /**< Total number of single dummy variables (output) */
1092: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1093: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1094: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1095: int ntveff=0; /**< ntveff number of effective time varying variables */
1096: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1097: int cptcov=0; /* Working variable */
1.218 brouard 1098: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 1099: int npar=NPARMAX;
1100: int nlstate=2; /* Number of live states */
1101: int ndeath=1; /* Number of dead states */
1.130 brouard 1102: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1103: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1104: int popbased=0;
1105:
1106: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1107: int maxwav=0; /* Maxim number of waves */
1108: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1109: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1110: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1111: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1112: int mle=1, weightopt=0;
1.126 brouard 1113: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1114: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1115: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1116: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1117: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1118: int selected(int kvar); /* Is covariate kvar selected for printing results */
1119:
1.130 brouard 1120: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1121: double **matprod2(); /* test */
1.126 brouard 1122: double **oldm, **newm, **savm; /* Working pointers to matrices */
1123: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1124: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1125:
1.136 brouard 1126: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1127: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1128: FILE *ficlog, *ficrespow;
1.130 brouard 1129: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1130: double fretone; /* Only one call to likelihood */
1.130 brouard 1131: long ipmx=0; /* Number of contributions */
1.126 brouard 1132: double sw; /* Sum of weights */
1133: char filerespow[FILENAMELENGTH];
1134: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1135: FILE *ficresilk;
1136: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1137: FILE *ficresprobmorprev;
1138: FILE *fichtm, *fichtmcov; /* Html File */
1139: FILE *ficreseij;
1140: char filerese[FILENAMELENGTH];
1141: FILE *ficresstdeij;
1142: char fileresstde[FILENAMELENGTH];
1143: FILE *ficrescveij;
1144: char filerescve[FILENAMELENGTH];
1145: FILE *ficresvij;
1146: char fileresv[FILENAMELENGTH];
1.269 brouard 1147:
1.126 brouard 1148: char title[MAXLINE];
1.234 brouard 1149: char model[MAXLINE]; /**< The model line */
1.217 brouard 1150: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1151: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1152: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1153: char command[FILENAMELENGTH];
1154: int outcmd=0;
1155:
1.217 brouard 1156: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1157: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1158: char filelog[FILENAMELENGTH]; /* Log file */
1159: char filerest[FILENAMELENGTH];
1160: char fileregp[FILENAMELENGTH];
1161: char popfile[FILENAMELENGTH];
1162:
1163: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1164:
1.157 brouard 1165: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1166: /* struct timezone tzp; */
1167: /* extern int gettimeofday(); */
1168: struct tm tml, *gmtime(), *localtime();
1169:
1170: extern time_t time();
1171:
1172: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1173: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1174: struct tm tm;
1175:
1.126 brouard 1176: char strcurr[80], strfor[80];
1177:
1178: char *endptr;
1179: long lval;
1180: double dval;
1181:
1182: #define NR_END 1
1183: #define FREE_ARG char*
1184: #define FTOL 1.0e-10
1185:
1186: #define NRANSI
1.240 brouard 1187: #define ITMAX 200
1188: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1189:
1190: #define TOL 2.0e-4
1191:
1192: #define CGOLD 0.3819660
1193: #define ZEPS 1.0e-10
1194: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1195:
1196: #define GOLD 1.618034
1197: #define GLIMIT 100.0
1198: #define TINY 1.0e-20
1199:
1200: static double maxarg1,maxarg2;
1201: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1202: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1203:
1204: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1205: #define rint(a) floor(a+0.5)
1.166 brouard 1206: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1207: #define mytinydouble 1.0e-16
1.166 brouard 1208: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1209: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1210: /* static double dsqrarg; */
1211: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1212: static double sqrarg;
1213: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1214: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1215: int agegomp= AGEGOMP;
1216:
1217: int imx;
1218: int stepm=1;
1219: /* Stepm, step in month: minimum step interpolation*/
1220:
1221: int estepm;
1222: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1223:
1224: int m,nb;
1225: long *num;
1.197 brouard 1226: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1227: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1228: covariate for which somebody answered excluding
1229: undefined. Usually 2: 0 and 1. */
1230: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1231: covariate for which somebody answered including
1232: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1233: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1234: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1235: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1236: double *ageexmed,*agecens;
1237: double dateintmean=0;
1238:
1239: double *weight;
1240: int **s; /* Status */
1.141 brouard 1241: double *agedc;
1.145 brouard 1242: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1243: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1244: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1245: double **coqvar; /* Fixed quantitative covariate nqv */
1246: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1247: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1248: double idx;
1249: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1250: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1251: /*k 1 2 3 4 5 6 7 8 9 */
1252: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1253: /* Tndvar[k] 1 2 3 4 5 */
1254: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1255: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1256: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1257: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1258: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1259: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1260: /* Tprod[i]=k 4 7 */
1261: /* Tage[i]=k 5 8 */
1262: /* */
1263: /* Type */
1264: /* V 1 2 3 4 5 */
1265: /* F F V V V */
1266: /* D Q D D Q */
1267: /* */
1268: int *TvarsD;
1269: int *TvarsDind;
1270: int *TvarsQ;
1271: int *TvarsQind;
1272:
1.235 brouard 1273: #define MAXRESULTLINES 10
1274: int nresult=0;
1.258 brouard 1275: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1276: int TKresult[MAXRESULTLINES];
1.237 brouard 1277: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1278: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1279: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1280: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1281: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1282: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1283:
1.234 brouard 1284: /* 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 1285: 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 */
1286: 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 */
1287: 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 */
1288: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1289: 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 */
1290: 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 1291: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1292: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1293: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1294: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1295: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1296: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1297: 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 */
1298: 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 */
1299:
1.230 brouard 1300: int *Tvarsel; /**< Selected covariates for output */
1301: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1302: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1303: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1304: 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 1305: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1306: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1307: int *Tage;
1.227 brouard 1308: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1309: 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 1310: 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*/
1311: 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 1312: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1313: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1314: int **Tvard;
1315: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1316: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1317: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1318: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1319: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1320: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1321: double *lsurv, *lpop, *tpop;
1322:
1.231 brouard 1323: #define FD 1; /* Fixed dummy covariate */
1324: #define FQ 2; /* Fixed quantitative covariate */
1325: #define FP 3; /* Fixed product covariate */
1326: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1327: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1328: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1329: #define VD 10; /* Varying dummy covariate */
1330: #define VQ 11; /* Varying quantitative covariate */
1331: #define VP 12; /* Varying product covariate */
1332: #define VPDD 13; /* Varying product dummy*dummy covariate */
1333: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1334: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1335: #define APFD 16; /* Age product * fixed dummy covariate */
1336: #define APFQ 17; /* Age product * fixed quantitative covariate */
1337: #define APVD 18; /* Age product * varying dummy covariate */
1338: #define APVQ 19; /* Age product * varying quantitative covariate */
1339:
1340: #define FTYPE 1; /* Fixed covariate */
1341: #define VTYPE 2; /* Varying covariate (loop in wave) */
1342: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1343:
1344: struct kmodel{
1345: int maintype; /* main type */
1346: int subtype; /* subtype */
1347: };
1348: struct kmodel modell[NCOVMAX];
1349:
1.143 brouard 1350: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1351: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1352:
1353: /**************** split *************************/
1354: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1355: {
1356: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1357: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1358: */
1359: char *ss; /* pointer */
1.186 brouard 1360: int l1=0, l2=0; /* length counters */
1.126 brouard 1361:
1362: l1 = strlen(path ); /* length of path */
1363: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1364: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1365: if ( ss == NULL ) { /* no directory, so determine current directory */
1366: strcpy( name, path ); /* we got the fullname name because no directory */
1367: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1368: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1369: /* get current working directory */
1370: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1371: #ifdef WIN32
1372: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1373: #else
1374: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1375: #endif
1.126 brouard 1376: return( GLOCK_ERROR_GETCWD );
1377: }
1378: /* got dirc from getcwd*/
1379: printf(" DIRC = %s \n",dirc);
1.205 brouard 1380: } else { /* strip directory from path */
1.126 brouard 1381: ss++; /* after this, the filename */
1382: l2 = strlen( ss ); /* length of filename */
1383: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1384: strcpy( name, ss ); /* save file name */
1385: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1386: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1387: printf(" DIRC2 = %s \n",dirc);
1388: }
1389: /* We add a separator at the end of dirc if not exists */
1390: l1 = strlen( dirc ); /* length of directory */
1391: if( dirc[l1-1] != DIRSEPARATOR ){
1392: dirc[l1] = DIRSEPARATOR;
1393: dirc[l1+1] = 0;
1394: printf(" DIRC3 = %s \n",dirc);
1395: }
1396: ss = strrchr( name, '.' ); /* find last / */
1397: if (ss >0){
1398: ss++;
1399: strcpy(ext,ss); /* save extension */
1400: l1= strlen( name);
1401: l2= strlen(ss)+1;
1402: strncpy( finame, name, l1-l2);
1403: finame[l1-l2]= 0;
1404: }
1405:
1406: return( 0 ); /* we're done */
1407: }
1408:
1409:
1410: /******************************************/
1411:
1412: void replace_back_to_slash(char *s, char*t)
1413: {
1414: int i;
1415: int lg=0;
1416: i=0;
1417: lg=strlen(t);
1418: for(i=0; i<= lg; i++) {
1419: (s[i] = t[i]);
1420: if (t[i]== '\\') s[i]='/';
1421: }
1422: }
1423:
1.132 brouard 1424: char *trimbb(char *out, char *in)
1.137 brouard 1425: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1426: char *s;
1427: s=out;
1428: while (*in != '\0'){
1.137 brouard 1429: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1430: in++;
1431: }
1432: *out++ = *in++;
1433: }
1434: *out='\0';
1435: return s;
1436: }
1437:
1.187 brouard 1438: /* char *substrchaine(char *out, char *in, char *chain) */
1439: /* { */
1440: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1441: /* char *s, *t; */
1442: /* t=in;s=out; */
1443: /* while ((*in != *chain) && (*in != '\0')){ */
1444: /* *out++ = *in++; */
1445: /* } */
1446:
1447: /* /\* *in matches *chain *\/ */
1448: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1449: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1450: /* } */
1451: /* in--; chain--; */
1452: /* while ( (*in != '\0')){ */
1453: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1454: /* *out++ = *in++; */
1455: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1456: /* } */
1457: /* *out='\0'; */
1458: /* out=s; */
1459: /* return out; */
1460: /* } */
1461: char *substrchaine(char *out, char *in, char *chain)
1462: {
1463: /* Substract chain 'chain' from 'in', return and output 'out' */
1464: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1465:
1466: char *strloc;
1467:
1468: strcpy (out, in);
1469: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1470: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1471: if(strloc != NULL){
1472: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1473: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1474: /* strcpy (strloc, strloc +strlen(chain));*/
1475: }
1476: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1477: return out;
1478: }
1479:
1480:
1.145 brouard 1481: char *cutl(char *blocc, char *alocc, char *in, char occ)
1482: {
1.187 brouard 1483: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1484: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1485: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1486: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1487: */
1.160 brouard 1488: char *s, *t;
1.145 brouard 1489: t=in;s=in;
1490: while ((*in != occ) && (*in != '\0')){
1491: *alocc++ = *in++;
1492: }
1493: if( *in == occ){
1494: *(alocc)='\0';
1495: s=++in;
1496: }
1497:
1498: if (s == t) {/* occ not found */
1499: *(alocc-(in-s))='\0';
1500: in=s;
1501: }
1502: while ( *in != '\0'){
1503: *blocc++ = *in++;
1504: }
1505:
1506: *blocc='\0';
1507: return t;
1508: }
1.137 brouard 1509: char *cutv(char *blocc, char *alocc, char *in, char occ)
1510: {
1.187 brouard 1511: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1512: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1513: gives blocc="abcdef2ghi" and alocc="j".
1514: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1515: */
1516: char *s, *t;
1517: t=in;s=in;
1518: while (*in != '\0'){
1519: while( *in == occ){
1520: *blocc++ = *in++;
1521: s=in;
1522: }
1523: *blocc++ = *in++;
1524: }
1525: if (s == t) /* occ not found */
1526: *(blocc-(in-s))='\0';
1527: else
1528: *(blocc-(in-s)-1)='\0';
1529: in=s;
1530: while ( *in != '\0'){
1531: *alocc++ = *in++;
1532: }
1533:
1534: *alocc='\0';
1535: return s;
1536: }
1537:
1.126 brouard 1538: int nbocc(char *s, char occ)
1539: {
1540: int i,j=0;
1541: int lg=20;
1542: i=0;
1543: lg=strlen(s);
1544: for(i=0; i<= lg; i++) {
1.234 brouard 1545: if (s[i] == occ ) j++;
1.126 brouard 1546: }
1547: return j;
1548: }
1549:
1.137 brouard 1550: /* void cutv(char *u,char *v, char*t, char occ) */
1551: /* { */
1552: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1553: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1554: /* gives u="abcdef2ghi" and v="j" *\/ */
1555: /* int i,lg,j,p=0; */
1556: /* i=0; */
1557: /* lg=strlen(t); */
1558: /* for(j=0; j<=lg-1; j++) { */
1559: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1560: /* } */
1.126 brouard 1561:
1.137 brouard 1562: /* for(j=0; j<p; j++) { */
1563: /* (u[j] = t[j]); */
1564: /* } */
1565: /* u[p]='\0'; */
1.126 brouard 1566:
1.137 brouard 1567: /* for(j=0; j<= lg; j++) { */
1568: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1569: /* } */
1570: /* } */
1.126 brouard 1571:
1.160 brouard 1572: #ifdef _WIN32
1573: char * strsep(char **pp, const char *delim)
1574: {
1575: char *p, *q;
1576:
1577: if ((p = *pp) == NULL)
1578: return 0;
1579: if ((q = strpbrk (p, delim)) != NULL)
1580: {
1581: *pp = q + 1;
1582: *q = '\0';
1583: }
1584: else
1585: *pp = 0;
1586: return p;
1587: }
1588: #endif
1589:
1.126 brouard 1590: /********************** nrerror ********************/
1591:
1592: void nrerror(char error_text[])
1593: {
1594: fprintf(stderr,"ERREUR ...\n");
1595: fprintf(stderr,"%s\n",error_text);
1596: exit(EXIT_FAILURE);
1597: }
1598: /*********************** vector *******************/
1599: double *vector(int nl, int nh)
1600: {
1601: double *v;
1602: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1603: if (!v) nrerror("allocation failure in vector");
1604: return v-nl+NR_END;
1605: }
1606:
1607: /************************ free vector ******************/
1608: void free_vector(double*v, int nl, int nh)
1609: {
1610: free((FREE_ARG)(v+nl-NR_END));
1611: }
1612:
1613: /************************ivector *******************************/
1614: int *ivector(long nl,long nh)
1615: {
1616: int *v;
1617: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1618: if (!v) nrerror("allocation failure in ivector");
1619: return v-nl+NR_END;
1620: }
1621:
1622: /******************free ivector **************************/
1623: void free_ivector(int *v, long nl, long nh)
1624: {
1625: free((FREE_ARG)(v+nl-NR_END));
1626: }
1627:
1628: /************************lvector *******************************/
1629: long *lvector(long nl,long nh)
1630: {
1631: long *v;
1632: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1633: if (!v) nrerror("allocation failure in ivector");
1634: return v-nl+NR_END;
1635: }
1636:
1637: /******************free lvector **************************/
1638: void free_lvector(long *v, long nl, long nh)
1639: {
1640: free((FREE_ARG)(v+nl-NR_END));
1641: }
1642:
1643: /******************* imatrix *******************************/
1644: int **imatrix(long nrl, long nrh, long ncl, long nch)
1645: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1646: {
1647: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1648: int **m;
1649:
1650: /* allocate pointers to rows */
1651: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1652: if (!m) nrerror("allocation failure 1 in matrix()");
1653: m += NR_END;
1654: m -= nrl;
1655:
1656:
1657: /* allocate rows and set pointers to them */
1658: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1659: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1660: m[nrl] += NR_END;
1661: m[nrl] -= ncl;
1662:
1663: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1664:
1665: /* return pointer to array of pointers to rows */
1666: return m;
1667: }
1668:
1669: /****************** free_imatrix *************************/
1670: void free_imatrix(m,nrl,nrh,ncl,nch)
1671: int **m;
1672: long nch,ncl,nrh,nrl;
1673: /* free an int matrix allocated by imatrix() */
1674: {
1675: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1676: free((FREE_ARG) (m+nrl-NR_END));
1677: }
1678:
1679: /******************* matrix *******************************/
1680: double **matrix(long nrl, long nrh, long ncl, long nch)
1681: {
1682: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1683: double **m;
1684:
1685: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1686: if (!m) nrerror("allocation failure 1 in matrix()");
1687: m += NR_END;
1688: m -= nrl;
1689:
1690: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1691: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1692: m[nrl] += NR_END;
1693: m[nrl] -= ncl;
1694:
1695: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1696: return m;
1.145 brouard 1697: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1698: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1699: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1700: */
1701: }
1702:
1703: /*************************free matrix ************************/
1704: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1705: {
1706: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1707: free((FREE_ARG)(m+nrl-NR_END));
1708: }
1709:
1710: /******************* ma3x *******************************/
1711: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1712: {
1713: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1714: double ***m;
1715:
1716: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1717: if (!m) nrerror("allocation failure 1 in matrix()");
1718: m += NR_END;
1719: m -= nrl;
1720:
1721: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1722: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1723: m[nrl] += NR_END;
1724: m[nrl] -= ncl;
1725:
1726: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1727:
1728: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1729: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1730: m[nrl][ncl] += NR_END;
1731: m[nrl][ncl] -= nll;
1732: for (j=ncl+1; j<=nch; j++)
1733: m[nrl][j]=m[nrl][j-1]+nlay;
1734:
1735: for (i=nrl+1; i<=nrh; i++) {
1736: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1737: for (j=ncl+1; j<=nch; j++)
1738: m[i][j]=m[i][j-1]+nlay;
1739: }
1740: return m;
1741: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1742: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1743: */
1744: }
1745:
1746: /*************************free ma3x ************************/
1747: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1748: {
1749: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1750: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1751: free((FREE_ARG)(m+nrl-NR_END));
1752: }
1753:
1754: /*************** function subdirf ***********/
1755: char *subdirf(char fileres[])
1756: {
1757: /* Caution optionfilefiname is hidden */
1758: strcpy(tmpout,optionfilefiname);
1759: strcat(tmpout,"/"); /* Add to the right */
1760: strcat(tmpout,fileres);
1761: return tmpout;
1762: }
1763:
1764: /*************** function subdirf2 ***********/
1765: char *subdirf2(char fileres[], char *preop)
1766: {
1767:
1768: /* Caution optionfilefiname is hidden */
1769: strcpy(tmpout,optionfilefiname);
1770: strcat(tmpout,"/");
1771: strcat(tmpout,preop);
1772: strcat(tmpout,fileres);
1773: return tmpout;
1774: }
1775:
1776: /*************** function subdirf3 ***********/
1777: char *subdirf3(char fileres[], char *preop, char *preop2)
1778: {
1779:
1780: /* Caution optionfilefiname is hidden */
1781: strcpy(tmpout,optionfilefiname);
1782: strcat(tmpout,"/");
1783: strcat(tmpout,preop);
1784: strcat(tmpout,preop2);
1785: strcat(tmpout,fileres);
1786: return tmpout;
1787: }
1.213 brouard 1788:
1789: /*************** function subdirfext ***********/
1790: char *subdirfext(char fileres[], char *preop, char *postop)
1791: {
1792:
1793: strcpy(tmpout,preop);
1794: strcat(tmpout,fileres);
1795: strcat(tmpout,postop);
1796: return tmpout;
1797: }
1.126 brouard 1798:
1.213 brouard 1799: /*************** function subdirfext3 ***********/
1800: char *subdirfext3(char fileres[], char *preop, char *postop)
1801: {
1802:
1803: /* Caution optionfilefiname is hidden */
1804: strcpy(tmpout,optionfilefiname);
1805: strcat(tmpout,"/");
1806: strcat(tmpout,preop);
1807: strcat(tmpout,fileres);
1808: strcat(tmpout,postop);
1809: return tmpout;
1810: }
1811:
1.162 brouard 1812: char *asc_diff_time(long time_sec, char ascdiff[])
1813: {
1814: long sec_left, days, hours, minutes;
1815: days = (time_sec) / (60*60*24);
1816: sec_left = (time_sec) % (60*60*24);
1817: hours = (sec_left) / (60*60) ;
1818: sec_left = (sec_left) %(60*60);
1819: minutes = (sec_left) /60;
1820: sec_left = (sec_left) % (60);
1821: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1822: return ascdiff;
1823: }
1824:
1.126 brouard 1825: /***************** f1dim *************************/
1826: extern int ncom;
1827: extern double *pcom,*xicom;
1828: extern double (*nrfunc)(double []);
1829:
1830: double f1dim(double x)
1831: {
1832: int j;
1833: double f;
1834: double *xt;
1835:
1836: xt=vector(1,ncom);
1837: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1838: f=(*nrfunc)(xt);
1839: free_vector(xt,1,ncom);
1840: return f;
1841: }
1842:
1843: /*****************brent *************************/
1844: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1845: {
1846: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1847: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1848: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1849: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1850: * returned function value.
1851: */
1.126 brouard 1852: int iter;
1853: double a,b,d,etemp;
1.159 brouard 1854: double fu=0,fv,fw,fx;
1.164 brouard 1855: double ftemp=0.;
1.126 brouard 1856: double p,q,r,tol1,tol2,u,v,w,x,xm;
1857: double e=0.0;
1858:
1859: a=(ax < cx ? ax : cx);
1860: b=(ax > cx ? ax : cx);
1861: x=w=v=bx;
1862: fw=fv=fx=(*f)(x);
1863: for (iter=1;iter<=ITMAX;iter++) {
1864: xm=0.5*(a+b);
1865: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1866: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1867: printf(".");fflush(stdout);
1868: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1869: #ifdef DEBUGBRENT
1.126 brouard 1870: 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);
1871: 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);
1872: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1873: #endif
1874: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1875: *xmin=x;
1876: return fx;
1877: }
1878: ftemp=fu;
1879: if (fabs(e) > tol1) {
1880: r=(x-w)*(fx-fv);
1881: q=(x-v)*(fx-fw);
1882: p=(x-v)*q-(x-w)*r;
1883: q=2.0*(q-r);
1884: if (q > 0.0) p = -p;
1885: q=fabs(q);
1886: etemp=e;
1887: e=d;
1888: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1889: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1890: else {
1.224 brouard 1891: d=p/q;
1892: u=x+d;
1893: if (u-a < tol2 || b-u < tol2)
1894: d=SIGN(tol1,xm-x);
1.126 brouard 1895: }
1896: } else {
1897: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1898: }
1899: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1900: fu=(*f)(u);
1901: if (fu <= fx) {
1902: if (u >= x) a=x; else b=x;
1903: SHFT(v,w,x,u)
1.183 brouard 1904: SHFT(fv,fw,fx,fu)
1905: } else {
1906: if (u < x) a=u; else b=u;
1907: if (fu <= fw || w == x) {
1.224 brouard 1908: v=w;
1909: w=u;
1910: fv=fw;
1911: fw=fu;
1.183 brouard 1912: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1913: v=u;
1914: fv=fu;
1.183 brouard 1915: }
1916: }
1.126 brouard 1917: }
1918: nrerror("Too many iterations in brent");
1919: *xmin=x;
1920: return fx;
1921: }
1922:
1923: /****************** mnbrak ***********************/
1924:
1925: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1926: double (*func)(double))
1.183 brouard 1927: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1928: the downhill direction (defined by the function as evaluated at the initial points) and returns
1929: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1930: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1931: */
1.126 brouard 1932: double ulim,u,r,q, dum;
1933: double fu;
1.187 brouard 1934:
1935: double scale=10.;
1936: int iterscale=0;
1937:
1938: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1939: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1940:
1941:
1942: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1943: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1944: /* *bx = *ax - (*ax - *bx)/scale; */
1945: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1946: /* } */
1947:
1.126 brouard 1948: if (*fb > *fa) {
1949: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1950: SHFT(dum,*fb,*fa,dum)
1951: }
1.126 brouard 1952: *cx=(*bx)+GOLD*(*bx-*ax);
1953: *fc=(*func)(*cx);
1.183 brouard 1954: #ifdef DEBUG
1.224 brouard 1955: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1956: 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 1957: #endif
1.224 brouard 1958: 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 1959: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1960: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1961: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1962: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1963: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1964: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1965: fu=(*func)(u);
1.163 brouard 1966: #ifdef DEBUG
1967: /* f(x)=A(x-u)**2+f(u) */
1968: double A, fparabu;
1969: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1970: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 1971: 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);
1972: 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 1973: /* And thus,it can be that fu > *fc even if fparabu < *fc */
1974: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
1975: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
1976: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 1977: #endif
1.184 brouard 1978: #ifdef MNBRAKORIGINAL
1.183 brouard 1979: #else
1.191 brouard 1980: /* if (fu > *fc) { */
1981: /* #ifdef DEBUG */
1982: /* printf("mnbrak4 fu > fc \n"); */
1983: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
1984: /* #endif */
1985: /* /\* 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 *\\/ *\/ */
1986: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
1987: /* dum=u; /\* Shifting c and u *\/ */
1988: /* u = *cx; */
1989: /* *cx = dum; */
1990: /* dum = fu; */
1991: /* fu = *fc; */
1992: /* *fc =dum; */
1993: /* } else { /\* end *\/ */
1994: /* #ifdef DEBUG */
1995: /* printf("mnbrak3 fu < fc \n"); */
1996: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
1997: /* #endif */
1998: /* dum=u; /\* Shifting c and u *\/ */
1999: /* u = *cx; */
2000: /* *cx = dum; */
2001: /* dum = fu; */
2002: /* fu = *fc; */
2003: /* *fc =dum; */
2004: /* } */
1.224 brouard 2005: #ifdef DEBUGMNBRAK
2006: double A, fparabu;
2007: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2008: fparabu= *fa - A*(*ax-u)*(*ax-u);
2009: 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);
2010: 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 2011: #endif
1.191 brouard 2012: dum=u; /* Shifting c and u */
2013: u = *cx;
2014: *cx = dum;
2015: dum = fu;
2016: fu = *fc;
2017: *fc =dum;
1.183 brouard 2018: #endif
1.162 brouard 2019: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2020: #ifdef DEBUG
1.224 brouard 2021: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2022: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2023: #endif
1.126 brouard 2024: fu=(*func)(u);
2025: if (fu < *fc) {
1.183 brouard 2026: #ifdef DEBUG
1.224 brouard 2027: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2028: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2029: #endif
2030: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2031: SHFT(*fb,*fc,fu,(*func)(u))
2032: #ifdef DEBUG
2033: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2034: #endif
2035: }
1.162 brouard 2036: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2037: #ifdef DEBUG
1.224 brouard 2038: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2039: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2040: #endif
1.126 brouard 2041: u=ulim;
2042: fu=(*func)(u);
1.183 brouard 2043: } else { /* u could be left to b (if r > q parabola has a maximum) */
2044: #ifdef DEBUG
1.224 brouard 2045: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2046: 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 2047: #endif
1.126 brouard 2048: u=(*cx)+GOLD*(*cx-*bx);
2049: fu=(*func)(u);
1.224 brouard 2050: #ifdef DEBUG
2051: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2052: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2053: #endif
1.183 brouard 2054: } /* end tests */
1.126 brouard 2055: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2056: SHFT(*fa,*fb,*fc,fu)
2057: #ifdef DEBUG
1.224 brouard 2058: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2059: 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 2060: #endif
2061: } /* 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 2062: }
2063:
2064: /*************** linmin ************************/
1.162 brouard 2065: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2066: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2067: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2068: the value of func at the returned location p . This is actually all accomplished by calling the
2069: routines mnbrak and brent .*/
1.126 brouard 2070: int ncom;
2071: double *pcom,*xicom;
2072: double (*nrfunc)(double []);
2073:
1.224 brouard 2074: #ifdef LINMINORIGINAL
1.126 brouard 2075: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2076: #else
2077: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2078: #endif
1.126 brouard 2079: {
2080: double brent(double ax, double bx, double cx,
2081: double (*f)(double), double tol, double *xmin);
2082: double f1dim(double x);
2083: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2084: double *fc, double (*func)(double));
2085: int j;
2086: double xx,xmin,bx,ax;
2087: double fx,fb,fa;
1.187 brouard 2088:
1.203 brouard 2089: #ifdef LINMINORIGINAL
2090: #else
2091: double scale=10., axs, xxs; /* Scale added for infinity */
2092: #endif
2093:
1.126 brouard 2094: ncom=n;
2095: pcom=vector(1,n);
2096: xicom=vector(1,n);
2097: nrfunc=func;
2098: for (j=1;j<=n;j++) {
2099: pcom[j]=p[j];
1.202 brouard 2100: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2101: }
1.187 brouard 2102:
1.203 brouard 2103: #ifdef LINMINORIGINAL
2104: xx=1.;
2105: #else
2106: axs=0.0;
2107: xxs=1.;
2108: do{
2109: xx= xxs;
2110: #endif
1.187 brouard 2111: ax=0.;
2112: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2113: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2114: /* 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)) */
2115: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2116: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2117: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2118: /* 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 2119: #ifdef LINMINORIGINAL
2120: #else
2121: if (fx != fx){
1.224 brouard 2122: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2123: printf("|");
2124: fprintf(ficlog,"|");
1.203 brouard 2125: #ifdef DEBUGLINMIN
1.224 brouard 2126: 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 2127: #endif
2128: }
1.224 brouard 2129: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2130: #endif
2131:
1.191 brouard 2132: #ifdef DEBUGLINMIN
2133: 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 2134: 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 2135: #endif
1.224 brouard 2136: #ifdef LINMINORIGINAL
2137: #else
2138: if(fb == fx){ /* Flat function in the direction */
2139: xmin=xx;
2140: *flat=1;
2141: }else{
2142: *flat=0;
2143: #endif
2144: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2145: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2146: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2147: /* fmin = f(p[j] + xmin * xi[j]) */
2148: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2149: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2150: #ifdef DEBUG
1.224 brouard 2151: 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);
2152: 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);
2153: #endif
2154: #ifdef LINMINORIGINAL
2155: #else
2156: }
1.126 brouard 2157: #endif
1.191 brouard 2158: #ifdef DEBUGLINMIN
2159: printf("linmin end ");
1.202 brouard 2160: fprintf(ficlog,"linmin end ");
1.191 brouard 2161: #endif
1.126 brouard 2162: for (j=1;j<=n;j++) {
1.203 brouard 2163: #ifdef LINMINORIGINAL
2164: xi[j] *= xmin;
2165: #else
2166: #ifdef DEBUGLINMIN
2167: if(xxs <1.0)
2168: printf(" before xi[%d]=%12.8f", j,xi[j]);
2169: #endif
2170: 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) */
2171: #ifdef DEBUGLINMIN
2172: if(xxs <1.0)
2173: 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 );
2174: #endif
2175: #endif
1.187 brouard 2176: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2177: }
1.191 brouard 2178: #ifdef DEBUGLINMIN
1.203 brouard 2179: printf("\n");
1.191 brouard 2180: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2181: 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 2182: for (j=1;j<=n;j++) {
1.202 brouard 2183: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2184: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2185: if(j % ncovmodel == 0){
1.191 brouard 2186: printf("\n");
1.202 brouard 2187: fprintf(ficlog,"\n");
2188: }
1.191 brouard 2189: }
1.203 brouard 2190: #else
1.191 brouard 2191: #endif
1.126 brouard 2192: free_vector(xicom,1,n);
2193: free_vector(pcom,1,n);
2194: }
2195:
2196:
2197: /*************** powell ************************/
1.162 brouard 2198: /*
2199: Minimization of a function func of n variables. Input consists of an initial starting point
2200: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2201: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2202: such that failure to decrease by more than this amount on one iteration signals doneness. On
2203: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2204: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2205: */
1.224 brouard 2206: #ifdef LINMINORIGINAL
2207: #else
2208: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2209: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2210: #endif
1.126 brouard 2211: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2212: double (*func)(double []))
2213: {
1.224 brouard 2214: #ifdef LINMINORIGINAL
2215: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2216: double (*func)(double []));
1.224 brouard 2217: #else
1.241 brouard 2218: void linmin(double p[], double xi[], int n, double *fret,
2219: double (*func)(double []),int *flat);
1.224 brouard 2220: #endif
1.239 brouard 2221: int i,ibig,j,jk,k;
1.126 brouard 2222: double del,t,*pt,*ptt,*xit;
1.181 brouard 2223: double directest;
1.126 brouard 2224: double fp,fptt;
2225: double *xits;
2226: int niterf, itmp;
1.224 brouard 2227: #ifdef LINMINORIGINAL
2228: #else
2229:
2230: flatdir=ivector(1,n);
2231: for (j=1;j<=n;j++) flatdir[j]=0;
2232: #endif
1.126 brouard 2233:
2234: pt=vector(1,n);
2235: ptt=vector(1,n);
2236: xit=vector(1,n);
2237: xits=vector(1,n);
2238: *fret=(*func)(p);
2239: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2240: rcurr_time = time(NULL);
1.126 brouard 2241: for (*iter=1;;++(*iter)) {
1.187 brouard 2242: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2243: ibig=0;
2244: del=0.0;
1.157 brouard 2245: rlast_time=rcurr_time;
2246: /* (void) gettimeofday(&curr_time,&tzp); */
2247: rcurr_time = time(NULL);
2248: curr_time = *localtime(&rcurr_time);
2249: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2250: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2251: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2252: for (i=1;i<=n;i++) {
1.126 brouard 2253: fprintf(ficrespow," %.12lf", p[i]);
2254: }
1.239 brouard 2255: fprintf(ficrespow,"\n");fflush(ficrespow);
2256: printf("\n#model= 1 + age ");
2257: fprintf(ficlog,"\n#model= 1 + age ");
2258: if(nagesqr==1){
1.241 brouard 2259: printf(" + age*age ");
2260: fprintf(ficlog," + age*age ");
1.239 brouard 2261: }
2262: for(j=1;j <=ncovmodel-2;j++){
2263: if(Typevar[j]==0) {
2264: printf(" + V%d ",Tvar[j]);
2265: fprintf(ficlog," + V%d ",Tvar[j]);
2266: }else if(Typevar[j]==1) {
2267: printf(" + V%d*age ",Tvar[j]);
2268: fprintf(ficlog," + V%d*age ",Tvar[j]);
2269: }else if(Typevar[j]==2) {
2270: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2271: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2272: }
2273: }
1.126 brouard 2274: printf("\n");
1.239 brouard 2275: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2276: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2277: fprintf(ficlog,"\n");
1.239 brouard 2278: for(i=1,jk=1; i <=nlstate; i++){
2279: for(k=1; k <=(nlstate+ndeath); k++){
2280: if (k != i) {
2281: printf("%d%d ",i,k);
2282: fprintf(ficlog,"%d%d ",i,k);
2283: for(j=1; j <=ncovmodel; j++){
2284: printf("%12.7f ",p[jk]);
2285: fprintf(ficlog,"%12.7f ",p[jk]);
2286: jk++;
2287: }
2288: printf("\n");
2289: fprintf(ficlog,"\n");
2290: }
2291: }
2292: }
1.241 brouard 2293: if(*iter <=3 && *iter >1){
1.157 brouard 2294: tml = *localtime(&rcurr_time);
2295: strcpy(strcurr,asctime(&tml));
2296: rforecast_time=rcurr_time;
1.126 brouard 2297: itmp = strlen(strcurr);
2298: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2299: strcurr[itmp-1]='\0';
1.162 brouard 2300: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2301: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2302: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2303: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2304: forecast_time = *localtime(&rforecast_time);
2305: strcpy(strfor,asctime(&forecast_time));
2306: itmp = strlen(strfor);
2307: if(strfor[itmp-1]=='\n')
2308: strfor[itmp-1]='\0';
2309: 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);
2310: 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 2311: }
2312: }
1.187 brouard 2313: for (i=1;i<=n;i++) { /* For each direction i */
2314: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2315: fptt=(*fret);
2316: #ifdef DEBUG
1.203 brouard 2317: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2318: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2319: #endif
1.203 brouard 2320: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2321: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2322: #ifdef LINMINORIGINAL
1.188 brouard 2323: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2324: #else
2325: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2326: flatdir[i]=flat; /* Function is vanishing in that direction i */
2327: #endif
2328: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2329: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2330: /* because that direction will be replaced unless the gain del is small */
2331: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2332: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2333: /* with the new direction. */
2334: del=fabs(fptt-(*fret));
2335: ibig=i;
1.126 brouard 2336: }
2337: #ifdef DEBUG
2338: printf("%d %.12e",i,(*fret));
2339: fprintf(ficlog,"%d %.12e",i,(*fret));
2340: for (j=1;j<=n;j++) {
1.224 brouard 2341: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2342: printf(" x(%d)=%.12e",j,xit[j]);
2343: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2344: }
2345: for(j=1;j<=n;j++) {
1.225 brouard 2346: printf(" p(%d)=%.12e",j,p[j]);
2347: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2348: }
2349: printf("\n");
2350: fprintf(ficlog,"\n");
2351: #endif
1.187 brouard 2352: } /* end loop on each direction i */
2353: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2354: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2355: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2356: for(j=1;j<=n;j++) {
1.225 brouard 2357: if(flatdir[j] >0){
2358: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2359: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2360: }
2361: /* printf("\n"); */
2362: /* fprintf(ficlog,"\n"); */
2363: }
1.243 brouard 2364: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2365: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2366: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2367: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2368: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2369: /* decreased of more than 3.84 */
2370: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2371: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2372: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2373:
1.188 brouard 2374: /* Starting the program with initial values given by a former maximization will simply change */
2375: /* the scales of the directions and the directions, because the are reset to canonical directions */
2376: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2377: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2378: #ifdef DEBUG
2379: int k[2],l;
2380: k[0]=1;
2381: k[1]=-1;
2382: printf("Max: %.12e",(*func)(p));
2383: fprintf(ficlog,"Max: %.12e",(*func)(p));
2384: for (j=1;j<=n;j++) {
2385: printf(" %.12e",p[j]);
2386: fprintf(ficlog," %.12e",p[j]);
2387: }
2388: printf("\n");
2389: fprintf(ficlog,"\n");
2390: for(l=0;l<=1;l++) {
2391: for (j=1;j<=n;j++) {
2392: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2393: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2394: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2395: }
2396: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2397: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2398: }
2399: #endif
2400:
1.224 brouard 2401: #ifdef LINMINORIGINAL
2402: #else
2403: free_ivector(flatdir,1,n);
2404: #endif
1.126 brouard 2405: free_vector(xit,1,n);
2406: free_vector(xits,1,n);
2407: free_vector(ptt,1,n);
2408: free_vector(pt,1,n);
2409: return;
1.192 brouard 2410: } /* enough precision */
1.240 brouard 2411: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2412: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2413: ptt[j]=2.0*p[j]-pt[j];
2414: xit[j]=p[j]-pt[j];
2415: pt[j]=p[j];
2416: }
1.181 brouard 2417: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2418: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2419: if (*iter <=4) {
1.225 brouard 2420: #else
2421: #endif
1.224 brouard 2422: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2423: #else
1.161 brouard 2424: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2425: #endif
1.162 brouard 2426: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2427: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2428: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2429: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2430: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2431: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2432: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2433: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2434: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2435: /* Even if f3 <f1, directest can be negative and t >0 */
2436: /* mu² and del² are equal when f3=f1 */
2437: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2438: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2439: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2440: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2441: #ifdef NRCORIGINAL
2442: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2443: #else
2444: 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 2445: t= t- del*SQR(fp-fptt);
1.183 brouard 2446: #endif
1.202 brouard 2447: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2448: #ifdef DEBUG
1.181 brouard 2449: 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);
2450: 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 2451: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2452: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2453: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2454: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2455: 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);
2456: 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);
2457: #endif
1.183 brouard 2458: #ifdef POWELLORIGINAL
2459: if (t < 0.0) { /* Then we use it for new direction */
2460: #else
1.182 brouard 2461: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2462: 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 2463: 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 2464: 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 2465: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2466: }
1.181 brouard 2467: if (directest < 0.0) { /* Then we use it for new direction */
2468: #endif
1.191 brouard 2469: #ifdef DEBUGLINMIN
1.234 brouard 2470: printf("Before linmin in direction P%d-P0\n",n);
2471: for (j=1;j<=n;j++) {
2472: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2473: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2474: if(j % ncovmodel == 0){
2475: printf("\n");
2476: fprintf(ficlog,"\n");
2477: }
2478: }
1.224 brouard 2479: #endif
2480: #ifdef LINMINORIGINAL
1.234 brouard 2481: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2482: #else
1.234 brouard 2483: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2484: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2485: #endif
1.234 brouard 2486:
1.191 brouard 2487: #ifdef DEBUGLINMIN
1.234 brouard 2488: for (j=1;j<=n;j++) {
2489: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2490: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2491: if(j % ncovmodel == 0){
2492: printf("\n");
2493: fprintf(ficlog,"\n");
2494: }
2495: }
1.224 brouard 2496: #endif
1.234 brouard 2497: for (j=1;j<=n;j++) {
2498: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2499: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2500: }
1.224 brouard 2501: #ifdef LINMINORIGINAL
2502: #else
1.234 brouard 2503: for (j=1, flatd=0;j<=n;j++) {
2504: if(flatdir[j]>0)
2505: flatd++;
2506: }
2507: if(flatd >0){
1.255 brouard 2508: printf("%d flat directions: ",flatd);
2509: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2510: for (j=1;j<=n;j++) {
2511: if(flatdir[j]>0){
2512: printf("%d ",j);
2513: fprintf(ficlog,"%d ",j);
2514: }
2515: }
2516: printf("\n");
2517: fprintf(ficlog,"\n");
2518: }
1.191 brouard 2519: #endif
1.234 brouard 2520: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2521: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2522:
1.126 brouard 2523: #ifdef DEBUG
1.234 brouard 2524: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2525: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2526: for(j=1;j<=n;j++){
2527: printf(" %lf",xit[j]);
2528: fprintf(ficlog," %lf",xit[j]);
2529: }
2530: printf("\n");
2531: fprintf(ficlog,"\n");
1.126 brouard 2532: #endif
1.192 brouard 2533: } /* end of t or directest negative */
1.224 brouard 2534: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2535: #else
1.234 brouard 2536: } /* end if (fptt < fp) */
1.192 brouard 2537: #endif
1.225 brouard 2538: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2539: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2540: #else
1.224 brouard 2541: #endif
1.234 brouard 2542: } /* loop iteration */
1.126 brouard 2543: }
1.234 brouard 2544:
1.126 brouard 2545: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2546:
1.235 brouard 2547: 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 2548: {
1.279 brouard 2549: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij
2550: * (and selected quantitative values in nres)
2551: * by left multiplying the unit
2552: * matrix by transitions matrix until convergence is reached with precision ftolpl
2553: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2554: * Wx is row vector: population in state 1, population in state 2, population dead
2555: * or prevalence in state 1, prevalence in state 2, 0
2556: * newm is the matrix after multiplications, its rows are identical at a factor.
2557: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2558: * Output is prlim.
2559: * Initial matrix pimij
2560: */
1.206 brouard 2561: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2562: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2563: /* 0, 0 , 1} */
2564: /*
2565: * and after some iteration: */
2566: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2567: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2568: /* 0, 0 , 1} */
2569: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2570: /* {0.51571254859325999, 0.4842874514067399, */
2571: /* 0.51326036147820708, 0.48673963852179264} */
2572: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2573:
1.126 brouard 2574: int i, ii,j,k;
1.209 brouard 2575: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2576: /* double **matprod2(); */ /* test */
1.218 brouard 2577: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2578: double **newm;
1.209 brouard 2579: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2580: int ncvloop=0;
1.288 ! brouard 2581: int first=0;
1.169 brouard 2582:
1.209 brouard 2583: min=vector(1,nlstate);
2584: max=vector(1,nlstate);
2585: meandiff=vector(1,nlstate);
2586:
1.218 brouard 2587: /* Starting with matrix unity */
1.126 brouard 2588: for (ii=1;ii<=nlstate+ndeath;ii++)
2589: for (j=1;j<=nlstate+ndeath;j++){
2590: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2591: }
1.169 brouard 2592:
2593: cov[1]=1.;
2594:
2595: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2596: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2597: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2598: ncvloop++;
1.126 brouard 2599: newm=savm;
2600: /* Covariates have to be included here again */
1.138 brouard 2601: cov[2]=agefin;
1.187 brouard 2602: if(nagesqr==1)
2603: cov[3]= agefin*agefin;;
1.234 brouard 2604: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2605: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2606: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2607: /* 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 2608: }
2609: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2610: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2611: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2612: /* 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 2613: }
1.237 brouard 2614: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2615: if(Dummy[Tvar[Tage[k]]]){
2616: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2617: } else{
1.235 brouard 2618: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2619: }
1.235 brouard 2620: /* 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 2621: }
1.237 brouard 2622: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2623: /* 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 2624: if(Dummy[Tvard[k][1]==0]){
2625: if(Dummy[Tvard[k][2]==0]){
2626: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2627: }else{
2628: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2629: }
2630: }else{
2631: if(Dummy[Tvard[k][2]==0]){
2632: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2633: }else{
2634: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2635: }
2636: }
1.234 brouard 2637: }
1.138 brouard 2638: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2639: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2640: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2641: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2642: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2643: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2644: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2645:
1.126 brouard 2646: savm=oldm;
2647: oldm=newm;
1.209 brouard 2648:
2649: for(j=1; j<=nlstate; j++){
2650: max[j]=0.;
2651: min[j]=1.;
2652: }
2653: for(i=1;i<=nlstate;i++){
2654: sumnew=0;
2655: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2656: for(j=1; j<=nlstate; j++){
2657: prlim[i][j]= newm[i][j]/(1-sumnew);
2658: max[j]=FMAX(max[j],prlim[i][j]);
2659: min[j]=FMIN(min[j],prlim[i][j]);
2660: }
2661: }
2662:
1.126 brouard 2663: maxmax=0.;
1.209 brouard 2664: for(j=1; j<=nlstate; j++){
2665: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2666: maxmax=FMAX(maxmax,meandiff[j]);
2667: /* 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 2668: } /* j loop */
1.203 brouard 2669: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2670: /* 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 2671: if(maxmax < ftolpl){
1.209 brouard 2672: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2673: free_vector(min,1,nlstate);
2674: free_vector(max,1,nlstate);
2675: free_vector(meandiff,1,nlstate);
1.126 brouard 2676: return prlim;
2677: }
1.288 ! brouard 2678: } /* agefin loop */
1.208 brouard 2679: /* After some age loop it doesn't converge */
1.288 ! brouard 2680: if(!first){
! 2681: first=1;
! 2682: printf("Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d). Others in log file only...\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax);
! 2683: }
! 2684: fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax);
! 2685:
1.209 brouard 2686: /* 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); */
2687: free_vector(min,1,nlstate);
2688: free_vector(max,1,nlstate);
2689: free_vector(meandiff,1,nlstate);
1.208 brouard 2690:
1.169 brouard 2691: return prlim; /* should not reach here */
1.126 brouard 2692: }
2693:
1.217 brouard 2694:
2695: /**** Back Prevalence limit (stable or period prevalence) ****************/
2696:
1.218 brouard 2697: /* 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) */
2698: /* 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 2699: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2700: {
1.264 brouard 2701: /* 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 2702: matrix by transitions matrix until convergence is reached with precision ftolpl */
2703: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2704: /* Wx is row vector: population in state 1, population in state 2, population dead */
2705: /* or prevalence in state 1, prevalence in state 2, 0 */
2706: /* newm is the matrix after multiplications, its rows are identical at a factor */
2707: /* Initial matrix pimij */
2708: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2709: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2710: /* 0, 0 , 1} */
2711: /*
2712: * and after some iteration: */
2713: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2714: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2715: /* 0, 0 , 1} */
2716: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2717: /* {0.51571254859325999, 0.4842874514067399, */
2718: /* 0.51326036147820708, 0.48673963852179264} */
2719: /* If we start from prlim again, prlim tends to a constant matrix */
2720:
2721: int i, ii,j,k;
1.247 brouard 2722: int first=0;
1.217 brouard 2723: double *min, *max, *meandiff, maxmax,sumnew=0.;
2724: /* double **matprod2(); */ /* test */
2725: double **out, cov[NCOVMAX+1], **bmij();
2726: double **newm;
1.218 brouard 2727: double **dnewm, **doldm, **dsavm; /* for use */
2728: double **oldm, **savm; /* for use */
2729:
1.217 brouard 2730: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2731: int ncvloop=0;
2732:
2733: min=vector(1,nlstate);
2734: max=vector(1,nlstate);
2735: meandiff=vector(1,nlstate);
2736:
1.266 brouard 2737: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2738: oldm=oldms; savm=savms;
2739:
2740: /* Starting with matrix unity */
2741: for (ii=1;ii<=nlstate+ndeath;ii++)
2742: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2743: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2744: }
2745:
2746: cov[1]=1.;
2747:
2748: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2749: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2750: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 ! brouard 2751: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
! 2752: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2753: ncvloop++;
1.218 brouard 2754: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2755: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2756: /* Covariates have to be included here again */
2757: cov[2]=agefin;
2758: if(nagesqr==1)
2759: cov[3]= agefin*agefin;;
1.242 brouard 2760: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2761: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2762: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2763: /* 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 2764: }
2765: /* for (k=1; k<=cptcovn;k++) { */
2766: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2767: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2768: /* /\* 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])]); *\/ */
2769: /* } */
2770: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2771: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2772: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2773: /* 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]); */
2774: }
2775: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2776: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2777: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2778: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2779: for (k=1; k<=cptcovage;k++){ /* For product with age */
2780: if(Dummy[Tvar[Tage[k]]]){
2781: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2782: } else{
2783: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2784: }
2785: /* 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]); */
2786: }
2787: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2788: /* 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]); */
2789: if(Dummy[Tvard[k][1]==0]){
2790: if(Dummy[Tvard[k][2]==0]){
2791: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2792: }else{
2793: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2794: }
2795: }else{
2796: if(Dummy[Tvard[k][2]==0]){
2797: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2798: }else{
2799: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2800: }
2801: }
1.217 brouard 2802: }
2803:
2804: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2805: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2806: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2807: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2808: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2809: /* ij should be linked to the correct index of cov */
2810: /* age and covariate values ij are in 'cov', but we need to pass
2811: * ij for the observed prevalence at age and status and covariate
2812: * number: prevacurrent[(int)agefin][ii][ij]
2813: */
2814: /* 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 *\/ */
2815: /* 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 *\/ */
2816: 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 2817: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2818: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2819: /* for(i=1; i<=nlstate+ndeath; i++) { */
2820: /* printf("%d newm= ",i); */
2821: /* for(j=1;j<=nlstate+ndeath;j++) { */
2822: /* printf("%f ",newm[i][j]); */
2823: /* } */
2824: /* printf("oldm * "); */
2825: /* for(j=1;j<=nlstate+ndeath;j++) { */
2826: /* printf("%f ",oldm[i][j]); */
2827: /* } */
1.268 brouard 2828: /* printf(" bmmij "); */
1.266 brouard 2829: /* for(j=1;j<=nlstate+ndeath;j++) { */
2830: /* printf("%f ",pmmij[i][j]); */
2831: /* } */
2832: /* printf("\n"); */
2833: /* } */
2834: /* } */
1.217 brouard 2835: savm=oldm;
2836: oldm=newm;
1.266 brouard 2837:
1.217 brouard 2838: for(j=1; j<=nlstate; j++){
2839: max[j]=0.;
2840: min[j]=1.;
2841: }
2842: for(j=1; j<=nlstate; j++){
2843: for(i=1;i<=nlstate;i++){
1.234 brouard 2844: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2845: bprlim[i][j]= newm[i][j];
2846: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2847: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2848: }
2849: }
1.218 brouard 2850:
1.217 brouard 2851: maxmax=0.;
2852: for(i=1; i<=nlstate; i++){
2853: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2854: maxmax=FMAX(maxmax,meandiff[i]);
2855: /* 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 2856: } /* i loop */
1.217 brouard 2857: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 2858: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2859: if(maxmax < ftolpl){
1.220 brouard 2860: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2861: free_vector(min,1,nlstate);
2862: free_vector(max,1,nlstate);
2863: free_vector(meandiff,1,nlstate);
2864: return bprlim;
2865: }
1.288 ! brouard 2866: } /* agefin loop */
1.217 brouard 2867: /* After some age loop it doesn't converge */
1.288 ! brouard 2868: if(!first){
1.247 brouard 2869: first=1;
2870: 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\
2871: 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);
2872: }
2873: 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 2874: Oldest age to start was %d-%d=%d, ncvloop=%d, ncvyear=%d\n", (int)age, maxmax, ftolpl, delaymax, (int)age, (int)delaymax, (int)agefin, ncvloop, *ncvyear);
2875: /* 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); */
2876: free_vector(min,1,nlstate);
2877: free_vector(max,1,nlstate);
2878: free_vector(meandiff,1,nlstate);
2879:
2880: return bprlim; /* should not reach here */
2881: }
2882:
1.126 brouard 2883: /*************** transition probabilities ***************/
2884:
2885: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2886: {
1.138 brouard 2887: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2888: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2889: model to the ncovmodel covariates (including constant and age).
2890: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2891: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2892: ncth covariate in the global vector x is given by the formula:
2893: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2894: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2895: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2896: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 2897: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 2898: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 2899: Sum on j ps[i][j] should equal to 1.
1.138 brouard 2900: */
2901: double s1, lnpijopii;
1.126 brouard 2902: /*double t34;*/
1.164 brouard 2903: int i,j, nc, ii, jj;
1.126 brouard 2904:
1.223 brouard 2905: for(i=1; i<= nlstate; i++){
2906: for(j=1; j<i;j++){
2907: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2908: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2909: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2910: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2911: }
2912: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2913: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2914: }
2915: for(j=i+1; j<=nlstate+ndeath;j++){
2916: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2917: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2918: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2919: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2920: }
2921: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2922: }
2923: }
1.218 brouard 2924:
1.223 brouard 2925: for(i=1; i<= nlstate; i++){
2926: s1=0;
2927: for(j=1; j<i; j++){
2928: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2929: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2930: }
2931: for(j=i+1; j<=nlstate+ndeath; j++){
2932: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2933: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2934: }
2935: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2936: ps[i][i]=1./(s1+1.);
2937: /* Computing other pijs */
2938: for(j=1; j<i; j++)
2939: ps[i][j]= exp(ps[i][j])*ps[i][i];
2940: for(j=i+1; j<=nlstate+ndeath; j++)
2941: ps[i][j]= exp(ps[i][j])*ps[i][i];
2942: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2943: } /* end i */
1.218 brouard 2944:
1.223 brouard 2945: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2946: for(jj=1; jj<= nlstate+ndeath; jj++){
2947: ps[ii][jj]=0;
2948: ps[ii][ii]=1;
2949: }
2950: }
1.218 brouard 2951:
2952:
1.223 brouard 2953: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2954: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2955: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2956: /* } */
2957: /* printf("\n "); */
2958: /* } */
2959: /* printf("\n ");printf("%lf ",cov[2]);*/
2960: /*
2961: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2962: goto end;*/
1.266 brouard 2963: return ps; /* Pointer is unchanged since its call */
1.126 brouard 2964: }
2965:
1.218 brouard 2966: /*************** backward transition probabilities ***************/
2967:
2968: /* 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 ) */
2969: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2970: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
2971: {
1.266 brouard 2972: /* Computes the backward probability at age agefin and covariate combination ij. In fact cov is already filled and x too.
2973: * 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 2974: */
1.218 brouard 2975: int i, ii, j,k;
1.222 brouard 2976:
2977: double **out, **pmij();
2978: double sumnew=0.;
1.218 brouard 2979: double agefin;
1.268 brouard 2980: 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 2981: double **dnewm, **dsavm, **doldm;
2982: double **bbmij;
2983:
1.218 brouard 2984: doldm=ddoldms; /* global pointers */
1.222 brouard 2985: dnewm=ddnewms;
2986: dsavm=ddsavms;
2987:
2988: agefin=cov[2];
1.268 brouard 2989: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 2990: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 2991: the observed prevalence (with this covariate ij) at beginning of transition */
2992: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 2993:
2994: /* P_x */
1.266 brouard 2995: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 2996: /* outputs pmmij which is a stochastic matrix in row */
2997:
2998: /* Diag(w_x) */
2999: /* Problem with prevacurrent which can be zero */
3000: sumnew=0.;
1.269 brouard 3001: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3002: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.269 brouard 3003: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3004: sumnew+=prevacurrent[(int)agefin][ii][ij];
3005: }
3006: if(sumnew >0.01){ /* At least some value in the prevalence */
3007: for (ii=1;ii<=nlstate+ndeath;ii++){
3008: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3009: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3010: }
3011: }else{
3012: for (ii=1;ii<=nlstate+ndeath;ii++){
3013: for (j=1;j<=nlstate+ndeath;j++)
3014: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3015: }
3016: /* if(sumnew <0.9){ */
3017: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3018: /* } */
3019: }
3020: k3=0.0; /* We put the last diagonal to 0 */
3021: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3022: doldm[ii][ii]= k3;
3023: }
3024: /* End doldm, At the end doldm is diag[(w_i)] */
3025:
3026: /* left Product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm) */
3027: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* Bug Valgrind */
3028:
3029: /* Diag(Sum_i w^i_x p^ij_x */
3030: /* 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 3031: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3032: sumnew=0.;
1.222 brouard 3033: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3034: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3035: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3036: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3037: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3038: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3039: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3040: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3041: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3042: /* }else */
1.268 brouard 3043: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3044: } /*End ii */
3045: } /* 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 */
3046:
3047: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* Bug Valgrind */
3048: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3049: /* end bmij */
1.266 brouard 3050: return ps; /*pointer is unchanged */
1.218 brouard 3051: }
1.217 brouard 3052: /*************** transition probabilities ***************/
3053:
1.218 brouard 3054: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3055: {
3056: /* According to parameters values stored in x and the covariate's values stored in cov,
3057: computes the probability to be observed in state j being in state i by appying the
3058: model to the ncovmodel covariates (including constant and age).
3059: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3060: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3061: ncth covariate in the global vector x is given by the formula:
3062: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3063: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3064: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3065: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3066: Outputs ps[i][j] the probability to be observed in j being in j according to
3067: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3068: */
3069: double s1, lnpijopii;
3070: /*double t34;*/
3071: int i,j, nc, ii, jj;
3072:
1.234 brouard 3073: for(i=1; i<= nlstate; i++){
3074: for(j=1; j<i;j++){
3075: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3076: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3077: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3078: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3079: }
3080: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3081: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3082: }
3083: for(j=i+1; j<=nlstate+ndeath;j++){
3084: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3085: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3086: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3087: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3088: }
3089: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3090: }
3091: }
3092:
3093: for(i=1; i<= nlstate; i++){
3094: s1=0;
3095: for(j=1; j<i; j++){
3096: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3097: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3098: }
3099: for(j=i+1; j<=nlstate+ndeath; j++){
3100: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3101: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3102: }
3103: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3104: ps[i][i]=1./(s1+1.);
3105: /* Computing other pijs */
3106: for(j=1; j<i; j++)
3107: ps[i][j]= exp(ps[i][j])*ps[i][i];
3108: for(j=i+1; j<=nlstate+ndeath; j++)
3109: ps[i][j]= exp(ps[i][j])*ps[i][i];
3110: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3111: } /* end i */
3112:
3113: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3114: for(jj=1; jj<= nlstate+ndeath; jj++){
3115: ps[ii][jj]=0;
3116: ps[ii][ii]=1;
3117: }
3118: }
3119: /* Added for backcast */ /* Transposed matrix too */
3120: for(jj=1; jj<= nlstate+ndeath; jj++){
3121: s1=0.;
3122: for(ii=1; ii<= nlstate+ndeath; ii++){
3123: s1+=ps[ii][jj];
3124: }
3125: for(ii=1; ii<= nlstate; ii++){
3126: ps[ii][jj]=ps[ii][jj]/s1;
3127: }
3128: }
3129: /* Transposition */
3130: for(jj=1; jj<= nlstate+ndeath; jj++){
3131: for(ii=jj; ii<= nlstate+ndeath; ii++){
3132: s1=ps[ii][jj];
3133: ps[ii][jj]=ps[jj][ii];
3134: ps[jj][ii]=s1;
3135: }
3136: }
3137: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3138: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3139: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3140: /* } */
3141: /* printf("\n "); */
3142: /* } */
3143: /* printf("\n ");printf("%lf ",cov[2]);*/
3144: /*
3145: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3146: goto end;*/
3147: return ps;
1.217 brouard 3148: }
3149:
3150:
1.126 brouard 3151: /**************** Product of 2 matrices ******************/
3152:
1.145 brouard 3153: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3154: {
3155: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3156: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3157: /* in, b, out are matrice of pointers which should have been initialized
3158: before: only the contents of out is modified. The function returns
3159: a pointer to pointers identical to out */
1.145 brouard 3160: int i, j, k;
1.126 brouard 3161: for(i=nrl; i<= nrh; i++)
1.145 brouard 3162: for(k=ncolol; k<=ncoloh; k++){
3163: out[i][k]=0.;
3164: for(j=ncl; j<=nch; j++)
3165: out[i][k] +=in[i][j]*b[j][k];
3166: }
1.126 brouard 3167: return out;
3168: }
3169:
3170:
3171: /************* Higher Matrix Product ***************/
3172:
1.235 brouard 3173: 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 3174: {
1.218 brouard 3175: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3176: 'nhstepm*hstepm*stepm' months (i.e. until
3177: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3178: nhstepm*hstepm matrices.
3179: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3180: (typically every 2 years instead of every month which is too big
3181: for the memory).
3182: Model is determined by parameters x and covariates have to be
3183: included manually here.
3184:
3185: */
3186:
3187: int i, j, d, h, k;
1.131 brouard 3188: double **out, cov[NCOVMAX+1];
1.126 brouard 3189: double **newm;
1.187 brouard 3190: double agexact;
1.214 brouard 3191: double agebegin, ageend;
1.126 brouard 3192:
3193: /* Hstepm could be zero and should return the unit matrix */
3194: for (i=1;i<=nlstate+ndeath;i++)
3195: for (j=1;j<=nlstate+ndeath;j++){
3196: oldm[i][j]=(i==j ? 1.0 : 0.0);
3197: po[i][j][0]=(i==j ? 1.0 : 0.0);
3198: }
3199: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3200: for(h=1; h <=nhstepm; h++){
3201: for(d=1; d <=hstepm; d++){
3202: newm=savm;
3203: /* Covariates have to be included here again */
3204: cov[1]=1.;
1.214 brouard 3205: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3206: cov[2]=agexact;
3207: if(nagesqr==1)
1.227 brouard 3208: cov[3]= agexact*agexact;
1.235 brouard 3209: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3210: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3211: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3212: /* 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)); */
3213: }
3214: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3215: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3216: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3217: /* 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]); */
3218: }
3219: for (k=1; k<=cptcovage;k++){
3220: if(Dummy[Tvar[Tage[k]]]){
3221: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3222: } else{
3223: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3224: }
3225: /* 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]); */
3226: }
3227: for (k=1; k<=cptcovprod;k++){ /* */
3228: /* 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]); */
3229: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3230: }
3231: /* for (k=1; k<=cptcovn;k++) */
3232: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3233: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3234: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3235: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3236: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3237:
3238:
1.126 brouard 3239: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3240: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3241: /* right multiplication of oldm by the current matrix */
1.126 brouard 3242: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3243: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3244: /* if((int)age == 70){ */
3245: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3246: /* for(i=1; i<=nlstate+ndeath; i++) { */
3247: /* printf("%d pmmij ",i); */
3248: /* for(j=1;j<=nlstate+ndeath;j++) { */
3249: /* printf("%f ",pmmij[i][j]); */
3250: /* } */
3251: /* printf(" oldm "); */
3252: /* for(j=1;j<=nlstate+ndeath;j++) { */
3253: /* printf("%f ",oldm[i][j]); */
3254: /* } */
3255: /* printf("\n"); */
3256: /* } */
3257: /* } */
1.126 brouard 3258: savm=oldm;
3259: oldm=newm;
3260: }
3261: for(i=1; i<=nlstate+ndeath; i++)
3262: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3263: po[i][j][h]=newm[i][j];
3264: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3265: }
1.128 brouard 3266: /*printf("h=%d ",h);*/
1.126 brouard 3267: } /* end h */
1.267 brouard 3268: /* printf("\n H=%d \n",h); */
1.126 brouard 3269: return po;
3270: }
3271:
1.217 brouard 3272: /************* Higher Back Matrix Product ***************/
1.218 brouard 3273: /* 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 3274: 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 3275: {
1.266 brouard 3276: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3277: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3278: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3279: nhstepm*hstepm matrices.
3280: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3281: (typically every 2 years instead of every month which is too big
1.217 brouard 3282: for the memory).
1.218 brouard 3283: Model is determined by parameters x and covariates have to be
1.266 brouard 3284: included manually here. Then we use a call to bmij(x and cov)
3285: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3286: */
1.217 brouard 3287:
3288: int i, j, d, h, k;
1.266 brouard 3289: double **out, cov[NCOVMAX+1], **bmij();
3290: double **newm, ***newmm;
1.217 brouard 3291: double agexact;
3292: double agebegin, ageend;
1.222 brouard 3293: double **oldm, **savm;
1.217 brouard 3294:
1.266 brouard 3295: newmm=po; /* To be saved */
3296: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3297: /* Hstepm could be zero and should return the unit matrix */
3298: for (i=1;i<=nlstate+ndeath;i++)
3299: for (j=1;j<=nlstate+ndeath;j++){
3300: oldm[i][j]=(i==j ? 1.0 : 0.0);
3301: po[i][j][0]=(i==j ? 1.0 : 0.0);
3302: }
3303: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3304: for(h=1; h <=nhstepm; h++){
3305: for(d=1; d <=hstepm; d++){
3306: newm=savm;
3307: /* Covariates have to be included here again */
3308: cov[1]=1.;
1.271 brouard 3309: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3310: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3311: cov[2]=agexact;
3312: if(nagesqr==1)
1.222 brouard 3313: cov[3]= agexact*agexact;
1.266 brouard 3314: for (k=1; k<=cptcovn;k++){
3315: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3316: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3317: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3318: /* 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)); */
3319: }
1.267 brouard 3320: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3321: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3322: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3323: /* 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]); */
3324: }
3325: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3326: if(Dummy[Tvar[Tage[k]]]){
3327: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3328: } else{
3329: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3330: }
3331: /* 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]); */
3332: }
3333: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3334: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3335: }
1.217 brouard 3336: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3337: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3338:
1.218 brouard 3339: /* Careful transposed matrix */
1.266 brouard 3340: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3341: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3342: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3343: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3344: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3345: /* if((int)age == 70){ */
3346: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3347: /* for(i=1; i<=nlstate+ndeath; i++) { */
3348: /* printf("%d pmmij ",i); */
3349: /* for(j=1;j<=nlstate+ndeath;j++) { */
3350: /* printf("%f ",pmmij[i][j]); */
3351: /* } */
3352: /* printf(" oldm "); */
3353: /* for(j=1;j<=nlstate+ndeath;j++) { */
3354: /* printf("%f ",oldm[i][j]); */
3355: /* } */
3356: /* printf("\n"); */
3357: /* } */
3358: /* } */
3359: savm=oldm;
3360: oldm=newm;
3361: }
3362: for(i=1; i<=nlstate+ndeath; i++)
3363: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3364: po[i][j][h]=newm[i][j];
1.268 brouard 3365: /* if(h==nhstepm) */
3366: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3367: }
1.268 brouard 3368: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3369: } /* end h */
1.268 brouard 3370: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3371: return po;
3372: }
3373:
3374:
1.162 brouard 3375: #ifdef NLOPT
3376: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3377: double fret;
3378: double *xt;
3379: int j;
3380: myfunc_data *d2 = (myfunc_data *) pd;
3381: /* xt = (p1-1); */
3382: xt=vector(1,n);
3383: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3384:
3385: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3386: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3387: printf("Function = %.12lf ",fret);
3388: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3389: printf("\n");
3390: free_vector(xt,1,n);
3391: return fret;
3392: }
3393: #endif
1.126 brouard 3394:
3395: /*************** log-likelihood *************/
3396: double func( double *x)
3397: {
1.226 brouard 3398: int i, ii, j, k, mi, d, kk;
3399: int ioffset=0;
3400: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3401: double **out;
3402: double lli; /* Individual log likelihood */
3403: int s1, s2;
1.228 brouard 3404: 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 3405: double bbh, survp;
3406: long ipmx;
3407: double agexact;
3408: /*extern weight */
3409: /* We are differentiating ll according to initial status */
3410: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3411: /*for(i=1;i<imx;i++)
3412: printf(" %d\n",s[4][i]);
3413: */
1.162 brouard 3414:
1.226 brouard 3415: ++countcallfunc;
1.162 brouard 3416:
1.226 brouard 3417: cov[1]=1.;
1.126 brouard 3418:
1.226 brouard 3419: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3420: ioffset=0;
1.226 brouard 3421: if(mle==1){
3422: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3423: /* Computes the values of the ncovmodel covariates of the model
3424: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3425: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3426: to be observed in j being in i according to the model.
3427: */
1.243 brouard 3428: ioffset=2+nagesqr ;
1.233 brouard 3429: /* Fixed */
1.234 brouard 3430: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3431: 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)*/
3432: }
1.226 brouard 3433: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3434: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3435: has been calculated etc */
3436: /* For an individual i, wav[i] gives the number of effective waves */
3437: /* We compute the contribution to Likelihood of each effective transition
3438: mw[mi][i] is real wave of the mi th effectve wave */
3439: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3440: s2=s[mw[mi+1][i]][i];
3441: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3442: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3443: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3444: */
3445: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3446: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3447: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3448: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3449: }
3450: for (ii=1;ii<=nlstate+ndeath;ii++)
3451: for (j=1;j<=nlstate+ndeath;j++){
3452: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3453: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3454: }
3455: for(d=0; d<dh[mi][i]; d++){
3456: newm=savm;
3457: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3458: cov[2]=agexact;
3459: if(nagesqr==1)
3460: cov[3]= agexact*agexact; /* Should be changed here */
3461: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3462: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3463: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3464: else
3465: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3466: }
3467: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3468: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3469: savm=oldm;
3470: oldm=newm;
3471: } /* end mult */
3472:
3473: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3474: /* But now since version 0.9 we anticipate for bias at large stepm.
3475: * If stepm is larger than one month (smallest stepm) and if the exact delay
3476: * (in months) between two waves is not a multiple of stepm, we rounded to
3477: * the nearest (and in case of equal distance, to the lowest) interval but now
3478: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3479: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3480: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3481: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3482: * -stepm/2 to stepm/2 .
3483: * For stepm=1 the results are the same as for previous versions of Imach.
3484: * For stepm > 1 the results are less biased than in previous versions.
3485: */
1.234 brouard 3486: s1=s[mw[mi][i]][i];
3487: s2=s[mw[mi+1][i]][i];
3488: bbh=(double)bh[mi][i]/(double)stepm;
3489: /* bias bh is positive if real duration
3490: * is higher than the multiple of stepm and negative otherwise.
3491: */
3492: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3493: if( s2 > nlstate){
3494: /* i.e. if s2 is a death state and if the date of death is known
3495: then the contribution to the likelihood is the probability to
3496: die between last step unit time and current step unit time,
3497: which is also equal to probability to die before dh
3498: minus probability to die before dh-stepm .
3499: In version up to 0.92 likelihood was computed
3500: as if date of death was unknown. Death was treated as any other
3501: health state: the date of the interview describes the actual state
3502: and not the date of a change in health state. The former idea was
3503: to consider that at each interview the state was recorded
3504: (healthy, disable or death) and IMaCh was corrected; but when we
3505: introduced the exact date of death then we should have modified
3506: the contribution of an exact death to the likelihood. This new
3507: contribution is smaller and very dependent of the step unit
3508: stepm. It is no more the probability to die between last interview
3509: and month of death but the probability to survive from last
3510: interview up to one month before death multiplied by the
3511: probability to die within a month. Thanks to Chris
3512: Jackson for correcting this bug. Former versions increased
3513: mortality artificially. The bad side is that we add another loop
3514: which slows down the processing. The difference can be up to 10%
3515: lower mortality.
3516: */
3517: /* If, at the beginning of the maximization mostly, the
3518: cumulative probability or probability to be dead is
3519: constant (ie = 1) over time d, the difference is equal to
3520: 0. out[s1][3] = savm[s1][3]: probability, being at state
3521: s1 at precedent wave, to be dead a month before current
3522: wave is equal to probability, being at state s1 at
3523: precedent wave, to be dead at mont of the current
3524: wave. Then the observed probability (that this person died)
3525: is null according to current estimated parameter. In fact,
3526: it should be very low but not zero otherwise the log go to
3527: infinity.
3528: */
1.183 brouard 3529: /* #ifdef INFINITYORIGINAL */
3530: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3531: /* #else */
3532: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3533: /* lli=log(mytinydouble); */
3534: /* else */
3535: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3536: /* #endif */
1.226 brouard 3537: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3538:
1.226 brouard 3539: } else if ( s2==-1 ) { /* alive */
3540: for (j=1,survp=0. ; j<=nlstate; j++)
3541: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3542: /*survp += out[s1][j]; */
3543: lli= log(survp);
3544: }
3545: else if (s2==-4) {
3546: for (j=3,survp=0. ; j<=nlstate; j++)
3547: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3548: lli= log(survp);
3549: }
3550: else if (s2==-5) {
3551: for (j=1,survp=0. ; j<=2; j++)
3552: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3553: lli= log(survp);
3554: }
3555: else{
3556: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3557: /* 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 */
3558: }
3559: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3560: /*if(lli ==000.0)*/
3561: /*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); */
3562: ipmx +=1;
3563: sw += weight[i];
3564: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3565: /* if (lli < log(mytinydouble)){ */
3566: /* 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); */
3567: /* 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]); */
3568: /* } */
3569: } /* end of wave */
3570: } /* end of individual */
3571: } else if(mle==2){
3572: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3573: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3574: for(mi=1; mi<= wav[i]-1; mi++){
3575: for (ii=1;ii<=nlstate+ndeath;ii++)
3576: for (j=1;j<=nlstate+ndeath;j++){
3577: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3578: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3579: }
3580: for(d=0; d<=dh[mi][i]; d++){
3581: newm=savm;
3582: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3583: cov[2]=agexact;
3584: if(nagesqr==1)
3585: cov[3]= agexact*agexact;
3586: for (kk=1; kk<=cptcovage;kk++) {
3587: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3588: }
3589: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3590: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3591: savm=oldm;
3592: oldm=newm;
3593: } /* end mult */
3594:
3595: s1=s[mw[mi][i]][i];
3596: s2=s[mw[mi+1][i]][i];
3597: bbh=(double)bh[mi][i]/(double)stepm;
3598: 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 */
3599: ipmx +=1;
3600: sw += weight[i];
3601: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3602: } /* end of wave */
3603: } /* end of individual */
3604: } else if(mle==3){ /* exponential inter-extrapolation */
3605: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3606: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3607: for(mi=1; mi<= wav[i]-1; mi++){
3608: for (ii=1;ii<=nlstate+ndeath;ii++)
3609: for (j=1;j<=nlstate+ndeath;j++){
3610: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3611: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3612: }
3613: for(d=0; d<dh[mi][i]; d++){
3614: newm=savm;
3615: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3616: cov[2]=agexact;
3617: if(nagesqr==1)
3618: cov[3]= agexact*agexact;
3619: for (kk=1; kk<=cptcovage;kk++) {
3620: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3621: }
3622: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3623: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3624: savm=oldm;
3625: oldm=newm;
3626: } /* end mult */
3627:
3628: s1=s[mw[mi][i]][i];
3629: s2=s[mw[mi+1][i]][i];
3630: bbh=(double)bh[mi][i]/(double)stepm;
3631: 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 */
3632: ipmx +=1;
3633: sw += weight[i];
3634: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3635: } /* end of wave */
3636: } /* end of individual */
3637: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3638: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3639: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3640: for(mi=1; mi<= wav[i]-1; mi++){
3641: for (ii=1;ii<=nlstate+ndeath;ii++)
3642: for (j=1;j<=nlstate+ndeath;j++){
3643: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3644: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3645: }
3646: for(d=0; d<dh[mi][i]; d++){
3647: newm=savm;
3648: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3649: cov[2]=agexact;
3650: if(nagesqr==1)
3651: cov[3]= agexact*agexact;
3652: for (kk=1; kk<=cptcovage;kk++) {
3653: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3654: }
1.126 brouard 3655:
1.226 brouard 3656: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3657: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3658: savm=oldm;
3659: oldm=newm;
3660: } /* end mult */
3661:
3662: s1=s[mw[mi][i]][i];
3663: s2=s[mw[mi+1][i]][i];
3664: if( s2 > nlstate){
3665: lli=log(out[s1][s2] - savm[s1][s2]);
3666: } else if ( s2==-1 ) { /* alive */
3667: for (j=1,survp=0. ; j<=nlstate; j++)
3668: survp += out[s1][j];
3669: lli= log(survp);
3670: }else{
3671: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3672: }
3673: ipmx +=1;
3674: sw += weight[i];
3675: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3676: /* 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 3677: } /* end of wave */
3678: } /* end of individual */
3679: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3680: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3681: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3682: for(mi=1; mi<= wav[i]-1; mi++){
3683: for (ii=1;ii<=nlstate+ndeath;ii++)
3684: for (j=1;j<=nlstate+ndeath;j++){
3685: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3686: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3687: }
3688: for(d=0; d<dh[mi][i]; d++){
3689: newm=savm;
3690: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3691: cov[2]=agexact;
3692: if(nagesqr==1)
3693: cov[3]= agexact*agexact;
3694: for (kk=1; kk<=cptcovage;kk++) {
3695: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3696: }
1.126 brouard 3697:
1.226 brouard 3698: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3699: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3700: savm=oldm;
3701: oldm=newm;
3702: } /* end mult */
3703:
3704: s1=s[mw[mi][i]][i];
3705: s2=s[mw[mi+1][i]][i];
3706: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3707: ipmx +=1;
3708: sw += weight[i];
3709: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3710: /*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]);*/
3711: } /* end of wave */
3712: } /* end of individual */
3713: } /* End of if */
3714: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3715: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3716: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3717: return -l;
1.126 brouard 3718: }
3719:
3720: /*************** log-likelihood *************/
3721: double funcone( double *x)
3722: {
1.228 brouard 3723: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3724: int i, ii, j, k, mi, d, kk;
1.228 brouard 3725: int ioffset=0;
1.131 brouard 3726: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3727: double **out;
3728: double lli; /* Individual log likelihood */
3729: double llt;
3730: int s1, s2;
1.228 brouard 3731: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3732:
1.126 brouard 3733: double bbh, survp;
1.187 brouard 3734: double agexact;
1.214 brouard 3735: double agebegin, ageend;
1.126 brouard 3736: /*extern weight */
3737: /* We are differentiating ll according to initial status */
3738: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3739: /*for(i=1;i<imx;i++)
3740: printf(" %d\n",s[4][i]);
3741: */
3742: cov[1]=1.;
3743:
3744: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3745: ioffset=0;
3746: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3747: /* ioffset=2+nagesqr+cptcovage; */
3748: ioffset=2+nagesqr;
1.232 brouard 3749: /* Fixed */
1.224 brouard 3750: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3751: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3752: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3753: 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)*/
3754: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3755: /* cov[2+6]=covar[Tvar[6]][i]; */
3756: /* cov[2+6]=covar[2][i]; V2 */
3757: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3758: /* cov[2+7]=covar[Tvar[7]][i]; */
3759: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3760: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3761: /* cov[2+9]=covar[Tvar[9]][i]; */
3762: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3763: }
1.232 brouard 3764: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3765: /* 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?)*\/ */
3766: /* } */
1.231 brouard 3767: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3768: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3769: /* } */
1.225 brouard 3770:
1.233 brouard 3771:
3772: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3773: /* Wave varying (but not age varying) */
3774: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3775: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3776: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3777: }
1.232 brouard 3778: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3779: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3780: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3781: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3782: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3783: /* 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 3784: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3785: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3786: /* /\* 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]); *\/ */
3787: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3788: /* } */
1.126 brouard 3789: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3790: for (j=1;j<=nlstate+ndeath;j++){
3791: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3792: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3793: }
1.214 brouard 3794:
3795: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3796: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3797: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3798: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3799: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3800: and mw[mi+1][i]. dh depends on stepm.*/
3801: newm=savm;
1.247 brouard 3802: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3803: cov[2]=agexact;
3804: if(nagesqr==1)
3805: cov[3]= agexact*agexact;
3806: for (kk=1; kk<=cptcovage;kk++) {
3807: if(!FixedV[Tvar[Tage[kk]]])
3808: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3809: else
3810: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3811: }
3812: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3813: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3814: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3815: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3816: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3817: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3818: savm=oldm;
3819: oldm=newm;
1.126 brouard 3820: } /* end mult */
3821:
3822: s1=s[mw[mi][i]][i];
3823: s2=s[mw[mi+1][i]][i];
1.217 brouard 3824: /* if(s2==-1){ */
1.268 brouard 3825: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3826: /* /\* exit(1); *\/ */
3827: /* } */
1.126 brouard 3828: bbh=(double)bh[mi][i]/(double)stepm;
3829: /* bias is positive if real duration
3830: * is higher than the multiple of stepm and negative otherwise.
3831: */
3832: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3833: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3834: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3835: for (j=1,survp=0. ; j<=nlstate; j++)
3836: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3837: lli= log(survp);
1.126 brouard 3838: }else if (mle==1){
1.242 brouard 3839: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3840: } else if(mle==2){
1.242 brouard 3841: 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 3842: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3843: 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 3844: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3845: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3846: } else{ /* mle=0 back to 1 */
1.242 brouard 3847: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3848: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3849: } /* End of if */
3850: ipmx +=1;
3851: sw += weight[i];
3852: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3853: /*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 3854: if(globpr){
1.246 brouard 3855: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3856: %11.6f %11.6f %11.6f ", \
1.242 brouard 3857: 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 3858: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3859: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3860: llt +=ll[k]*gipmx/gsw;
3861: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3862: }
3863: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3864: }
1.232 brouard 3865: } /* end of wave */
3866: } /* end of individual */
3867: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3868: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3869: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3870: if(globpr==0){ /* First time we count the contributions and weights */
3871: gipmx=ipmx;
3872: gsw=sw;
3873: }
3874: return -l;
1.126 brouard 3875: }
3876:
3877:
3878: /*************** function likelione ***********/
3879: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*funcone)(double []))
3880: {
3881: /* This routine should help understanding what is done with
3882: the selection of individuals/waves and
3883: to check the exact contribution to the likelihood.
3884: Plotting could be done.
3885: */
3886: int k;
3887:
3888: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3889: strcpy(fileresilk,"ILK_");
1.202 brouard 3890: strcat(fileresilk,fileresu);
1.126 brouard 3891: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3892: printf("Problem with resultfile: %s\n", fileresilk);
3893: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3894: }
1.214 brouard 3895: 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");
3896: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3897: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3898: for(k=1; k<=nlstate; k++)
3899: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3900: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3901: }
3902:
3903: *fretone=(*funcone)(p);
3904: if(*globpri !=0){
3905: fclose(ficresilk);
1.205 brouard 3906: if (mle ==0)
3907: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3908: else if(mle >=1)
3909: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3910: 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 3911: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 3912:
3913: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3914: 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 3915: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3916: }
1.207 brouard 3917: 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 3918: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3919: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3920: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3921: fflush(fichtm);
1.205 brouard 3922: }
1.126 brouard 3923: return;
3924: }
3925:
3926:
3927: /*********** Maximum Likelihood Estimation ***************/
3928:
3929: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3930: {
1.165 brouard 3931: int i,j, iter=0;
1.126 brouard 3932: double **xi;
3933: double fret;
3934: double fretone; /* Only one call to likelihood */
3935: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3936:
3937: #ifdef NLOPT
3938: int creturn;
3939: nlopt_opt opt;
3940: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3941: double *lb;
3942: double minf; /* the minimum objective value, upon return */
3943: double * p1; /* Shifted parameters from 0 instead of 1 */
3944: myfunc_data dinst, *d = &dinst;
3945: #endif
3946:
3947:
1.126 brouard 3948: xi=matrix(1,npar,1,npar);
3949: for (i=1;i<=npar;i++)
3950: for (j=1;j<=npar;j++)
3951: xi[i][j]=(i==j ? 1.0 : 0.0);
3952: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3953: strcpy(filerespow,"POW_");
1.126 brouard 3954: strcat(filerespow,fileres);
3955: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3956: printf("Problem with resultfile: %s\n", filerespow);
3957: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3958: }
3959: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3960: for (i=1;i<=nlstate;i++)
3961: for(j=1;j<=nlstate+ndeath;j++)
3962: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3963: fprintf(ficrespow,"\n");
1.162 brouard 3964: #ifdef POWELL
1.126 brouard 3965: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3966: #endif
1.126 brouard 3967:
1.162 brouard 3968: #ifdef NLOPT
3969: #ifdef NEWUOA
3970: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
3971: #else
3972: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
3973: #endif
3974: lb=vector(0,npar-1);
3975: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
3976: nlopt_set_lower_bounds(opt, lb);
3977: nlopt_set_initial_step1(opt, 0.1);
3978:
3979: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
3980: d->function = func;
3981: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
3982: nlopt_set_min_objective(opt, myfunc, d);
3983: nlopt_set_xtol_rel(opt, ftol);
3984: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
3985: printf("nlopt failed! %d\n",creturn);
3986: }
3987: else {
3988: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
3989: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
3990: iter=1; /* not equal */
3991: }
3992: nlopt_destroy(opt);
3993: #endif
1.126 brouard 3994: free_matrix(xi,1,npar,1,npar);
3995: fclose(ficrespow);
1.203 brouard 3996: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
3997: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 3998: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 3999:
4000: }
4001:
4002: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 4003: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 4004: {
4005: double **a,**y,*x,pd;
1.203 brouard 4006: /* double **hess; */
1.164 brouard 4007: int i, j;
1.126 brouard 4008: int *indx;
4009:
4010: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 4011: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 4012: void lubksb(double **a, int npar, int *indx, double b[]) ;
4013: void ludcmp(double **a, int npar, int *indx, double *d) ;
4014: double gompertz(double p[]);
1.203 brouard 4015: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 4016:
4017: printf("\nCalculation of the hessian matrix. Wait...\n");
4018: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
4019: for (i=1;i<=npar;i++){
1.203 brouard 4020: printf("%d-",i);fflush(stdout);
4021: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 4022:
4023: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
4024:
4025: /* printf(" %f ",p[i]);
4026: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
4027: }
4028:
4029: for (i=1;i<=npar;i++) {
4030: for (j=1;j<=npar;j++) {
4031: if (j>i) {
1.203 brouard 4032: printf(".%d-%d",i,j);fflush(stdout);
4033: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
4034: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 4035:
4036: hess[j][i]=hess[i][j];
4037: /*printf(" %lf ",hess[i][j]);*/
4038: }
4039: }
4040: }
4041: printf("\n");
4042: fprintf(ficlog,"\n");
4043:
4044: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
4045: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
4046:
4047: a=matrix(1,npar,1,npar);
4048: y=matrix(1,npar,1,npar);
4049: x=vector(1,npar);
4050: indx=ivector(1,npar);
4051: for (i=1;i<=npar;i++)
4052: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
4053: ludcmp(a,npar,indx,&pd);
4054:
4055: for (j=1;j<=npar;j++) {
4056: for (i=1;i<=npar;i++) x[i]=0;
4057: x[j]=1;
4058: lubksb(a,npar,indx,x);
4059: for (i=1;i<=npar;i++){
4060: matcov[i][j]=x[i];
4061: }
4062: }
4063:
4064: printf("\n#Hessian matrix#\n");
4065: fprintf(ficlog,"\n#Hessian matrix#\n");
4066: for (i=1;i<=npar;i++) {
4067: for (j=1;j<=npar;j++) {
1.203 brouard 4068: printf("%.6e ",hess[i][j]);
4069: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4070: }
4071: printf("\n");
4072: fprintf(ficlog,"\n");
4073: }
4074:
1.203 brouard 4075: /* printf("\n#Covariance matrix#\n"); */
4076: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4077: /* for (i=1;i<=npar;i++) { */
4078: /* for (j=1;j<=npar;j++) { */
4079: /* printf("%.6e ",matcov[i][j]); */
4080: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4081: /* } */
4082: /* printf("\n"); */
4083: /* fprintf(ficlog,"\n"); */
4084: /* } */
4085:
1.126 brouard 4086: /* Recompute Inverse */
1.203 brouard 4087: /* for (i=1;i<=npar;i++) */
4088: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4089: /* ludcmp(a,npar,indx,&pd); */
4090:
4091: /* printf("\n#Hessian matrix recomputed#\n"); */
4092:
4093: /* for (j=1;j<=npar;j++) { */
4094: /* for (i=1;i<=npar;i++) x[i]=0; */
4095: /* x[j]=1; */
4096: /* lubksb(a,npar,indx,x); */
4097: /* for (i=1;i<=npar;i++){ */
4098: /* y[i][j]=x[i]; */
4099: /* printf("%.3e ",y[i][j]); */
4100: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4101: /* } */
4102: /* printf("\n"); */
4103: /* fprintf(ficlog,"\n"); */
4104: /* } */
4105:
4106: /* Verifying the inverse matrix */
4107: #ifdef DEBUGHESS
4108: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4109:
1.203 brouard 4110: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4111: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4112:
4113: for (j=1;j<=npar;j++) {
4114: for (i=1;i<=npar;i++){
1.203 brouard 4115: printf("%.2f ",y[i][j]);
4116: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4117: }
4118: printf("\n");
4119: fprintf(ficlog,"\n");
4120: }
1.203 brouard 4121: #endif
1.126 brouard 4122:
4123: free_matrix(a,1,npar,1,npar);
4124: free_matrix(y,1,npar,1,npar);
4125: free_vector(x,1,npar);
4126: free_ivector(indx,1,npar);
1.203 brouard 4127: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4128:
4129:
4130: }
4131:
4132: /*************** hessian matrix ****************/
4133: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4134: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4135: int i;
4136: int l=1, lmax=20;
1.203 brouard 4137: double k1,k2, res, fx;
1.132 brouard 4138: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4139: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4140: int k=0,kmax=10;
4141: double l1;
4142:
4143: fx=func(x);
4144: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4145: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4146: l1=pow(10,l);
4147: delts=delt;
4148: for(k=1 ; k <kmax; k=k+1){
4149: delt = delta*(l1*k);
4150: p2[theta]=x[theta] +delt;
1.145 brouard 4151: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4152: p2[theta]=x[theta]-delt;
4153: k2=func(p2)-fx;
4154: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4155: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4156:
1.203 brouard 4157: #ifdef DEBUGHESSII
1.126 brouard 4158: 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);
4159: 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);
4160: #endif
4161: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4162: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4163: k=kmax;
4164: }
4165: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4166: k=kmax; l=lmax*10;
1.126 brouard 4167: }
4168: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4169: delts=delt;
4170: }
1.203 brouard 4171: } /* End loop k */
1.126 brouard 4172: }
4173: delti[theta]=delts;
4174: return res;
4175:
4176: }
4177:
1.203 brouard 4178: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4179: {
4180: int i;
1.164 brouard 4181: int l=1, lmax=20;
1.126 brouard 4182: double k1,k2,k3,k4,res,fx;
1.132 brouard 4183: double p2[MAXPARM+1];
1.203 brouard 4184: int k, kmax=1;
4185: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4186:
4187: int firstime=0;
1.203 brouard 4188:
1.126 brouard 4189: fx=func(x);
1.203 brouard 4190: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4191: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4192: p2[thetai]=x[thetai]+delti[thetai]*k;
4193: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4194: k1=func(p2)-fx;
4195:
1.203 brouard 4196: p2[thetai]=x[thetai]+delti[thetai]*k;
4197: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4198: k2=func(p2)-fx;
4199:
1.203 brouard 4200: p2[thetai]=x[thetai]-delti[thetai]*k;
4201: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4202: k3=func(p2)-fx;
4203:
1.203 brouard 4204: p2[thetai]=x[thetai]-delti[thetai]*k;
4205: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4206: k4=func(p2)-fx;
1.203 brouard 4207: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4208: if(k1*k2*k3*k4 <0.){
1.208 brouard 4209: firstime=1;
1.203 brouard 4210: kmax=kmax+10;
1.208 brouard 4211: }
4212: if(kmax >=10 || firstime ==1){
1.246 brouard 4213: 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);
4214: 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 4215: 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);
4216: 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);
4217: }
4218: #ifdef DEBUGHESSIJ
4219: v1=hess[thetai][thetai];
4220: v2=hess[thetaj][thetaj];
4221: cv12=res;
4222: /* Computing eigen value of Hessian matrix */
4223: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4224: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4225: if ((lc2 <0) || (lc1 <0) ){
4226: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4227: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4228: 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);
4229: 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);
4230: }
1.126 brouard 4231: #endif
4232: }
4233: return res;
4234: }
4235:
1.203 brouard 4236: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4237: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4238: /* { */
4239: /* int i; */
4240: /* int l=1, lmax=20; */
4241: /* double k1,k2,k3,k4,res,fx; */
4242: /* double p2[MAXPARM+1]; */
4243: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4244: /* int k=0,kmax=10; */
4245: /* double l1; */
4246:
4247: /* fx=func(x); */
4248: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4249: /* l1=pow(10,l); */
4250: /* delts=delt; */
4251: /* for(k=1 ; k <kmax; k=k+1){ */
4252: /* delt = delti*(l1*k); */
4253: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4254: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4255: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4256: /* k1=func(p2)-fx; */
4257:
4258: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4259: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4260: /* k2=func(p2)-fx; */
4261:
4262: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4263: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4264: /* k3=func(p2)-fx; */
4265:
4266: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4267: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4268: /* k4=func(p2)-fx; */
4269: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4270: /* #ifdef DEBUGHESSIJ */
4271: /* 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); */
4272: /* 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); */
4273: /* #endif */
4274: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4275: /* k=kmax; */
4276: /* } */
4277: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4278: /* k=kmax; l=lmax*10; */
4279: /* } */
4280: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4281: /* delts=delt; */
4282: /* } */
4283: /* } /\* End loop k *\/ */
4284: /* } */
4285: /* delti[theta]=delts; */
4286: /* return res; */
4287: /* } */
4288:
4289:
1.126 brouard 4290: /************** Inverse of matrix **************/
4291: void ludcmp(double **a, int n, int *indx, double *d)
4292: {
4293: int i,imax,j,k;
4294: double big,dum,sum,temp;
4295: double *vv;
4296:
4297: vv=vector(1,n);
4298: *d=1.0;
4299: for (i=1;i<=n;i++) {
4300: big=0.0;
4301: for (j=1;j<=n;j++)
4302: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4303: if (big == 0.0){
4304: printf(" Singular Hessian matrix at row %d:\n",i);
4305: for (j=1;j<=n;j++) {
4306: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4307: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4308: }
4309: fflush(ficlog);
4310: fclose(ficlog);
4311: nrerror("Singular matrix in routine ludcmp");
4312: }
1.126 brouard 4313: vv[i]=1.0/big;
4314: }
4315: for (j=1;j<=n;j++) {
4316: for (i=1;i<j;i++) {
4317: sum=a[i][j];
4318: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4319: a[i][j]=sum;
4320: }
4321: big=0.0;
4322: for (i=j;i<=n;i++) {
4323: sum=a[i][j];
4324: for (k=1;k<j;k++)
4325: sum -= a[i][k]*a[k][j];
4326: a[i][j]=sum;
4327: if ( (dum=vv[i]*fabs(sum)) >= big) {
4328: big=dum;
4329: imax=i;
4330: }
4331: }
4332: if (j != imax) {
4333: for (k=1;k<=n;k++) {
4334: dum=a[imax][k];
4335: a[imax][k]=a[j][k];
4336: a[j][k]=dum;
4337: }
4338: *d = -(*d);
4339: vv[imax]=vv[j];
4340: }
4341: indx[j]=imax;
4342: if (a[j][j] == 0.0) a[j][j]=TINY;
4343: if (j != n) {
4344: dum=1.0/(a[j][j]);
4345: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4346: }
4347: }
4348: free_vector(vv,1,n); /* Doesn't work */
4349: ;
4350: }
4351:
4352: void lubksb(double **a, int n, int *indx, double b[])
4353: {
4354: int i,ii=0,ip,j;
4355: double sum;
4356:
4357: for (i=1;i<=n;i++) {
4358: ip=indx[i];
4359: sum=b[ip];
4360: b[ip]=b[i];
4361: if (ii)
4362: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4363: else if (sum) ii=i;
4364: b[i]=sum;
4365: }
4366: for (i=n;i>=1;i--) {
4367: sum=b[i];
4368: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4369: b[i]=sum/a[i][i];
4370: }
4371: }
4372:
4373: void pstamp(FILE *fichier)
4374: {
1.196 brouard 4375: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4376: }
4377:
1.253 brouard 4378:
4379:
1.126 brouard 4380: /************ Frequencies ********************/
1.251 brouard 4381: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4382: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4383: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4384: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4385:
1.265 brouard 4386: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4387: int iind=0, iage=0;
4388: int mi; /* Effective wave */
4389: int first;
4390: double ***freq; /* Frequencies */
1.268 brouard 4391: 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 */
4392: 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 4393: double *meanq, *stdq, *idq;
1.226 brouard 4394: double **meanqt;
4395: double *pp, **prop, *posprop, *pospropt;
4396: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4397: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4398: double agebegin, ageend;
4399:
4400: pp=vector(1,nlstate);
1.251 brouard 4401: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4402: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4403: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4404: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4405: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 4406: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 4407: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 4408: meanqt=matrix(1,lastpass,1,nqtveff);
4409: strcpy(fileresp,"P_");
4410: strcat(fileresp,fileresu);
4411: /*strcat(fileresphtm,fileresu);*/
4412: if((ficresp=fopen(fileresp,"w"))==NULL) {
4413: printf("Problem with prevalence resultfile: %s\n", fileresp);
4414: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4415: exit(0);
4416: }
1.240 brouard 4417:
1.226 brouard 4418: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4419: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4420: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4421: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4422: fflush(ficlog);
4423: exit(70);
4424: }
4425: else{
4426: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4427: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4428: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4429: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4430: }
1.237 brouard 4431: 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 4432:
1.226 brouard 4433: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4434: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4435: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4436: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4437: fflush(ficlog);
4438: exit(70);
1.240 brouard 4439: } else{
1.226 brouard 4440: 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 4441: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4442: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4443: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4444: }
1.240 brouard 4445: 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);
4446:
1.253 brouard 4447: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4448: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4449: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4450: j1=0;
1.126 brouard 4451:
1.227 brouard 4452: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4453: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4454: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4455:
4456:
1.226 brouard 4457: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4458: reference=low_education V1=0,V2=0
4459: med_educ V1=1 V2=0,
4460: high_educ V1=0 V2=1
4461: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4462: */
1.249 brouard 4463: dateintsum=0;
4464: k2cpt=0;
4465:
1.253 brouard 4466: if(cptcoveff == 0 )
1.265 brouard 4467: nl=1; /* Constant and age model only */
1.253 brouard 4468: else
4469: nl=2;
1.265 brouard 4470:
4471: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4472: /* Loop on nj=1 or 2 if dummy covariates j!=0
4473: * Loop on j1(1 to 2**cptcoveff) covariate combination
4474: * freq[s1][s2][iage] =0.
4475: * Loop on iind
4476: * ++freq[s1][s2][iage] weighted
4477: * end iind
4478: * if covariate and j!0
4479: * headers Variable on one line
4480: * endif cov j!=0
4481: * header of frequency table by age
4482: * Loop on age
4483: * pp[s1]+=freq[s1][s2][iage] weighted
4484: * pos+=freq[s1][s2][iage] weighted
4485: * Loop on s1 initial state
4486: * fprintf(ficresp
4487: * end s1
4488: * end age
4489: * if j!=0 computes starting values
4490: * end compute starting values
4491: * end j1
4492: * end nl
4493: */
1.253 brouard 4494: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4495: if(nj==1)
4496: j=0; /* First pass for the constant */
1.265 brouard 4497: else{
1.253 brouard 4498: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4499: }
1.251 brouard 4500: first=1;
1.265 brouard 4501: 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 4502: posproptt=0.;
4503: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4504: scanf("%d", i);*/
4505: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4506: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4507: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4508: freq[i][s2][m]=0;
1.251 brouard 4509:
4510: for (i=1; i<=nlstate; i++) {
1.240 brouard 4511: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4512: prop[i][m]=0;
4513: posprop[i]=0;
4514: pospropt[i]=0;
4515: }
1.283 brouard 4516: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 4517: idq[z1]=0.;
4518: meanq[z1]=0.;
4519: stdq[z1]=0.;
1.283 brouard 4520: }
4521: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 4522: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 4523: /* meanqt[m][z1]=0.; */
4524: /* } */
4525: /* } */
1.251 brouard 4526: /* dateintsum=0; */
4527: /* k2cpt=0; */
4528:
1.265 brouard 4529: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4530: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4531: bool=1;
4532: if(j !=0){
4533: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4534: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4535: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4536: /* if(Tvaraff[z1] ==-20){ */
4537: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4538: /* }else if(Tvaraff[z1] ==-10){ */
4539: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4540: /* }else */
4541: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4542: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4543: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4544: /* 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",
4545: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4546: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4547: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4548: } /* Onlyf fixed */
4549: } /* end z1 */
4550: } /* cptcovn > 0 */
4551: } /* end any */
4552: }/* end j==0 */
1.265 brouard 4553: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4554: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 4555: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 4556: m=mw[mi][iind];
4557: if(j!=0){
4558: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4559: for (z1=1; z1<=cptcoveff; z1++) {
4560: if( Fixed[Tmodelind[z1]]==1){
4561: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4562: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4563: value is -1, we don't select. It differs from the
4564: constant and age model which counts them. */
4565: bool=0; /* not selected */
4566: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4567: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4568: bool=0;
4569: }
4570: }
4571: }
4572: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4573: } /* end j==0 */
4574: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 4575: if(bool==1){ /*Selected */
1.251 brouard 4576: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4577: and mw[mi+1][iind]. dh depends on stepm. */
4578: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4579: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4580: if(m >=firstpass && m <=lastpass){
4581: k2=anint[m][iind]+(mint[m][iind]/12.);
4582: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4583: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4584: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4585: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4586: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4587: if (m<lastpass) {
4588: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4589: /* 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]); */
4590: if(s[m][iind]==-1)
4591: 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.));
4592: 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 4593: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean */
4594: idq[z1]=idq[z1]+weight[iind];
4595: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
4596: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
4597: }
1.251 brouard 4598: /* if((int)agev[m][iind] == 55) */
4599: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4600: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4601: 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 4602: }
1.251 brouard 4603: } /* end if between passes */
4604: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4605: dateintsum=dateintsum+k2; /* on all covariates ?*/
4606: k2cpt++;
4607: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4608: }
1.251 brouard 4609: }else{
4610: bool=1;
4611: }/* end bool 2 */
4612: } /* end m */
1.284 brouard 4613: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
4614: /* idq[z1]=idq[z1]+weight[iind]; */
4615: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
4616: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
4617: /* } */
1.251 brouard 4618: } /* end bool */
4619: } /* end iind = 1 to imx */
4620: /* prop[s][age] is feeded for any initial and valid live state as well as
4621: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4622:
4623:
4624: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4625: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4626: pstamp(ficresp);
1.251 brouard 4627: if (cptcoveff>0 && j!=0){
1.265 brouard 4628: pstamp(ficresp);
1.251 brouard 4629: printf( "\n#********** Variable ");
4630: fprintf(ficresp, "\n#********** Variable ");
4631: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4632: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4633: fprintf(ficlog, "\n#********** Variable ");
4634: for (z1=1; z1<=cptcoveff; z1++){
4635: if(!FixedV[Tvaraff[z1]]){
4636: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4637: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4638: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4639: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4640: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4641: }else{
1.251 brouard 4642: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4643: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4644: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4645: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4646: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4647: }
4648: }
4649: printf( "**********\n#");
4650: fprintf(ficresp, "**********\n#");
4651: fprintf(ficresphtm, "**********</h3>\n");
4652: fprintf(ficresphtmfr, "**********</h3>\n");
4653: fprintf(ficlog, "**********\n");
4654: }
1.284 brouard 4655: /*
4656: Printing means of quantitative variables if any
4657: */
4658: for (z1=1; z1<= nqfveff; z1++) {
1.285 brouard 4659: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.0f individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.284 brouard 4660: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
4661: if(weightopt==1){
4662: printf(" Weighted mean and standard deviation of");
4663: fprintf(ficlog," Weighted mean and standard deviation of");
4664: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
4665: }
1.285 brouard 4666: printf(" fixed quantitative variable V%d on %.0f representatives of the population : %6.3g (%6.3g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt((stdq[z1]-meanq[z1]*meanq[z1]/idq[z1])/idq[z1]));
4667: fprintf(ficlog," fixed quantitative variable V%d on %.0f representatives of the population : %6.3g (%6.3g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt((stdq[z1]-meanq[z1]*meanq[z1]/idq[z1])/idq[z1]));
4668: fprintf(ficresphtmfr," fixed quantitative variable V%d on %.0f representatives of the population : %6.3g (%6.3g)<p>\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt((stdq[z1]-meanq[z1]*meanq[z1]/idq[z1])/idq[z1]));
1.284 brouard 4669: }
4670: /* for (z1=1; z1<= nqtveff; z1++) { */
4671: /* for(m=1;m<=lastpass;m++){ */
4672: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
4673: /* } */
4674: /* } */
1.283 brouard 4675:
1.251 brouard 4676: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4677: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4678: fprintf(ficresp, " Age");
4679: 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 4680: for(i=1; i<=nlstate;i++) {
1.265 brouard 4681: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4682: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4683: }
1.265 brouard 4684: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4685: fprintf(ficresphtm, "\n");
4686:
4687: /* Header of frequency table by age */
4688: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4689: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4690: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4691: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4692: if(s2!=0 && m!=0)
4693: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4694: }
1.226 brouard 4695: }
1.251 brouard 4696: fprintf(ficresphtmfr, "\n");
4697:
4698: /* For each age */
4699: for(iage=iagemin; iage <= iagemax+3; iage++){
4700: fprintf(ficresphtm,"<tr>");
4701: if(iage==iagemax+1){
4702: fprintf(ficlog,"1");
4703: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4704: }else if(iage==iagemax+2){
4705: fprintf(ficlog,"0");
4706: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4707: }else if(iage==iagemax+3){
4708: fprintf(ficlog,"Total");
4709: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4710: }else{
1.240 brouard 4711: if(first==1){
1.251 brouard 4712: first=0;
4713: printf("See log file for details...\n");
4714: }
4715: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4716: fprintf(ficlog,"Age %d", iage);
4717: }
1.265 brouard 4718: for(s1=1; s1 <=nlstate ; s1++){
4719: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4720: pp[s1] += freq[s1][m][iage];
1.251 brouard 4721: }
1.265 brouard 4722: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4723: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4724: pos += freq[s1][m][iage];
4725: if(pp[s1]>=1.e-10){
1.251 brouard 4726: if(first==1){
1.265 brouard 4727: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4728: }
1.265 brouard 4729: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4730: }else{
4731: if(first==1)
1.265 brouard 4732: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4733: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4734: }
4735: }
4736:
1.265 brouard 4737: for(s1=1; s1 <=nlstate ; s1++){
4738: /* posprop[s1]=0; */
4739: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4740: pp[s1] += freq[s1][m][iage];
4741: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4742:
4743: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4744: pos += pp[s1]; /* pos is the total number of transitions until this age */
4745: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4746: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4747: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4748: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4749: }
4750:
4751: /* Writing ficresp */
4752: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4753: if( iage <= iagemax){
4754: fprintf(ficresp," %d",iage);
4755: }
4756: }else if( nj==2){
4757: if( iage <= iagemax){
4758: fprintf(ficresp," %d",iage);
4759: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4760: }
1.240 brouard 4761: }
1.265 brouard 4762: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4763: if(pos>=1.e-5){
1.251 brouard 4764: if(first==1)
1.265 brouard 4765: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4766: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4767: }else{
4768: if(first==1)
1.265 brouard 4769: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4770: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4771: }
4772: if( iage <= iagemax){
4773: if(pos>=1.e-5){
1.265 brouard 4774: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4775: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4776: }else if( nj==2){
4777: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4778: }
4779: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4780: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4781: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4782: } else{
4783: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4784: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4785: }
1.240 brouard 4786: }
1.265 brouard 4787: pospropt[s1] +=posprop[s1];
4788: } /* end loop s1 */
1.251 brouard 4789: /* pospropt=0.; */
1.265 brouard 4790: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4791: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4792: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4793: if(first==1){
1.265 brouard 4794: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4795: }
1.265 brouard 4796: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4797: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4798: }
1.265 brouard 4799: if(s1!=0 && m!=0)
4800: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4801: }
1.265 brouard 4802: } /* end loop s1 */
1.251 brouard 4803: posproptt=0.;
1.265 brouard 4804: for(s1=1; s1 <=nlstate; s1++){
4805: posproptt += pospropt[s1];
1.251 brouard 4806: }
4807: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4808: fprintf(ficresphtm,"</tr>\n");
4809: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4810: if(iage <= iagemax)
4811: fprintf(ficresp,"\n");
1.240 brouard 4812: }
1.251 brouard 4813: if(first==1)
4814: printf("Others in log...\n");
4815: fprintf(ficlog,"\n");
4816: } /* end loop age iage */
1.265 brouard 4817:
1.251 brouard 4818: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4819: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4820: if(posproptt < 1.e-5){
1.265 brouard 4821: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4822: }else{
1.265 brouard 4823: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4824: }
1.226 brouard 4825: }
1.251 brouard 4826: fprintf(ficresphtm,"</tr>\n");
4827: fprintf(ficresphtm,"</table>\n");
4828: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4829: if(posproptt < 1.e-5){
1.251 brouard 4830: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4831: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4832: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4833: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4834: invalidvarcomb[j1]=1;
1.226 brouard 4835: }else{
1.251 brouard 4836: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4837: invalidvarcomb[j1]=0;
1.226 brouard 4838: }
1.251 brouard 4839: fprintf(ficresphtmfr,"</table>\n");
4840: fprintf(ficlog,"\n");
4841: if(j!=0){
4842: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4843: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4844: for(k=1; k <=(nlstate+ndeath); k++){
4845: if (k != i) {
1.265 brouard 4846: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4847: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4848: if(j1==1){ /* All dummy covariates to zero */
4849: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4850: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4851: printf("%d%d ",i,k);
4852: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4853: 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]));
4854: 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]));
4855: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4856: }
1.253 brouard 4857: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4858: for(iage=iagemin; iage <= iagemax+3; iage++){
4859: x[iage]= (double)iage;
4860: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4861: /* 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 4862: }
1.268 brouard 4863: /* Some are not finite, but linreg will ignore these ages */
4864: no=0;
1.253 brouard 4865: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4866: pstart[s1]=b;
4867: pstart[s1-1]=a;
1.252 brouard 4868: }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 */
4869: 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]);
4870: 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 4871: 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 4872: printf("%d%d ",i,k);
4873: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4874: 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 4875: }else{ /* Other cases, like quantitative fixed or varying covariates */
4876: ;
4877: }
4878: /* printf("%12.7f )", param[i][jj][k]); */
4879: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4880: s1++;
1.251 brouard 4881: } /* end jj */
4882: } /* end k!= i */
4883: } /* end k */
1.265 brouard 4884: } /* end i, s1 */
1.251 brouard 4885: } /* end j !=0 */
4886: } /* end selected combination of covariate j1 */
4887: if(j==0){ /* We can estimate starting values from the occurences in each case */
4888: printf("#Freqsummary: Starting values for the constants:\n");
4889: fprintf(ficlog,"\n");
1.265 brouard 4890: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4891: for(k=1; k <=(nlstate+ndeath); k++){
4892: if (k != i) {
4893: printf("%d%d ",i,k);
4894: fprintf(ficlog,"%d%d ",i,k);
4895: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 4896: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 4897: if(jj==1){ /* Age has to be done */
1.265 brouard 4898: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
4899: 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]));
4900: 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 4901: }
4902: /* printf("%12.7f )", param[i][jj][k]); */
4903: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4904: s1++;
1.250 brouard 4905: }
1.251 brouard 4906: printf("\n");
4907: fprintf(ficlog,"\n");
1.250 brouard 4908: }
4909: }
1.284 brouard 4910: } /* end of state i */
1.251 brouard 4911: printf("#Freqsummary\n");
4912: fprintf(ficlog,"\n");
1.265 brouard 4913: for(s1=-1; s1 <=nlstate+ndeath; s1++){
4914: for(s2=-1; s2 <=nlstate+ndeath; s2++){
4915: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
4916: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4917: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4918: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
4919: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
4920: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 4921: /* } */
4922: }
1.265 brouard 4923: } /* end loop s1 */
1.251 brouard 4924:
4925: printf("\n");
4926: fprintf(ficlog,"\n");
4927: } /* end j=0 */
1.249 brouard 4928: } /* end j */
1.252 brouard 4929:
1.253 brouard 4930: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 4931: for(i=1, jk=1; i <=nlstate; i++){
4932: for(j=1; j <=nlstate+ndeath; j++){
4933: if(j!=i){
4934: /*ca[0]= k+'a'-1;ca[1]='\0';*/
4935: printf("%1d%1d",i,j);
4936: fprintf(ficparo,"%1d%1d",i,j);
4937: for(k=1; k<=ncovmodel;k++){
4938: /* printf(" %lf",param[i][j][k]); */
4939: /* fprintf(ficparo," %lf",param[i][j][k]); */
4940: p[jk]=pstart[jk];
4941: printf(" %f ",pstart[jk]);
4942: fprintf(ficparo," %f ",pstart[jk]);
4943: jk++;
4944: }
4945: printf("\n");
4946: fprintf(ficparo,"\n");
4947: }
4948: }
4949: }
4950: } /* end mle=-2 */
1.226 brouard 4951: dateintmean=dateintsum/k2cpt;
1.240 brouard 4952:
1.226 brouard 4953: fclose(ficresp);
4954: fclose(ficresphtm);
4955: fclose(ficresphtmfr);
1.283 brouard 4956: free_vector(idq,1,nqfveff);
1.226 brouard 4957: free_vector(meanq,1,nqfveff);
1.284 brouard 4958: free_vector(stdq,1,nqfveff);
1.226 brouard 4959: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 4960: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
4961: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 4962: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4963: free_vector(pospropt,1,nlstate);
4964: free_vector(posprop,1,nlstate);
1.251 brouard 4965: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4966: free_vector(pp,1,nlstate);
4967: /* End of freqsummary */
4968: }
1.126 brouard 4969:
1.268 brouard 4970: /* Simple linear regression */
4971: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
4972:
4973: /* y=a+bx regression */
4974: double sumx = 0.0; /* sum of x */
4975: double sumx2 = 0.0; /* sum of x**2 */
4976: double sumxy = 0.0; /* sum of x * y */
4977: double sumy = 0.0; /* sum of y */
4978: double sumy2 = 0.0; /* sum of y**2 */
4979: double sume2 = 0.0; /* sum of square or residuals */
4980: double yhat;
4981:
4982: double denom=0;
4983: int i;
4984: int ne=*no;
4985:
4986: for ( i=ifi, ne=0;i<=ila;i++) {
4987: if(!isfinite(x[i]) || !isfinite(y[i])){
4988: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
4989: continue;
4990: }
4991: ne=ne+1;
4992: sumx += x[i];
4993: sumx2 += x[i]*x[i];
4994: sumxy += x[i] * y[i];
4995: sumy += y[i];
4996: sumy2 += y[i]*y[i];
4997: denom = (ne * sumx2 - sumx*sumx);
4998: /* 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); */
4999: }
5000:
5001: denom = (ne * sumx2 - sumx*sumx);
5002: if (denom == 0) {
5003: // vertical, slope m is infinity
5004: *b = INFINITY;
5005: *a = 0;
5006: if (r) *r = 0;
5007: return 1;
5008: }
5009:
5010: *b = (ne * sumxy - sumx * sumy) / denom;
5011: *a = (sumy * sumx2 - sumx * sumxy) / denom;
5012: if (r!=NULL) {
5013: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
5014: sqrt((sumx2 - sumx*sumx/ne) *
5015: (sumy2 - sumy*sumy/ne));
5016: }
5017: *no=ne;
5018: for ( i=ifi, ne=0;i<=ila;i++) {
5019: if(!isfinite(x[i]) || !isfinite(y[i])){
5020: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
5021: continue;
5022: }
5023: ne=ne+1;
5024: yhat = y[i] - *a -*b* x[i];
5025: sume2 += yhat * yhat ;
5026:
5027: denom = (ne * sumx2 - sumx*sumx);
5028: /* 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); */
5029: }
5030: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
5031: *sa= *sb * sqrt(sumx2/ne);
5032:
5033: return 0;
5034: }
5035:
1.126 brouard 5036: /************ Prevalence ********************/
1.227 brouard 5037: 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)
5038: {
5039: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
5040: in each health status at the date of interview (if between dateprev1 and dateprev2).
5041: We still use firstpass and lastpass as another selection.
5042: */
1.126 brouard 5043:
1.227 brouard 5044: int i, m, jk, j1, bool, z1,j, iv;
5045: int mi; /* Effective wave */
5046: int iage;
5047: double agebegin, ageend;
5048:
5049: double **prop;
5050: double posprop;
5051: double y2; /* in fractional years */
5052: int iagemin, iagemax;
5053: int first; /** to stop verbosity which is redirected to log file */
5054:
5055: iagemin= (int) agemin;
5056: iagemax= (int) agemax;
5057: /*pp=vector(1,nlstate);*/
1.251 brouard 5058: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5059: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
5060: j1=0;
1.222 brouard 5061:
1.227 brouard 5062: /*j=cptcoveff;*/
5063: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 5064:
1.288 ! brouard 5065: first=0;
1.227 brouard 5066: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
5067: for (i=1; i<=nlstate; i++)
1.251 brouard 5068: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 5069: prop[i][iage]=0.0;
5070: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
5071: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
5072: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
5073:
5074: for (i=1; i<=imx; i++) { /* Each individual */
5075: bool=1;
5076: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
5077: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
5078: m=mw[mi][i];
5079: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
5080: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
5081: for (z1=1; z1<=cptcoveff; z1++){
5082: if( Fixed[Tmodelind[z1]]==1){
5083: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
5084: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
5085: bool=0;
5086: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
5087: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
5088: bool=0;
5089: }
5090: }
5091: if(bool==1){ /* Otherwise we skip that wave/person */
5092: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
5093: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
5094: if(m >=firstpass && m <=lastpass){
5095: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5096: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5097: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5098: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5099: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5100: 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);
5101: exit(1);
5102: }
5103: if (s[m][i]>0 && s[m][i]<=nlstate) {
5104: /*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]]);*/
5105: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5106: prop[s[m][i]][iagemax+3] += weight[i];
5107: } /* end valid statuses */
5108: } /* end selection of dates */
5109: } /* end selection of waves */
5110: } /* end bool */
5111: } /* end wave */
5112: } /* end individual */
5113: for(i=iagemin; i <= iagemax+3; i++){
5114: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5115: posprop += prop[jk][i];
5116: }
5117:
5118: for(jk=1; jk <=nlstate ; jk++){
5119: if( i <= iagemax){
5120: if(posprop>=1.e-5){
5121: probs[i][jk][j1]= prop[jk][i]/posprop;
5122: } else{
1.288 ! brouard 5123: if(!first){
! 5124: first=1;
1.266 brouard 5125: 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]);
5126: }else{
1.288 ! brouard 5127: fprintf(ficlog,"Warning Observed prevalence doesn't sum to 1 for state %d: probs[%d][%d][%d]=%lf because of lack of cases.\n",jk,i,jk, j1,probs[i][jk][j1]);
1.227 brouard 5128: }
5129: }
5130: }
5131: }/* end jk */
5132: }/* end i */
1.222 brouard 5133: /*} *//* end i1 */
1.227 brouard 5134: } /* end j1 */
1.222 brouard 5135:
1.227 brouard 5136: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5137: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5138: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5139: } /* End of prevalence */
1.126 brouard 5140:
5141: /************* Waves Concatenation ***************/
5142:
5143: 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)
5144: {
5145: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
5146: Death is a valid wave (if date is known).
5147: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5148: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
5149: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 5150: */
1.126 brouard 5151:
1.224 brouard 5152: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5153: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5154: double sum=0., jmean=0.;*/
1.224 brouard 5155: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5156: int j, k=0,jk, ju, jl;
5157: double sum=0.;
5158: first=0;
1.214 brouard 5159: firstwo=0;
1.217 brouard 5160: firsthree=0;
1.218 brouard 5161: firstfour=0;
1.164 brouard 5162: jmin=100000;
1.126 brouard 5163: jmax=-1;
5164: jmean=0.;
1.224 brouard 5165:
5166: /* Treating live states */
1.214 brouard 5167: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5168: mi=0; /* First valid wave */
1.227 brouard 5169: mli=0; /* Last valid wave */
1.126 brouard 5170: m=firstpass;
1.214 brouard 5171: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 5172: 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 */
5173: mli=m-1;/* mw[++mi][i]=m-1; */
5174: }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 */
5175: mw[++mi][i]=m;
5176: mli=m;
1.224 brouard 5177: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5178: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5179: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5180: }
1.227 brouard 5181: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 5182: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5183: break;
1.224 brouard 5184: #else
1.227 brouard 5185: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
5186: if(firsthree == 0){
1.262 brouard 5187: 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 5188: firsthree=1;
5189: }
1.262 brouard 5190: 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 5191: mw[++mi][i]=m;
5192: mli=m;
5193: }
5194: if(s[m][i]==-2){ /* Vital status is really unknown */
5195: nbwarn++;
5196: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
5197: 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);
5198: 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);
5199: }
5200: break;
5201: }
5202: break;
1.224 brouard 5203: #endif
1.227 brouard 5204: }/* End m >= lastpass */
1.126 brouard 5205: }/* end while */
1.224 brouard 5206:
1.227 brouard 5207: /* 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 5208: /* After last pass */
1.224 brouard 5209: /* Treating death states */
1.214 brouard 5210: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5211: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5212: /* } */
1.126 brouard 5213: mi++; /* Death is another wave */
5214: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5215: /* Only death is a correct wave */
1.126 brouard 5216: mw[mi][i]=m;
1.257 brouard 5217: } /* else not in a death state */
1.224 brouard 5218: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5219: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5220: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 5221: 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 */
5222: nbwarn++;
5223: if(firstfiv==0){
5224: 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 );
5225: firstfiv=1;
5226: }else{
5227: 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 );
5228: }
5229: }else{ /* Death occured afer last wave potential bias */
5230: nberr++;
5231: if(firstwo==0){
1.257 brouard 5232: 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 5233: firstwo=1;
5234: }
1.257 brouard 5235: 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 5236: }
1.257 brouard 5237: }else{ /* if date of interview is unknown */
1.227 brouard 5238: /* death is known but not confirmed by death status at any wave */
5239: if(firstfour==0){
5240: 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 );
5241: firstfour=1;
5242: }
5243: 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 5244: }
1.224 brouard 5245: } /* end if date of death is known */
5246: #endif
5247: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5248: /* wav[i]=mw[mi][i]; */
1.126 brouard 5249: if(mi==0){
5250: nbwarn++;
5251: if(first==0){
1.227 brouard 5252: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5253: first=1;
1.126 brouard 5254: }
5255: if(first==1){
1.227 brouard 5256: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5257: }
5258: } /* end mi==0 */
5259: } /* End individuals */
1.214 brouard 5260: /* wav and mw are no more changed */
1.223 brouard 5261:
1.214 brouard 5262:
1.126 brouard 5263: for(i=1; i<=imx; i++){
5264: for(mi=1; mi<wav[i];mi++){
5265: if (stepm <=0)
1.227 brouard 5266: dh[mi][i]=1;
1.126 brouard 5267: else{
1.260 brouard 5268: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5269: if (agedc[i] < 2*AGESUP) {
5270: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5271: if(j==0) j=1; /* Survives at least one month after exam */
5272: else if(j<0){
5273: nberr++;
5274: 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]);
5275: j=1; /* Temporary Dangerous patch */
5276: 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);
5277: 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]);
5278: 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);
5279: }
5280: k=k+1;
5281: if (j >= jmax){
5282: jmax=j;
5283: ijmax=i;
5284: }
5285: if (j <= jmin){
5286: jmin=j;
5287: ijmin=i;
5288: }
5289: sum=sum+j;
5290: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5291: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5292: }
5293: }
5294: else{
5295: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5296: /* 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 5297:
1.227 brouard 5298: k=k+1;
5299: if (j >= jmax) {
5300: jmax=j;
5301: ijmax=i;
5302: }
5303: else if (j <= jmin){
5304: jmin=j;
5305: ijmin=i;
5306: }
5307: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5308: /*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]);*/
5309: if(j<0){
5310: nberr++;
5311: 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]);
5312: 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]);
5313: }
5314: sum=sum+j;
5315: }
5316: jk= j/stepm;
5317: jl= j -jk*stepm;
5318: ju= j -(jk+1)*stepm;
5319: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5320: if(jl==0){
5321: dh[mi][i]=jk;
5322: bh[mi][i]=0;
5323: }else{ /* We want a negative bias in order to only have interpolation ie
5324: * to avoid the price of an extra matrix product in likelihood */
5325: dh[mi][i]=jk+1;
5326: bh[mi][i]=ju;
5327: }
5328: }else{
5329: if(jl <= -ju){
5330: dh[mi][i]=jk;
5331: bh[mi][i]=jl; /* bias is positive if real duration
5332: * is higher than the multiple of stepm and negative otherwise.
5333: */
5334: }
5335: else{
5336: dh[mi][i]=jk+1;
5337: bh[mi][i]=ju;
5338: }
5339: if(dh[mi][i]==0){
5340: dh[mi][i]=1; /* At least one step */
5341: bh[mi][i]=ju; /* At least one step */
5342: /* 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);*/
5343: }
5344: } /* end if mle */
1.126 brouard 5345: }
5346: } /* end wave */
5347: }
5348: jmean=sum/k;
5349: 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 5350: 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 5351: }
1.126 brouard 5352:
5353: /*********** Tricode ****************************/
1.220 brouard 5354: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5355: {
5356: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5357: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5358: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5359: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5360: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5361: */
1.130 brouard 5362:
1.242 brouard 5363: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5364: int modmaxcovj=0; /* Modality max of covariates j */
5365: int cptcode=0; /* Modality max of covariates j */
5366: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5367:
5368:
1.242 brouard 5369: /* cptcoveff=0; */
5370: /* *cptcov=0; */
1.126 brouard 5371:
1.242 brouard 5372: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 5373: for (k=1; k <= maxncov; k++)
5374: for(j=1; j<=2; j++)
5375: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 5376:
1.242 brouard 5377: /* Loop on covariates without age and products and no quantitative variable */
5378: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5379: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5380: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5381: switch(Fixed[k]) {
5382: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5383: 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*/
5384: ij=(int)(covar[Tvar[k]][i]);
5385: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5386: * If product of Vn*Vm, still boolean *:
5387: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5388: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5389: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5390: modality of the nth covariate of individual i. */
5391: if (ij > modmaxcovj)
5392: modmaxcovj=ij;
5393: else if (ij < modmincovj)
5394: modmincovj=ij;
1.287 brouard 5395: if (ij <0 || ij >1 ){
5396: printf("Information, IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5397: fprintf(ficlog,"Information, currently IMaCh doesn't treat covariate with missing values (-1), individual %d will be skipped.\n",i);
5398: }
5399: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 5400: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5401: exit(1);
5402: }else
5403: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5404: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5405: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5406: /* getting the maximum value of the modality of the covariate
5407: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5408: female ies 1, then modmaxcovj=1.
5409: */
5410: } /* end for loop on individuals i */
5411: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5412: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5413: cptcode=modmaxcovj;
5414: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5415: /*for (i=0; i<=cptcode; i++) {*/
5416: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5417: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5418: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5419: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5420: if( j != -1){
5421: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5422: covariate for which somebody answered excluding
5423: undefined. Usually 2: 0 and 1. */
5424: }
5425: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5426: covariate for which somebody answered including
5427: undefined. Usually 3: -1, 0 and 1. */
5428: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5429: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5430: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5431:
1.242 brouard 5432: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5433: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5434: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5435: /* modmincovj=3; modmaxcovj = 7; */
5436: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5437: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5438: /* defining two dummy variables: variables V1_1 and V1_2.*/
5439: /* nbcode[Tvar[j]][ij]=k; */
5440: /* nbcode[Tvar[j]][1]=0; */
5441: /* nbcode[Tvar[j]][2]=1; */
5442: /* nbcode[Tvar[j]][3]=2; */
5443: /* To be continued (not working yet). */
5444: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 5445:
5446: /* 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*/
5447: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
5448: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
5449: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
5450: /*, could be restored in the future */
5451: for (i=0; i<=1; i++) { /* i= 1 to 2 for dichotomous, or from 1 to 3 or from -1 or 0 to 1 currently*/
1.242 brouard 5452: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5453: break;
5454: }
5455: ij++;
1.287 brouard 5456: nbcode[Tvar[k]][ij]=i; /* stores the original value of modality i in an array nbcode, ij modality from 1 to last non-nul modality. nbcode[1][1]=0 nbcode[1][2]=1 . Could be -1*/
1.242 brouard 5457: cptcode = ij; /* New max modality for covar j */
5458: } /* end of loop on modality i=-1 to 1 or more */
5459: break;
5460: case 1: /* Testing on varying covariate, could be simple and
5461: * should look at waves or product of fixed *
5462: * varying. No time to test -1, assuming 0 and 1 only */
5463: ij=0;
5464: for(i=0; i<=1;i++){
5465: nbcode[Tvar[k]][++ij]=i;
5466: }
5467: break;
5468: default:
5469: break;
5470: } /* end switch */
5471: } /* end dummy test */
1.287 brouard 5472: } /* end of loop on model-covariate k. nbcode[Tvark][1]=-1, nbcode[Tvark][1]=0 and nbcode[Tvark][2]=1 sets the value of covariate k*/
1.242 brouard 5473:
5474: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5475: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5476: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5477: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5478: 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 */
5479: 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 */
5480: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5481: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5482:
5483: ij=0;
5484: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5485: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5486: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5487: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5488: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5489: /* If product not in single variable we don't print results */
5490: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5491: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5492: 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*/
5493: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5494: 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 */
5495: if(Fixed[k]!=0)
5496: anyvaryingduminmodel=1;
5497: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5498: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5499: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5500: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5501: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5502: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5503: }
5504: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5505: /* ij--; */
5506: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5507: *cptcov=ij; /*Number of total real effective covariates: effective
5508: * because they can be excluded from the model and real
5509: * if in the model but excluded because missing values, but how to get k from ij?*/
5510: for(j=ij+1; j<= cptcovt; j++){
5511: Tvaraff[j]=0;
5512: Tmodelind[j]=0;
5513: }
5514: for(j=ntveff+1; j<= cptcovt; j++){
5515: TmodelInvind[j]=0;
5516: }
5517: /* To be sorted */
5518: ;
5519: }
1.126 brouard 5520:
1.145 brouard 5521:
1.126 brouard 5522: /*********** Health Expectancies ****************/
5523:
1.235 brouard 5524: 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 5525:
5526: {
5527: /* Health expectancies, no variances */
1.164 brouard 5528: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5529: int nhstepma, nstepma; /* Decreasing with age */
5530: double age, agelim, hf;
5531: double ***p3mat;
5532: double eip;
5533:
1.238 brouard 5534: /* pstamp(ficreseij); */
1.126 brouard 5535: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5536: fprintf(ficreseij,"# Age");
5537: for(i=1; i<=nlstate;i++){
5538: for(j=1; j<=nlstate;j++){
5539: fprintf(ficreseij," e%1d%1d ",i,j);
5540: }
5541: fprintf(ficreseij," e%1d. ",i);
5542: }
5543: fprintf(ficreseij,"\n");
5544:
5545:
5546: if(estepm < stepm){
5547: printf ("Problem %d lower than %d\n",estepm, stepm);
5548: }
5549: else hstepm=estepm;
5550: /* We compute the life expectancy from trapezoids spaced every estepm months
5551: * This is mainly to measure the difference between two models: for example
5552: * if stepm=24 months pijx are given only every 2 years and by summing them
5553: * we are calculating an estimate of the Life Expectancy assuming a linear
5554: * progression in between and thus overestimating or underestimating according
5555: * to the curvature of the survival function. If, for the same date, we
5556: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5557: * to compare the new estimate of Life expectancy with the same linear
5558: * hypothesis. A more precise result, taking into account a more precise
5559: * curvature will be obtained if estepm is as small as stepm. */
5560:
5561: /* For example we decided to compute the life expectancy with the smallest unit */
5562: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5563: nhstepm is the number of hstepm from age to agelim
5564: nstepm is the number of stepm from age to agelin.
1.270 brouard 5565: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5566: and note for a fixed period like estepm months */
5567: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5568: survival function given by stepm (the optimization length). Unfortunately it
5569: means that if the survival funtion is printed only each two years of age and if
5570: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5571: results. So we changed our mind and took the option of the best precision.
5572: */
5573: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5574:
5575: agelim=AGESUP;
5576: /* If stepm=6 months */
5577: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5578: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5579:
5580: /* nhstepm age range expressed in number of stepm */
5581: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5582: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5583: /* if (stepm >= YEARM) hstepm=1;*/
5584: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5585: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5586:
5587: for (age=bage; age<=fage; age ++){
5588: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5589: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5590: /* if (stepm >= YEARM) hstepm=1;*/
5591: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5592:
5593: /* If stepm=6 months */
5594: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5595: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5596:
1.235 brouard 5597: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5598:
5599: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5600:
5601: printf("%d|",(int)age);fflush(stdout);
5602: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5603:
5604: /* Computing expectancies */
5605: for(i=1; i<=nlstate;i++)
5606: for(j=1; j<=nlstate;j++)
5607: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5608: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5609:
5610: /* 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]);*/
5611:
5612: }
5613:
5614: fprintf(ficreseij,"%3.0f",age );
5615: for(i=1; i<=nlstate;i++){
5616: eip=0;
5617: for(j=1; j<=nlstate;j++){
5618: eip +=eij[i][j][(int)age];
5619: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5620: }
5621: fprintf(ficreseij,"%9.4f", eip );
5622: }
5623: fprintf(ficreseij,"\n");
5624:
5625: }
5626: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5627: printf("\n");
5628: fprintf(ficlog,"\n");
5629:
5630: }
5631:
1.235 brouard 5632: 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 5633:
5634: {
5635: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5636: to initial status i, ei. .
1.126 brouard 5637: */
5638: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5639: int nhstepma, nstepma; /* Decreasing with age */
5640: double age, agelim, hf;
5641: double ***p3matp, ***p3matm, ***varhe;
5642: double **dnewm,**doldm;
5643: double *xp, *xm;
5644: double **gp, **gm;
5645: double ***gradg, ***trgradg;
5646: int theta;
5647:
5648: double eip, vip;
5649:
5650: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5651: xp=vector(1,npar);
5652: xm=vector(1,npar);
5653: dnewm=matrix(1,nlstate*nlstate,1,npar);
5654: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5655:
5656: pstamp(ficresstdeij);
5657: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5658: fprintf(ficresstdeij,"# Age");
5659: for(i=1; i<=nlstate;i++){
5660: for(j=1; j<=nlstate;j++)
5661: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5662: fprintf(ficresstdeij," e%1d. ",i);
5663: }
5664: fprintf(ficresstdeij,"\n");
5665:
5666: pstamp(ficrescveij);
5667: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5668: fprintf(ficrescveij,"# Age");
5669: for(i=1; i<=nlstate;i++)
5670: for(j=1; j<=nlstate;j++){
5671: cptj= (j-1)*nlstate+i;
5672: for(i2=1; i2<=nlstate;i2++)
5673: for(j2=1; j2<=nlstate;j2++){
5674: cptj2= (j2-1)*nlstate+i2;
5675: if(cptj2 <= cptj)
5676: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5677: }
5678: }
5679: fprintf(ficrescveij,"\n");
5680:
5681: if(estepm < stepm){
5682: printf ("Problem %d lower than %d\n",estepm, stepm);
5683: }
5684: else hstepm=estepm;
5685: /* We compute the life expectancy from trapezoids spaced every estepm months
5686: * This is mainly to measure the difference between two models: for example
5687: * if stepm=24 months pijx are given only every 2 years and by summing them
5688: * we are calculating an estimate of the Life Expectancy assuming a linear
5689: * progression in between and thus overestimating or underestimating according
5690: * to the curvature of the survival function. If, for the same date, we
5691: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5692: * to compare the new estimate of Life expectancy with the same linear
5693: * hypothesis. A more precise result, taking into account a more precise
5694: * curvature will be obtained if estepm is as small as stepm. */
5695:
5696: /* For example we decided to compute the life expectancy with the smallest unit */
5697: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5698: nhstepm is the number of hstepm from age to agelim
5699: nstepm is the number of stepm from age to agelin.
5700: Look at hpijx to understand the reason of that which relies in memory size
5701: and note for a fixed period like estepm months */
5702: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5703: survival function given by stepm (the optimization length). Unfortunately it
5704: means that if the survival funtion is printed only each two years of age and if
5705: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5706: results. So we changed our mind and took the option of the best precision.
5707: */
5708: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5709:
5710: /* If stepm=6 months */
5711: /* nhstepm age range expressed in number of stepm */
5712: agelim=AGESUP;
5713: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5714: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5715: /* if (stepm >= YEARM) hstepm=1;*/
5716: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5717:
5718: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5719: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5720: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5721: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5722: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5723: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5724:
5725: for (age=bage; age<=fage; age ++){
5726: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5727: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5728: /* if (stepm >= YEARM) hstepm=1;*/
5729: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5730:
1.126 brouard 5731: /* If stepm=6 months */
5732: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5733: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5734:
5735: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5736:
1.126 brouard 5737: /* Computing Variances of health expectancies */
5738: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5739: decrease memory allocation */
5740: for(theta=1; theta <=npar; theta++){
5741: for(i=1; i<=npar; i++){
1.222 brouard 5742: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5743: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5744: }
1.235 brouard 5745: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5746: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5747:
1.126 brouard 5748: for(j=1; j<= nlstate; j++){
1.222 brouard 5749: for(i=1; i<=nlstate; i++){
5750: for(h=0; h<=nhstepm-1; h++){
5751: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5752: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5753: }
5754: }
1.126 brouard 5755: }
1.218 brouard 5756:
1.126 brouard 5757: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5758: for(h=0; h<=nhstepm-1; h++){
5759: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5760: }
1.126 brouard 5761: }/* End theta */
5762:
5763:
5764: for(h=0; h<=nhstepm-1; h++)
5765: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5766: for(theta=1; theta <=npar; theta++)
5767: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5768:
1.218 brouard 5769:
1.222 brouard 5770: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5771: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5772: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5773:
1.222 brouard 5774: printf("%d|",(int)age);fflush(stdout);
5775: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5776: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5777: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5778: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5779: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5780: for(ij=1;ij<=nlstate*nlstate;ij++)
5781: for(ji=1;ji<=nlstate*nlstate;ji++)
5782: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5783: }
5784: }
1.218 brouard 5785:
1.126 brouard 5786: /* Computing expectancies */
1.235 brouard 5787: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5788: for(i=1; i<=nlstate;i++)
5789: for(j=1; j<=nlstate;j++)
1.222 brouard 5790: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5791: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5792:
1.222 brouard 5793: /* 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 5794:
1.222 brouard 5795: }
1.269 brouard 5796:
5797: /* Standard deviation of expectancies ij */
1.126 brouard 5798: fprintf(ficresstdeij,"%3.0f",age );
5799: for(i=1; i<=nlstate;i++){
5800: eip=0.;
5801: vip=0.;
5802: for(j=1; j<=nlstate;j++){
1.222 brouard 5803: eip += eij[i][j][(int)age];
5804: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5805: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5806: 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 5807: }
5808: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5809: }
5810: fprintf(ficresstdeij,"\n");
1.218 brouard 5811:
1.269 brouard 5812: /* Variance of expectancies ij */
1.126 brouard 5813: fprintf(ficrescveij,"%3.0f",age );
5814: for(i=1; i<=nlstate;i++)
5815: for(j=1; j<=nlstate;j++){
1.222 brouard 5816: cptj= (j-1)*nlstate+i;
5817: for(i2=1; i2<=nlstate;i2++)
5818: for(j2=1; j2<=nlstate;j2++){
5819: cptj2= (j2-1)*nlstate+i2;
5820: if(cptj2 <= cptj)
5821: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5822: }
1.126 brouard 5823: }
5824: fprintf(ficrescveij,"\n");
1.218 brouard 5825:
1.126 brouard 5826: }
5827: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5828: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5829: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5830: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5831: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5832: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5833: printf("\n");
5834: fprintf(ficlog,"\n");
1.218 brouard 5835:
1.126 brouard 5836: free_vector(xm,1,npar);
5837: free_vector(xp,1,npar);
5838: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5839: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5840: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5841: }
1.218 brouard 5842:
1.126 brouard 5843: /************ Variance ******************/
1.235 brouard 5844: 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 5845: {
1.279 brouard 5846: /** Variance of health expectancies
5847: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
5848: * double **newm;
5849: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
5850: */
1.218 brouard 5851:
5852: /* int movingaverage(); */
5853: double **dnewm,**doldm;
5854: double **dnewmp,**doldmp;
5855: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 ! brouard 5856: int first=0;
1.218 brouard 5857: int k;
5858: double *xp;
1.279 brouard 5859: double **gp, **gm; /**< for var eij */
5860: double ***gradg, ***trgradg; /**< for var eij */
5861: double **gradgp, **trgradgp; /**< for var p point j */
5862: double *gpp, *gmp; /**< for var p point j */
5863: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 5864: double ***p3mat;
5865: double age,agelim, hf;
5866: /* double ***mobaverage; */
5867: int theta;
5868: char digit[4];
5869: char digitp[25];
5870:
5871: char fileresprobmorprev[FILENAMELENGTH];
5872:
5873: if(popbased==1){
5874: if(mobilav!=0)
5875: strcpy(digitp,"-POPULBASED-MOBILAV_");
5876: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5877: }
5878: else
5879: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5880:
1.218 brouard 5881: /* if (mobilav!=0) { */
5882: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5883: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5884: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5885: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5886: /* } */
5887: /* } */
5888:
5889: strcpy(fileresprobmorprev,"PRMORPREV-");
5890: sprintf(digit,"%-d",ij);
5891: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5892: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5893: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5894: strcat(fileresprobmorprev,fileresu);
5895: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5896: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5897: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5898: }
5899: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5900: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5901: pstamp(ficresprobmorprev);
5902: 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 5903: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5904: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5905: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5906: }
5907: for(j=1;j<=cptcoveff;j++)
5908: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5909: fprintf(ficresprobmorprev,"\n");
5910:
1.218 brouard 5911: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5912: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5913: fprintf(ficresprobmorprev," p.%-d SE",j);
5914: for(i=1; i<=nlstate;i++)
5915: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5916: }
5917: fprintf(ficresprobmorprev,"\n");
5918:
5919: fprintf(ficgp,"\n# Routine varevsij");
5920: fprintf(ficgp,"\nunset title \n");
5921: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5922: 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");
5923: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 5924:
1.218 brouard 5925: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5926: pstamp(ficresvij);
5927: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5928: if(popbased==1)
5929: 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);
5930: else
5931: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5932: fprintf(ficresvij,"# Age");
5933: for(i=1; i<=nlstate;i++)
5934: for(j=1; j<=nlstate;j++)
5935: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5936: fprintf(ficresvij,"\n");
5937:
5938: xp=vector(1,npar);
5939: dnewm=matrix(1,nlstate,1,npar);
5940: doldm=matrix(1,nlstate,1,nlstate);
5941: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5942: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5943:
5944: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5945: gpp=vector(nlstate+1,nlstate+ndeath);
5946: gmp=vector(nlstate+1,nlstate+ndeath);
5947: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5948:
1.218 brouard 5949: if(estepm < stepm){
5950: printf ("Problem %d lower than %d\n",estepm, stepm);
5951: }
5952: else hstepm=estepm;
5953: /* For example we decided to compute the life expectancy with the smallest unit */
5954: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5955: nhstepm is the number of hstepm from age to agelim
5956: nstepm is the number of stepm from age to agelim.
5957: Look at function hpijx to understand why because of memory size limitations,
5958: we decided (b) to get a life expectancy respecting the most precise curvature of the
5959: survival function given by stepm (the optimization length). Unfortunately it
5960: means that if the survival funtion is printed every two years of age and if
5961: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5962: results. So we changed our mind and took the option of the best precision.
5963: */
5964: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5965: agelim = AGESUP;
5966: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5967: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5968: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5969: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5970: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
5971: gp=matrix(0,nhstepm,1,nlstate);
5972: gm=matrix(0,nhstepm,1,nlstate);
5973:
5974:
5975: for(theta=1; theta <=npar; theta++){
5976: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
5977: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5978: }
1.279 brouard 5979: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
5980: * returns into prlim .
1.288 ! brouard 5981: */
1.242 brouard 5982: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 5983:
5984: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 5985: if (popbased==1) {
5986: if(mobilav ==0){
5987: for(i=1; i<=nlstate;i++)
5988: prlim[i][i]=probs[(int)age][i][ij];
5989: }else{ /* mobilav */
5990: for(i=1; i<=nlstate;i++)
5991: prlim[i][i]=mobaverage[(int)age][i][ij];
5992: }
5993: }
1.279 brouard 5994: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}_x\f$ at horizon h.
5995: */
5996: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Returns p3mat[i][j][h] for h=0 to nhstepm */
5997: /**< And for each alive state j, sums over i \f$ w^i_x {}{h}_p^{ij}_x\f$, which are the probability
5998: * at horizon h in state j including mortality.
5999: */
1.218 brouard 6000: for(j=1; j<= nlstate; j++){
6001: for(h=0; h<=nhstepm; h++){
6002: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
6003: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
6004: }
6005: }
1.279 brouard 6006: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 6007: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 6008: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 6009: */
6010: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6011: for(i=1,gpp[j]=0.; i<= nlstate; i++)
6012: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 6013: }
6014:
6015: /* Again with minus shift */
1.218 brouard 6016:
6017: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
6018: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 ! brouard 6019:
1.242 brouard 6020: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 6021:
6022: if (popbased==1) {
6023: if(mobilav ==0){
6024: for(i=1; i<=nlstate;i++)
6025: prlim[i][i]=probs[(int)age][i][ij];
6026: }else{ /* mobilav */
6027: for(i=1; i<=nlstate;i++)
6028: prlim[i][i]=mobaverage[(int)age][i][ij];
6029: }
6030: }
6031:
1.235 brouard 6032: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 6033:
6034: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
6035: for(h=0; h<=nhstepm; h++){
6036: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
6037: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
6038: }
6039: }
6040: /* This for computing probability of death (h=1 means
6041: computed over hstepm matrices product = hstepm*stepm months)
6042: as a weighted average of prlim.
6043: */
6044: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6045: for(i=1,gmp[j]=0.; i<= nlstate; i++)
6046: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6047: }
1.279 brouard 6048: /* end shifting computations */
6049:
6050: /**< Computing gradient matrix at horizon h
6051: */
1.218 brouard 6052: for(j=1; j<= nlstate; j++) /* vareij */
6053: for(h=0; h<=nhstepm; h++){
6054: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
6055: }
1.279 brouard 6056: /**< Gradient of overall mortality p.3 (or p.j)
6057: */
6058: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 6059: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
6060: }
6061:
6062: } /* End theta */
1.279 brouard 6063:
6064: /* We got the gradient matrix for each theta and state j */
1.218 brouard 6065: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
6066:
6067: for(h=0; h<=nhstepm; h++) /* veij */
6068: for(j=1; j<=nlstate;j++)
6069: for(theta=1; theta <=npar; theta++)
6070: trgradg[h][j][theta]=gradg[h][theta][j];
6071:
6072: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
6073: for(theta=1; theta <=npar; theta++)
6074: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 6075: /**< as well as its transposed matrix
6076: */
1.218 brouard 6077:
6078: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6079: for(i=1;i<=nlstate;i++)
6080: for(j=1;j<=nlstate;j++)
6081: vareij[i][j][(int)age] =0.;
1.279 brouard 6082:
6083: /* Computing trgradg by matcov by gradg at age and summing over h
6084: * and k (nhstepm) formula 15 of article
6085: * Lievre-Brouard-Heathcote
6086: */
6087:
1.218 brouard 6088: for(h=0;h<=nhstepm;h++){
6089: for(k=0;k<=nhstepm;k++){
6090: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
6091: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
6092: for(i=1;i<=nlstate;i++)
6093: for(j=1;j<=nlstate;j++)
6094: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
6095: }
6096: }
6097:
1.279 brouard 6098: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
6099: * p.j overall mortality formula 49 but computed directly because
6100: * we compute the grad (wix pijx) instead of grad (pijx),even if
6101: * wix is independent of theta.
6102: */
1.218 brouard 6103: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
6104: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
6105: for(j=nlstate+1;j<=nlstate+ndeath;j++)
6106: for(i=nlstate+1;i<=nlstate+ndeath;i++)
6107: varppt[j][i]=doldmp[j][i];
6108: /* end ppptj */
6109: /* x centered again */
6110:
1.242 brouard 6111: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 6112:
6113: if (popbased==1) {
6114: if(mobilav ==0){
6115: for(i=1; i<=nlstate;i++)
6116: prlim[i][i]=probs[(int)age][i][ij];
6117: }else{ /* mobilav */
6118: for(i=1; i<=nlstate;i++)
6119: prlim[i][i]=mobaverage[(int)age][i][ij];
6120: }
6121: }
6122:
6123: /* This for computing probability of death (h=1 means
6124: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6125: as a weighted average of prlim.
6126: */
1.235 brouard 6127: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6128: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6129: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6130: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6131: }
6132: /* end probability of death */
6133:
6134: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6135: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6136: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6137: for(i=1; i<=nlstate;i++){
6138: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6139: }
6140: }
6141: fprintf(ficresprobmorprev,"\n");
6142:
6143: fprintf(ficresvij,"%.0f ",age );
6144: for(i=1; i<=nlstate;i++)
6145: for(j=1; j<=nlstate;j++){
6146: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6147: }
6148: fprintf(ficresvij,"\n");
6149: free_matrix(gp,0,nhstepm,1,nlstate);
6150: free_matrix(gm,0,nhstepm,1,nlstate);
6151: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6152: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6153: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6154: } /* End age */
6155: free_vector(gpp,nlstate+1,nlstate+ndeath);
6156: free_vector(gmp,nlstate+1,nlstate+ndeath);
6157: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6158: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6159: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6160: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6161: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6162: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6163: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6164: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6165: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6166: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6167: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6168: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6169: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6170: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6171: 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);
6172: /* 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 6173: */
1.218 brouard 6174: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6175: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6176:
1.218 brouard 6177: free_vector(xp,1,npar);
6178: free_matrix(doldm,1,nlstate,1,nlstate);
6179: free_matrix(dnewm,1,nlstate,1,npar);
6180: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6181: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6182: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6183: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6184: fclose(ficresprobmorprev);
6185: fflush(ficgp);
6186: fflush(fichtm);
6187: } /* end varevsij */
1.126 brouard 6188:
6189: /************ Variance of prevlim ******************/
1.269 brouard 6190: 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 6191: {
1.205 brouard 6192: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6193: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6194:
1.268 brouard 6195: double **dnewmpar,**doldm;
1.126 brouard 6196: int i, j, nhstepm, hstepm;
6197: double *xp;
6198: double *gp, *gm;
6199: double **gradg, **trgradg;
1.208 brouard 6200: double **mgm, **mgp;
1.126 brouard 6201: double age,agelim;
6202: int theta;
6203:
6204: pstamp(ficresvpl);
1.288 ! brouard 6205: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 6206: fprintf(ficresvpl,"# Age ");
6207: if(nresult >=1)
6208: fprintf(ficresvpl," Result# ");
1.126 brouard 6209: for(i=1; i<=nlstate;i++)
6210: fprintf(ficresvpl," %1d-%1d",i,i);
6211: fprintf(ficresvpl,"\n");
6212:
6213: xp=vector(1,npar);
1.268 brouard 6214: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6215: doldm=matrix(1,nlstate,1,nlstate);
6216:
6217: hstepm=1*YEARM; /* Every year of age */
6218: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6219: agelim = AGESUP;
6220: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6221: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6222: if (stepm >= YEARM) hstepm=1;
6223: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6224: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6225: mgp=matrix(1,npar,1,nlstate);
6226: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6227: gp=vector(1,nlstate);
6228: gm=vector(1,nlstate);
6229:
6230: for(theta=1; theta <=npar; theta++){
6231: for(i=1; i<=npar; i++){ /* Computes gradient */
6232: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6233: }
1.288 ! brouard 6234: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
! 6235: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
! 6236: /* else */
! 6237: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6238: for(i=1;i<=nlstate;i++){
1.126 brouard 6239: gp[i] = prlim[i][i];
1.208 brouard 6240: mgp[theta][i] = prlim[i][i];
6241: }
1.126 brouard 6242: for(i=1; i<=npar; i++) /* Computes gradient */
6243: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 ! brouard 6244: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
! 6245: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
! 6246: /* else */
! 6247: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6248: for(i=1;i<=nlstate;i++){
1.126 brouard 6249: gm[i] = prlim[i][i];
1.208 brouard 6250: mgm[theta][i] = prlim[i][i];
6251: }
1.126 brouard 6252: for(i=1;i<=nlstate;i++)
6253: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6254: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6255: } /* End theta */
6256:
6257: trgradg =matrix(1,nlstate,1,npar);
6258:
6259: for(j=1; j<=nlstate;j++)
6260: for(theta=1; theta <=npar; theta++)
6261: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6262: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6263: /* printf("\nmgm mgp %d ",(int)age); */
6264: /* for(j=1; j<=nlstate;j++){ */
6265: /* printf(" %d ",j); */
6266: /* for(theta=1; theta <=npar; theta++) */
6267: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6268: /* printf("\n "); */
6269: /* } */
6270: /* } */
6271: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6272: /* printf("\n gradg %d ",(int)age); */
6273: /* for(j=1; j<=nlstate;j++){ */
6274: /* printf("%d ",j); */
6275: /* for(theta=1; theta <=npar; theta++) */
6276: /* printf("%d %lf ",theta,gradg[theta][j]); */
6277: /* printf("\n "); */
6278: /* } */
6279: /* } */
1.126 brouard 6280:
6281: for(i=1;i<=nlstate;i++)
6282: varpl[i][(int)age] =0.;
1.209 brouard 6283: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6284: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6285: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6286: }else{
1.268 brouard 6287: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6288: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6289: }
1.126 brouard 6290: for(i=1;i<=nlstate;i++)
6291: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6292:
6293: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6294: if(nresult >=1)
6295: fprintf(ficresvpl,"%d ",nres );
1.288 ! brouard 6296: for(i=1; i<=nlstate;i++){
1.126 brouard 6297: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 ! brouard 6298: /* for(j=1;j<=nlstate;j++) */
! 6299: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
! 6300: }
1.126 brouard 6301: fprintf(ficresvpl,"\n");
6302: free_vector(gp,1,nlstate);
6303: free_vector(gm,1,nlstate);
1.208 brouard 6304: free_matrix(mgm,1,npar,1,nlstate);
6305: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6306: free_matrix(gradg,1,npar,1,nlstate);
6307: free_matrix(trgradg,1,nlstate,1,npar);
6308: } /* End age */
6309:
6310: free_vector(xp,1,npar);
6311: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6312: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6313:
6314: }
6315:
6316:
6317: /************ Variance of backprevalence limit ******************/
1.269 brouard 6318: 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 6319: {
6320: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6321: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6322:
6323: double **dnewmpar,**doldm;
6324: int i, j, nhstepm, hstepm;
6325: double *xp;
6326: double *gp, *gm;
6327: double **gradg, **trgradg;
6328: double **mgm, **mgp;
6329: double age,agelim;
6330: int theta;
6331:
6332: pstamp(ficresvbl);
6333: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6334: fprintf(ficresvbl,"# Age ");
6335: if(nresult >=1)
6336: fprintf(ficresvbl," Result# ");
6337: for(i=1; i<=nlstate;i++)
6338: fprintf(ficresvbl," %1d-%1d",i,i);
6339: fprintf(ficresvbl,"\n");
6340:
6341: xp=vector(1,npar);
6342: dnewmpar=matrix(1,nlstate,1,npar);
6343: doldm=matrix(1,nlstate,1,nlstate);
6344:
6345: hstepm=1*YEARM; /* Every year of age */
6346: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6347: agelim = AGEINF;
6348: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6349: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6350: if (stepm >= YEARM) hstepm=1;
6351: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6352: gradg=matrix(1,npar,1,nlstate);
6353: mgp=matrix(1,npar,1,nlstate);
6354: mgm=matrix(1,npar,1,nlstate);
6355: gp=vector(1,nlstate);
6356: gm=vector(1,nlstate);
6357:
6358: for(theta=1; theta <=npar; theta++){
6359: for(i=1; i<=npar; i++){ /* Computes gradient */
6360: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6361: }
6362: if(mobilavproj > 0 )
6363: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6364: else
6365: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6366: for(i=1;i<=nlstate;i++){
6367: gp[i] = bprlim[i][i];
6368: mgp[theta][i] = bprlim[i][i];
6369: }
6370: for(i=1; i<=npar; i++) /* Computes gradient */
6371: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6372: if(mobilavproj > 0 )
6373: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6374: else
6375: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6376: for(i=1;i<=nlstate;i++){
6377: gm[i] = bprlim[i][i];
6378: mgm[theta][i] = bprlim[i][i];
6379: }
6380: for(i=1;i<=nlstate;i++)
6381: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6382: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6383: } /* End theta */
6384:
6385: trgradg =matrix(1,nlstate,1,npar);
6386:
6387: for(j=1; j<=nlstate;j++)
6388: for(theta=1; theta <=npar; theta++)
6389: trgradg[j][theta]=gradg[theta][j];
6390: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6391: /* printf("\nmgm mgp %d ",(int)age); */
6392: /* for(j=1; j<=nlstate;j++){ */
6393: /* printf(" %d ",j); */
6394: /* for(theta=1; theta <=npar; theta++) */
6395: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6396: /* printf("\n "); */
6397: /* } */
6398: /* } */
6399: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6400: /* printf("\n gradg %d ",(int)age); */
6401: /* for(j=1; j<=nlstate;j++){ */
6402: /* printf("%d ",j); */
6403: /* for(theta=1; theta <=npar; theta++) */
6404: /* printf("%d %lf ",theta,gradg[theta][j]); */
6405: /* printf("\n "); */
6406: /* } */
6407: /* } */
6408:
6409: for(i=1;i<=nlstate;i++)
6410: varbpl[i][(int)age] =0.;
6411: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6412: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6413: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6414: }else{
6415: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6416: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6417: }
6418: for(i=1;i<=nlstate;i++)
6419: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6420:
6421: fprintf(ficresvbl,"%.0f ",age );
6422: if(nresult >=1)
6423: fprintf(ficresvbl,"%d ",nres );
6424: for(i=1; i<=nlstate;i++)
6425: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6426: fprintf(ficresvbl,"\n");
6427: free_vector(gp,1,nlstate);
6428: free_vector(gm,1,nlstate);
6429: free_matrix(mgm,1,npar,1,nlstate);
6430: free_matrix(mgp,1,npar,1,nlstate);
6431: free_matrix(gradg,1,npar,1,nlstate);
6432: free_matrix(trgradg,1,nlstate,1,npar);
6433: } /* End age */
6434:
6435: free_vector(xp,1,npar);
6436: free_matrix(doldm,1,nlstate,1,npar);
6437: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6438:
6439: }
6440:
6441: /************ Variance of one-step probabilities ******************/
6442: 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 6443: {
6444: int i, j=0, k1, l1, tj;
6445: int k2, l2, j1, z1;
6446: int k=0, l;
6447: int first=1, first1, first2;
6448: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6449: double **dnewm,**doldm;
6450: double *xp;
6451: double *gp, *gm;
6452: double **gradg, **trgradg;
6453: double **mu;
6454: double age, cov[NCOVMAX+1];
6455: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6456: int theta;
6457: char fileresprob[FILENAMELENGTH];
6458: char fileresprobcov[FILENAMELENGTH];
6459: char fileresprobcor[FILENAMELENGTH];
6460: double ***varpij;
6461:
6462: strcpy(fileresprob,"PROB_");
6463: strcat(fileresprob,fileres);
6464: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6465: printf("Problem with resultfile: %s\n", fileresprob);
6466: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6467: }
6468: strcpy(fileresprobcov,"PROBCOV_");
6469: strcat(fileresprobcov,fileresu);
6470: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6471: printf("Problem with resultfile: %s\n", fileresprobcov);
6472: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6473: }
6474: strcpy(fileresprobcor,"PROBCOR_");
6475: strcat(fileresprobcor,fileresu);
6476: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6477: printf("Problem with resultfile: %s\n", fileresprobcor);
6478: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6479: }
6480: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6481: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6482: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6483: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6484: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6485: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6486: pstamp(ficresprob);
6487: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6488: fprintf(ficresprob,"# Age");
6489: pstamp(ficresprobcov);
6490: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6491: fprintf(ficresprobcov,"# Age");
6492: pstamp(ficresprobcor);
6493: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6494: fprintf(ficresprobcor,"# Age");
1.126 brouard 6495:
6496:
1.222 brouard 6497: for(i=1; i<=nlstate;i++)
6498: for(j=1; j<=(nlstate+ndeath);j++){
6499: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6500: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6501: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6502: }
6503: /* fprintf(ficresprob,"\n");
6504: fprintf(ficresprobcov,"\n");
6505: fprintf(ficresprobcor,"\n");
6506: */
6507: xp=vector(1,npar);
6508: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6509: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6510: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6511: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6512: first=1;
6513: fprintf(ficgp,"\n# Routine varprob");
6514: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6515: fprintf(fichtm,"\n");
6516:
1.288 ! brouard 6517: fprintf(fichtm,"\n<li><h4> <a href=\"%s\">Matrix of variance-covariance of one-step probabilities (drawings)</a></h4> this page is important in order to visualize confidence intervals and especially correlation between disability and recovery, or more generally, way in and way back. File %s</li>\n",optionfilehtmcov,optionfilehtmcov);
1.222 brouard 6518: 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);
6519: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6520: and drawn. It helps understanding how is the covariance between two incidences.\
6521: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6522: 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 6523: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6524: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6525: standard deviations wide on each axis. <br>\
6526: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6527: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6528: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6529:
1.222 brouard 6530: cov[1]=1;
6531: /* tj=cptcoveff; */
1.225 brouard 6532: tj = (int) pow(2,cptcoveff);
1.222 brouard 6533: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6534: j1=0;
1.224 brouard 6535: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6536: if (cptcovn>0) {
6537: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6538: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6539: fprintf(ficresprob, "**********\n#\n");
6540: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6541: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6542: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6543:
1.222 brouard 6544: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6545: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6546: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6547:
6548:
1.222 brouard 6549: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6550: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6551: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6552:
1.222 brouard 6553: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6554: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6555: fprintf(ficresprobcor, "**********\n#");
6556: if(invalidvarcomb[j1]){
6557: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6558: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6559: continue;
6560: }
6561: }
6562: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6563: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6564: gp=vector(1,(nlstate)*(nlstate+ndeath));
6565: gm=vector(1,(nlstate)*(nlstate+ndeath));
6566: for (age=bage; age<=fage; age ++){
6567: cov[2]=age;
6568: if(nagesqr==1)
6569: cov[3]= age*age;
6570: for (k=1; k<=cptcovn;k++) {
6571: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6572: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6573: * 1 1 1 1 1
6574: * 2 2 1 1 1
6575: * 3 1 2 1 1
6576: */
6577: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6578: }
6579: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6580: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6581: for (k=1; k<=cptcovprod;k++)
6582: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6583:
6584:
1.222 brouard 6585: for(theta=1; theta <=npar; theta++){
6586: for(i=1; i<=npar; i++)
6587: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6588:
1.222 brouard 6589: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6590:
1.222 brouard 6591: k=0;
6592: for(i=1; i<= (nlstate); i++){
6593: for(j=1; j<=(nlstate+ndeath);j++){
6594: k=k+1;
6595: gp[k]=pmmij[i][j];
6596: }
6597: }
1.220 brouard 6598:
1.222 brouard 6599: for(i=1; i<=npar; i++)
6600: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6601:
1.222 brouard 6602: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6603: k=0;
6604: for(i=1; i<=(nlstate); i++){
6605: for(j=1; j<=(nlstate+ndeath);j++){
6606: k=k+1;
6607: gm[k]=pmmij[i][j];
6608: }
6609: }
1.220 brouard 6610:
1.222 brouard 6611: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6612: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6613: }
1.126 brouard 6614:
1.222 brouard 6615: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6616: for(theta=1; theta <=npar; theta++)
6617: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6618:
1.222 brouard 6619: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6620: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6621:
1.222 brouard 6622: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6623:
1.222 brouard 6624: k=0;
6625: for(i=1; i<=(nlstate); i++){
6626: for(j=1; j<=(nlstate+ndeath);j++){
6627: k=k+1;
6628: mu[k][(int) age]=pmmij[i][j];
6629: }
6630: }
6631: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6632: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6633: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6634:
1.222 brouard 6635: /*printf("\n%d ",(int)age);
6636: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6637: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6638: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6639: }*/
1.220 brouard 6640:
1.222 brouard 6641: fprintf(ficresprob,"\n%d ",(int)age);
6642: fprintf(ficresprobcov,"\n%d ",(int)age);
6643: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6644:
1.222 brouard 6645: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6646: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6647: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6648: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6649: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6650: }
6651: i=0;
6652: for (k=1; k<=(nlstate);k++){
6653: for (l=1; l<=(nlstate+ndeath);l++){
6654: i++;
6655: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6656: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6657: for (j=1; j<=i;j++){
6658: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6659: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6660: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6661: }
6662: }
6663: }/* end of loop for state */
6664: } /* end of loop for age */
6665: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6666: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6667: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6668: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6669:
6670: /* Confidence intervalle of pij */
6671: /*
6672: fprintf(ficgp,"\nunset parametric;unset label");
6673: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6674: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6675: 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);
6676: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6677: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6678: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6679: */
6680:
6681: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6682: first1=1;first2=2;
6683: for (k2=1; k2<=(nlstate);k2++){
6684: for (l2=1; l2<=(nlstate+ndeath);l2++){
6685: if(l2==k2) continue;
6686: j=(k2-1)*(nlstate+ndeath)+l2;
6687: for (k1=1; k1<=(nlstate);k1++){
6688: for (l1=1; l1<=(nlstate+ndeath);l1++){
6689: if(l1==k1) continue;
6690: i=(k1-1)*(nlstate+ndeath)+l1;
6691: if(i<=j) continue;
6692: for (age=bage; age<=fage; age ++){
6693: if ((int)age %5==0){
6694: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6695: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6696: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6697: mu1=mu[i][(int) age]/stepm*YEARM ;
6698: mu2=mu[j][(int) age]/stepm*YEARM;
6699: c12=cv12/sqrt(v1*v2);
6700: /* Computing eigen value of matrix of covariance */
6701: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6702: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6703: if ((lc2 <0) || (lc1 <0) ){
6704: if(first2==1){
6705: first1=0;
6706: 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);
6707: }
6708: 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);
6709: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6710: /* lc2=fabs(lc2); */
6711: }
1.220 brouard 6712:
1.222 brouard 6713: /* Eigen vectors */
1.280 brouard 6714: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
6715: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6716: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
6717: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
6718: }else
6719: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 6720: /*v21=sqrt(1.-v11*v11); *//* error */
6721: v21=(lc1-v1)/cv12*v11;
6722: v12=-v21;
6723: v22=v11;
6724: tnalp=v21/v11;
6725: if(first1==1){
6726: first1=0;
6727: 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);
6728: }
6729: 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);
6730: /*printf(fignu*/
6731: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6732: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6733: if(first==1){
6734: first=0;
6735: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6736: fprintf(ficgp,"\nset parametric;unset label");
6737: 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);
6738: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6739: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6740: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6741: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6742: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6743: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6744: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6745: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6746: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6747: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6748: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6749: 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 6750: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
6751: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6752: }else{
6753: first=0;
6754: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6755: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6756: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6757: 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 6758: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6759: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6760: }/* if first */
6761: } /* age mod 5 */
6762: } /* end loop age */
6763: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6764: first=1;
6765: } /*l12 */
6766: } /* k12 */
6767: } /*l1 */
6768: }/* k1 */
6769: } /* loop on combination of covariates j1 */
6770: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6771: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6772: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6773: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6774: free_vector(xp,1,npar);
6775: fclose(ficresprob);
6776: fclose(ficresprobcov);
6777: fclose(ficresprobcor);
6778: fflush(ficgp);
6779: fflush(fichtmcov);
6780: }
1.126 brouard 6781:
6782:
6783: /******************* Printing html file ***********/
1.201 brouard 6784: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6785: int lastpass, int stepm, int weightopt, char model[],\
6786: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.258 brouard 6787: int popforecast, int mobilav, int prevfcast, int mobilavproj, int backcast, int estepm , \
1.273 brouard 6788: double jprev1, double mprev1,double anprev1, double dateprev1, double dateproj1, double dateback1, \
6789: double jprev2, double mprev2,double anprev2, double dateprev2, double dateproj2, double dateback2){
1.237 brouard 6790: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6791:
6792: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6793: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6794: </ul>");
1.237 brouard 6795: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6796: </ul>", model);
1.214 brouard 6797: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6798: 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",
6799: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6800: 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 6801: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6802: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6803: fprintf(fichtm,"\
6804: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6805: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6806: fprintf(fichtm,"\
1.217 brouard 6807: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6808: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6809: fprintf(fichtm,"\
1.288 ! brouard 6810: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6811: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6812: fprintf(fichtm,"\
1.288 ! brouard 6813: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 6814: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6815: fprintf(fichtm,"\
1.211 brouard 6816: - (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 6817: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6818: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6819: if(prevfcast==1){
6820: fprintf(fichtm,"\
6821: - Prevalence projections by age and states: \
1.201 brouard 6822: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6823: }
1.126 brouard 6824:
6825:
1.225 brouard 6826: m=pow(2,cptcoveff);
1.222 brouard 6827: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6828:
1.264 brouard 6829: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6830:
6831: jj1=0;
6832:
6833: fprintf(fichtm," \n<ul>");
6834: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6835: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6836: if(m != 1 && TKresult[nres]!= k1)
6837: continue;
6838: jj1++;
6839: if (cptcovn > 0) {
6840: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6841: for (cpt=1; cpt<=cptcoveff;cpt++){
6842: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6843: }
6844: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6845: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6846: }
6847: fprintf(fichtm,"\">");
6848:
6849: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6850: fprintf(fichtm,"************ Results for covariates");
6851: for (cpt=1; cpt<=cptcoveff;cpt++){
6852: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6853: }
6854: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6855: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6856: }
6857: if(invalidvarcomb[k1]){
6858: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
6859: continue;
6860: }
6861: fprintf(fichtm,"</a></li>");
6862: } /* cptcovn >0 */
6863: }
6864: fprintf(fichtm," \n</ul>");
6865:
1.222 brouard 6866: jj1=0;
1.237 brouard 6867:
6868: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6869: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6870: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6871: continue;
1.220 brouard 6872:
1.222 brouard 6873: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6874: jj1++;
6875: if (cptcovn > 0) {
1.264 brouard 6876: fprintf(fichtm,"\n<p><a name=\"rescov");
6877: for (cpt=1; cpt<=cptcoveff;cpt++){
6878: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6879: }
6880: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6881: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6882: }
6883: fprintf(fichtm,"\"</a>");
6884:
1.222 brouard 6885: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6886: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6887: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6888: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6889: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6890: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6891: }
1.237 brouard 6892: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6893: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6894: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6895: }
6896:
1.230 brouard 6897: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6898: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6899: if(invalidvarcomb[k1]){
6900: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6901: printf("\nCombination (%d) ignored because no cases \n",k1);
6902: continue;
6903: }
6904: }
6905: /* aij, bij */
1.259 brouard 6906: 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 6907: <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 6908: /* Pij */
1.241 brouard 6909: 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> \
6910: <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 6911: /* Quasi-incidences */
6912: 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 6913: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6914: 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 6915: 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> \
6916: <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 6917: /* Survival functions (period) in state j */
6918: for(cpt=1; cpt<=nlstate;cpt++){
1.241 brouard 6919: 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> \
6920: <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 6921: }
6922: /* State specific survival functions (period) */
6923: for(cpt=1; cpt<=nlstate;cpt++){
6924: fprintf(fichtm,"<br>\n- Survival functions from state %d in each live state and total.\
1.220 brouard 6925: Or probability to survive in various states (1 to %d) being in state %d at different ages. \
1.283 brouard 6926: <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 6927: }
1.288 ! brouard 6928: /* Period (forward stable) prevalence in each health state */
1.222 brouard 6929: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6930: 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> \
6931: <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 6932: }
6933: if(backcast==1){
1.288 ! brouard 6934: /* Backward prevalence in each health state */
1.222 brouard 6935: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6936: 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 6937: <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 6938: }
1.217 brouard 6939: }
1.222 brouard 6940: if(prevfcast==1){
1.288 ! brouard 6941: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 6942: for(cpt=1; cpt<=nlstate;cpt++){
1.288 ! brouard 6943: fprintf(fichtm,"<br>\n- Projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), from year %.1f up to year %.1f tending to period (stable) forward prevalence in state %d. Or probability to be in state %d being in an observed weighted state (from 1 to %d). <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
1.273 brouard 6944: <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 6945: }
6946: }
1.268 brouard 6947: if(backcast==1){
6948: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
6949: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 6950: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
6951: 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 \
6952: 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) \
6953: with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
6954: <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 6955: }
6956: }
1.220 brouard 6957:
1.222 brouard 6958: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 6959: 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> \
6960: <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 6961: }
6962: /* } /\* end i1 *\/ */
6963: }/* End k1 */
6964: fprintf(fichtm,"</ul>");
1.126 brouard 6965:
1.222 brouard 6966: fprintf(fichtm,"\
1.126 brouard 6967: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 6968: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 6969: - 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 6970: But because parameters are usually highly correlated (a higher incidence of disability \
6971: and a higher incidence of recovery can give very close observed transition) it might \
6972: be very useful to look not only at linear confidence intervals estimated from the \
6973: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
6974: (parameters) of the logistic regression, it might be more meaningful to visualize the \
6975: covariance matrix of the one-step probabilities. \
6976: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 6977:
1.222 brouard 6978: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
6979: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
6980: fprintf(fichtm,"\
1.126 brouard 6981: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6982: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 6983:
1.222 brouard 6984: fprintf(fichtm,"\
1.126 brouard 6985: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6986: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
6987: fprintf(fichtm,"\
1.126 brouard 6988: - 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): \
6989: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6990: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 6991: fprintf(fichtm,"\
1.126 brouard 6992: - (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): \
6993: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6994: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 6995: fprintf(fichtm,"\
1.288 ! brouard 6996: - Variances and covariances of health expectancies by age. Status (i) based health expectancies (in state j), e<sup>ij</sup> are weighted by the forward (period) prevalences in each state i (if popbased=1, an additional computation is done using the cross-sectional prevalences, i.e population based) (estepm=%d months): <a href=\"%s\">%s</a><br>\n",
1.222 brouard 6997: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
6998: fprintf(fichtm,"\
1.128 brouard 6999: - 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 7000: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
7001: fprintf(fichtm,"\
1.288 ! brouard 7002: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 7003: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 7004:
7005: /* if(popforecast==1) fprintf(fichtm,"\n */
7006: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
7007: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
7008: /* <br>",fileres,fileres,fileres,fileres); */
7009: /* else */
7010: /* 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 7011: fflush(fichtm);
7012: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 7013:
1.225 brouard 7014: m=pow(2,cptcoveff);
1.222 brouard 7015: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 7016:
1.222 brouard 7017: jj1=0;
1.237 brouard 7018:
1.241 brouard 7019: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 7020: for(k1=1; k1<=m;k1++){
1.253 brouard 7021: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7022: continue;
1.222 brouard 7023: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
7024: jj1++;
1.126 brouard 7025: if (cptcovn > 0) {
7026: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 7027: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 7028: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
7029: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
7030: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7031: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7032: }
7033:
1.126 brouard 7034: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 7035:
1.222 brouard 7036: if(invalidvarcomb[k1]){
7037: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
7038: continue;
7039: }
1.126 brouard 7040: }
7041: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 7042: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 7043: 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 7044: <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 7045: }
7046: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 7047: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
7048: true period expectancies (those weighted with period prevalences are also\
7049: drawn in addition to the population based expectancies computed using\
1.241 brouard 7050: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
7051: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 7052: /* } /\* end i1 *\/ */
7053: }/* End k1 */
1.241 brouard 7054: }/* End nres */
1.222 brouard 7055: fprintf(fichtm,"</ul>");
7056: fflush(fichtm);
1.126 brouard 7057: }
7058:
7059: /******************* Gnuplot file **************/
1.270 brouard 7060: 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 7061:
7062: char dirfileres[132],optfileres[132];
1.264 brouard 7063: char gplotcondition[132], gplotlabel[132];
1.237 brouard 7064: 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 7065: int lv=0, vlv=0, kl=0;
1.130 brouard 7066: int ng=0;
1.201 brouard 7067: int vpopbased;
1.223 brouard 7068: int ioffset; /* variable offset for columns */
1.270 brouard 7069: int iyearc=1; /* variable column for year of projection */
7070: int iagec=1; /* variable column for age of projection */
1.235 brouard 7071: int nres=0; /* Index of resultline */
1.266 brouard 7072: int istart=1; /* For starting graphs in projections */
1.219 brouard 7073:
1.126 brouard 7074: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
7075: /* printf("Problem with file %s",optionfilegnuplot); */
7076: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
7077: /* } */
7078:
7079: /*#ifdef windows */
7080: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 7081: /*#endif */
1.225 brouard 7082: m=pow(2,cptcoveff);
1.126 brouard 7083:
1.274 brouard 7084: /* diagram of the model */
7085: fprintf(ficgp,"\n#Diagram of the model \n");
7086: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
7087: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
7088: 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);
7089:
7090: 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);
7091: fprintf(ficgp,"\n#show arrow\nunset label\n");
7092: 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);
7093: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
7094: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
7095: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
7096: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
7097:
1.202 brouard 7098: /* Contribution to likelihood */
7099: /* Plot the probability implied in the likelihood */
1.223 brouard 7100: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
7101: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
7102: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
7103: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 7104: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 7105: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
7106: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 7107: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
7108: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
7109: 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));
7110: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
7111: 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));
7112: for (i=1; i<= nlstate ; i ++) {
7113: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
7114: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
7115: 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);
7116: for (j=2; j<= nlstate+ndeath ; j ++) {
7117: 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);
7118: }
7119: fprintf(ficgp,";\nset out; unset ylabel;\n");
7120: }
7121: /* 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 */
7122: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
7123: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
7124: fprintf(ficgp,"\nset out;unset log\n");
7125: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 7126:
1.126 brouard 7127: strcpy(dirfileres,optionfilefiname);
7128: strcpy(optfileres,"vpl");
1.223 brouard 7129: /* 1eme*/
1.238 brouard 7130: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
7131: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 7132: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 7133: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 7134: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7135: continue;
7136: /* We are interested in selected combination by the resultline */
1.246 brouard 7137: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 ! brouard 7138: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 7139: strcpy(gplotlabel,"(");
1.238 brouard 7140: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7141: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7142: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7143: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7144: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7145: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7146: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7147: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7148: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7149: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7150: }
7151: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7152: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7153: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7154: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7155: }
7156: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7157: /* printf("\n#\n"); */
1.238 brouard 7158: fprintf(ficgp,"\n#\n");
7159: if(invalidvarcomb[k1]){
1.260 brouard 7160: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7161: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7162: continue;
7163: }
1.235 brouard 7164:
1.241 brouard 7165: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7166: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 7167: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
7168: fprintf(ficgp,"set title \"Alive state %d %s\" font \"Helvetica,12\"\n",cpt,gplotlabel);
1.260 brouard 7169: 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);
7170: /* 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); */
7171: /* k1-1 error should be nres-1*/
1.238 brouard 7172: for (i=1; i<= nlstate ; i ++) {
7173: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7174: else fprintf(ficgp," %%*lf (%%*lf)");
7175: }
1.288 ! brouard 7176: fprintf(ficgp,"\" t\"Forward prevalence\" w l lt 0,\"%s\" every :::%d::%d u 1:($2==%d ? $3+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7177: for (i=1; i<= nlstate ; i ++) {
7178: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7179: else fprintf(ficgp," %%*lf (%%*lf)");
7180: }
1.260 brouard 7181: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7182: for (i=1; i<= nlstate ; i ++) {
7183: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7184: else fprintf(ficgp," %%*lf (%%*lf)");
7185: }
1.265 brouard 7186: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7187:
7188: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7189: if(cptcoveff ==0){
1.271 brouard 7190: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7191: }else{
7192: kl=0;
7193: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7194: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7195: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7196: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7197: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7198: vlv= nbcode[Tvaraff[k]][lv];
7199: kl++;
7200: /* 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 *\/ */
7201: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7202: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7203: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7204: if(k==cptcoveff){
7205: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7206: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7207: }else{
7208: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7209: kl++;
7210: }
7211: } /* end covariate */
7212: } /* end if no covariate */
7213:
1.238 brouard 7214: if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
7215: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7216: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7217: if(cptcoveff ==0){
1.245 brouard 7218: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7219: }else{
7220: kl=0;
7221: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7222: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7223: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7224: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7225: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7226: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7227: kl++;
1.238 brouard 7228: /* 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 *\/ */
7229: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7230: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7231: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7232: if(k==cptcoveff){
1.245 brouard 7233: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7234: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7235: }else{
7236: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7237: kl++;
7238: }
7239: } /* end covariate */
7240: } /* end if no covariate */
1.268 brouard 7241: if(backcast == 1){
7242: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7243: /* k1-1 error should be nres-1*/
7244: for (i=1; i<= nlstate ; i ++) {
7245: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7246: else fprintf(ficgp," %%*lf (%%*lf)");
7247: }
1.271 brouard 7248: 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 7249: for (i=1; i<= nlstate ; i ++) {
7250: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7251: else fprintf(ficgp," %%*lf (%%*lf)");
7252: }
1.276 brouard 7253: 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 7254: for (i=1; i<= nlstate ; i ++) {
7255: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7256: else fprintf(ficgp," %%*lf (%%*lf)");
7257: }
1.274 brouard 7258: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 7259: } /* end if backprojcast */
1.238 brouard 7260: } /* end if backcast */
1.276 brouard 7261: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
7262: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 7263: } /* nres */
1.201 brouard 7264: } /* k1 */
7265: } /* cpt */
1.235 brouard 7266:
7267:
1.126 brouard 7268: /*2 eme*/
1.238 brouard 7269: for (k1=1; k1<= m ; k1 ++){
7270: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7271: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7272: continue;
7273: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7274: strcpy(gplotlabel,"(");
1.238 brouard 7275: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7276: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7277: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7278: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7279: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7280: vlv= nbcode[Tvaraff[k]][lv];
7281: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7282: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7283: }
1.237 brouard 7284: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7285: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7286: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7287: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7288: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7289: }
1.264 brouard 7290: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7291: fprintf(ficgp,"\n#\n");
1.223 brouard 7292: if(invalidvarcomb[k1]){
7293: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7294: continue;
7295: }
1.219 brouard 7296:
1.241 brouard 7297: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7298: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7299: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7300: if(vpopbased==0){
1.238 brouard 7301: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7302: }else
1.238 brouard 7303: fprintf(ficgp,"\nreplot ");
7304: for (i=1; i<= nlstate+1 ; i ++) {
7305: k=2*i;
1.261 brouard 7306: 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 7307: for (j=1; j<= nlstate+1 ; j ++) {
7308: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7309: else fprintf(ficgp," %%*lf (%%*lf)");
7310: }
7311: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7312: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7313: 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 7314: for (j=1; j<= nlstate+1 ; j ++) {
7315: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7316: else fprintf(ficgp," %%*lf (%%*lf)");
7317: }
7318: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7319: 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 7320: for (j=1; j<= nlstate+1 ; j ++) {
7321: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7322: else fprintf(ficgp," %%*lf (%%*lf)");
7323: }
7324: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7325: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7326: } /* state */
7327: } /* vpopbased */
1.264 brouard 7328: 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 7329: } /* end nres */
7330: } /* k1 end 2 eme*/
7331:
7332:
7333: /*3eme*/
7334: for (k1=1; k1<= m ; k1 ++){
7335: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7336: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7337: continue;
7338:
7339: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7340: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7341: strcpy(gplotlabel,"(");
1.238 brouard 7342: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7343: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7344: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7345: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7346: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7347: vlv= nbcode[Tvaraff[k]][lv];
7348: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7349: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7350: }
7351: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7352: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7353: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7354: }
1.264 brouard 7355: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7356: fprintf(ficgp,"\n#\n");
7357: if(invalidvarcomb[k1]){
7358: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7359: continue;
7360: }
7361:
7362: /* k=2+nlstate*(2*cpt-2); */
7363: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7364: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7365: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7366: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7367: 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 7368: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7369: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7370: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7371: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7372: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7373: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7374:
1.238 brouard 7375: */
7376: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7377: 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 7378: /* 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 7379:
1.238 brouard 7380: }
1.261 brouard 7381: 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 7382: }
1.264 brouard 7383: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7384: } /* end nres */
7385: } /* end kl 3eme */
1.126 brouard 7386:
1.223 brouard 7387: /* 4eme */
1.201 brouard 7388: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7389: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7390: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7391: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7392: continue;
1.238 brouard 7393: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7394: strcpy(gplotlabel,"(");
1.238 brouard 7395: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7396: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7397: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7398: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7399: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7400: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7401: vlv= nbcode[Tvaraff[k]][lv];
7402: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7403: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7404: }
7405: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7406: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7407: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7408: }
1.264 brouard 7409: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7410: fprintf(ficgp,"\n#\n");
7411: if(invalidvarcomb[k1]){
7412: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7413: continue;
1.223 brouard 7414: }
1.238 brouard 7415:
1.241 brouard 7416: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7417: 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 7418: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7419: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7420: k=3;
7421: for (i=1; i<= nlstate ; i ++){
7422: if(i==1){
7423: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7424: }else{
7425: fprintf(ficgp,", '' ");
7426: }
7427: l=(nlstate+ndeath)*(i-1)+1;
7428: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7429: for (j=2; j<= nlstate+ndeath ; j ++)
7430: fprintf(ficgp,"+$%d",k+l+j-1);
7431: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7432: } /* nlstate */
1.264 brouard 7433: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7434: } /* end cpt state*/
7435: } /* end nres */
7436: } /* end covariate k1 */
7437:
1.220 brouard 7438: /* 5eme */
1.201 brouard 7439: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7440: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7441: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7442: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7443: continue;
1.238 brouard 7444: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7445: strcpy(gplotlabel,"(");
1.238 brouard 7446: 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);
7447: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7448: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7449: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7450: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7451: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7452: vlv= nbcode[Tvaraff[k]][lv];
7453: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7454: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7455: }
7456: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7457: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7458: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7459: }
1.264 brouard 7460: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7461: fprintf(ficgp,"\n#\n");
7462: if(invalidvarcomb[k1]){
7463: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7464: continue;
7465: }
1.227 brouard 7466:
1.241 brouard 7467: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7468: 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 7469: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7470: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7471: k=3;
7472: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7473: if(j==1)
7474: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7475: else
7476: fprintf(ficgp,", '' ");
7477: l=(nlstate+ndeath)*(cpt-1) +j;
7478: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7479: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7480: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7481: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7482: } /* nlstate */
7483: fprintf(ficgp,", '' ");
7484: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7485: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7486: l=(nlstate+ndeath)*(cpt-1) +j;
7487: if(j < nlstate)
7488: fprintf(ficgp,"$%d +",k+l);
7489: else
7490: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7491: }
1.264 brouard 7492: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7493: } /* end cpt state*/
7494: } /* end covariate */
7495: } /* end nres */
1.227 brouard 7496:
1.220 brouard 7497: /* 6eme */
1.202 brouard 7498: /* CV preval stable (period) for each covariate */
1.237 brouard 7499: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7500: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7501: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7502: continue;
1.255 brouard 7503: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7504: strcpy(gplotlabel,"(");
1.288 ! brouard 7505: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7506: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7507: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7508: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7509: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7510: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7511: vlv= nbcode[Tvaraff[k]][lv];
7512: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7513: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7514: }
1.237 brouard 7515: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7516: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7517: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7518: }
1.264 brouard 7519: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7520: fprintf(ficgp,"\n#\n");
1.223 brouard 7521: if(invalidvarcomb[k1]){
1.227 brouard 7522: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7523: continue;
1.223 brouard 7524: }
1.227 brouard 7525:
1.241 brouard 7526: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7527: 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 7528: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7529: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7530: k=3; /* Offset */
1.255 brouard 7531: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7532: if(i==1)
7533: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7534: else
7535: fprintf(ficgp,", '' ");
1.255 brouard 7536: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7537: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7538: for (j=2; j<= nlstate ; j ++)
7539: fprintf(ficgp,"+$%d",k+l+j-1);
7540: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7541: } /* nlstate */
1.264 brouard 7542: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7543: } /* end cpt state*/
7544: } /* end covariate */
1.227 brouard 7545:
7546:
1.220 brouard 7547: /* 7eme */
1.218 brouard 7548: if(backcast == 1){
1.288 ! brouard 7549: /* CV backward prevalence for each covariate */
1.237 brouard 7550: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7551: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7552: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7553: continue;
1.268 brouard 7554: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7555: strcpy(gplotlabel,"(");
1.288 ! brouard 7556: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7557: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7558: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7559: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7560: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7561: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7562: vlv= nbcode[Tvaraff[k]][lv];
7563: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7564: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7565: }
1.237 brouard 7566: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7567: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7568: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7569: }
1.264 brouard 7570: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7571: fprintf(ficgp,"\n#\n");
7572: if(invalidvarcomb[k1]){
7573: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7574: continue;
7575: }
7576:
1.241 brouard 7577: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7578: 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 7579: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7580: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7581: k=3; /* Offset */
1.268 brouard 7582: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7583: if(i==1)
7584: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7585: else
7586: fprintf(ficgp,", '' ");
7587: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7588: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7589: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7590: /* 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 7591: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7592: /* for (j=2; j<= nlstate ; j ++) */
7593: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7594: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7595: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7596: } /* nlstate */
1.264 brouard 7597: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7598: } /* end cpt state*/
7599: } /* end covariate */
7600: } /* End if backcast */
7601:
1.223 brouard 7602: /* 8eme */
1.218 brouard 7603: if(prevfcast==1){
1.288 ! brouard 7604: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 7605:
1.237 brouard 7606: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7607: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7608: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7609: continue;
1.211 brouard 7610: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7611: strcpy(gplotlabel,"(");
1.288 ! brouard 7612: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7613: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7614: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7615: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7616: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7617: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7618: vlv= nbcode[Tvaraff[k]][lv];
7619: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7620: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7621: }
1.237 brouard 7622: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7623: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7624: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7625: }
1.264 brouard 7626: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7627: fprintf(ficgp,"\n#\n");
7628: if(invalidvarcomb[k1]){
7629: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7630: continue;
7631: }
7632:
7633: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7634: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7635: 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 7636: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7637: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7638:
7639: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7640: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7641: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7642: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7643: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7644: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7645: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7646: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7647: if(i==istart){
1.227 brouard 7648: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7649: }else{
7650: fprintf(ficgp,",\\\n '' ");
7651: }
7652: if(cptcoveff ==0){ /* No covariate */
7653: ioffset=2; /* Age is in 2 */
7654: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7655: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7656: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7657: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7658: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7659: if(i==nlstate+1){
1.270 brouard 7660: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 7661: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7662: fprintf(ficgp,",\\\n '' ");
7663: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7664: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 7665: offyear, \
1.268 brouard 7666: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7667: }else
1.227 brouard 7668: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7669: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7670: }else{ /* more than 2 covariates */
1.270 brouard 7671: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7672: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7673: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7674: iyearc=ioffset-1;
7675: iagec=ioffset;
1.227 brouard 7676: fprintf(ficgp," u %d:(",ioffset);
7677: kl=0;
7678: strcpy(gplotcondition,"(");
7679: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7680: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7681: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7682: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7683: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7684: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7685: kl++;
7686: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7687: kl++;
7688: if(k <cptcoveff && cptcoveff>1)
7689: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7690: }
7691: strcpy(gplotcondition+strlen(gplotcondition),")");
7692: /* 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 *\/ */
7693: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7694: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7695: /* '' 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*/
7696: if(i==nlstate+1){
1.270 brouard 7697: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
7698: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 7699: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7700: fprintf(ficgp," u %d:(",iagec);
7701: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
7702: iyearc, iagec, offyear, \
7703: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 7704: /* '' 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 7705: }else{
7706: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7707: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7708: }
7709: } /* end if covariate */
7710: } /* nlstate */
1.264 brouard 7711: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7712: } /* end cpt state*/
7713: } /* end covariate */
7714: } /* End if prevfcast */
1.227 brouard 7715:
1.268 brouard 7716: if(backcast==1){
7717: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7718:
7719: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7720: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7721: if(m != 1 && TKresult[nres]!= k1)
7722: continue;
7723: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7724: strcpy(gplotlabel,"(");
7725: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7726: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7727: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7728: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7729: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7730: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7731: vlv= nbcode[Tvaraff[k]][lv];
7732: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7733: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7734: }
7735: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7736: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7737: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7738: }
7739: strcpy(gplotlabel+strlen(gplotlabel),")");
7740: fprintf(ficgp,"\n#\n");
7741: if(invalidvarcomb[k1]){
7742: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7743: continue;
7744: }
7745:
7746: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7747: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7748: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7749: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7750: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7751:
7752: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7753: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7754: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7755: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7756: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7757: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7758: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7759: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7760: if(i==istart){
7761: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
7762: }else{
7763: fprintf(ficgp,",\\\n '' ");
7764: }
7765: if(cptcoveff ==0){ /* No covariate */
7766: ioffset=2; /* Age is in 2 */
7767: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7768: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7769: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7770: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7771: fprintf(ficgp," u %d:(", ioffset);
7772: if(i==nlstate+1){
1.270 brouard 7773: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 7774: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7775: fprintf(ficgp,",\\\n '' ");
7776: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7777: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 7778: offbyear, \
7779: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7780: }else
7781: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
7782: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
7783: }else{ /* more than 2 covariates */
1.270 brouard 7784: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7785: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7786: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7787: iyearc=ioffset-1;
7788: iagec=ioffset;
1.268 brouard 7789: fprintf(ficgp," u %d:(",ioffset);
7790: kl=0;
7791: strcpy(gplotcondition,"(");
7792: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7793: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7794: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7795: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7796: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7797: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7798: kl++;
7799: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7800: kl++;
7801: if(k <cptcoveff && cptcoveff>1)
7802: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7803: }
7804: strcpy(gplotcondition+strlen(gplotcondition),")");
7805: /* 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 *\/ */
7806: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7807: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7808: /* '' 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*/
7809: if(i==nlstate+1){
1.270 brouard 7810: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
7811: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 7812: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7813: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 7814: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 7815: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
7816: iyearc,iagec,offbyear, \
7817: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 7818: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
7819: }else{
7820: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
7821: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
7822: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
7823: }
7824: } /* end if covariate */
7825: } /* nlstate */
7826: fprintf(ficgp,"\nset out; unset label;\n");
7827: } /* end cpt state*/
7828: } /* end covariate */
7829: } /* End if backcast */
7830:
1.227 brouard 7831:
1.238 brouard 7832: /* 9eme writing MLE parameters */
7833: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7834: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7835: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7836: for(k=1; k <=(nlstate+ndeath); k++){
7837: if (k != i) {
1.227 brouard 7838: fprintf(ficgp,"# current state %d\n",k);
7839: for(j=1; j <=ncovmodel; j++){
7840: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7841: jk++;
7842: }
7843: fprintf(ficgp,"\n");
1.126 brouard 7844: }
7845: }
1.223 brouard 7846: }
1.187 brouard 7847: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7848:
1.145 brouard 7849: /*goto avoid;*/
1.238 brouard 7850: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7851: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7852: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7853: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7854: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7855: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7856: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7857: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7858: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7859: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7860: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7861: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7862: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7863: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7864: fprintf(ficgp,"#\n");
1.223 brouard 7865: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7866: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7867: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7868: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 7869: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
7870: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7871: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 7872: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7873: continue;
1.264 brouard 7874: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
7875: strcpy(gplotlabel,"(");
1.276 brouard 7876: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.264 brouard 7877: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7878: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7879: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7880: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7881: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7882: vlv= nbcode[Tvaraff[k]][lv];
7883: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7884: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7885: }
1.237 brouard 7886: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7887: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7888: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7889: }
1.264 brouard 7890: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7891: fprintf(ficgp,"\n#\n");
1.264 brouard 7892: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 7893: fprintf(ficgp,"\nset key outside ");
7894: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
7895: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7896: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7897: if (ng==1){
7898: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7899: fprintf(ficgp,"\nunset log y");
7900: }else if (ng==2){
7901: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7902: fprintf(ficgp,"\nset log y");
7903: }else if (ng==3){
7904: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7905: fprintf(ficgp,"\nset log y");
7906: }else
7907: fprintf(ficgp,"\nunset title ");
7908: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7909: i=1;
7910: for(k2=1; k2<=nlstate; k2++) {
7911: k3=i;
7912: for(k=1; k<=(nlstate+ndeath); k++) {
7913: if (k != k2){
7914: switch( ng) {
7915: case 1:
7916: if(nagesqr==0)
7917: fprintf(ficgp," p%d+p%d*x",i,i+1);
7918: else /* nagesqr =1 */
7919: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7920: break;
7921: case 2: /* ng=2 */
7922: if(nagesqr==0)
7923: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
7924: else /* nagesqr =1 */
7925: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7926: break;
7927: case 3:
7928: if(nagesqr==0)
7929: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
7930: else /* nagesqr =1 */
7931: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
7932: break;
7933: }
7934: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 7935: ijp=1; /* product no age */
7936: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
7937: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 7938: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 7939: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7940: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
7941: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7942: if(DummyV[j]==0){
7943: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
7944: }else{ /* quantitative */
7945: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
7946: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7947: }
7948: ij++;
1.237 brouard 7949: }
1.268 brouard 7950: }
7951: }else if(cptcovprod >0){
7952: if(j==Tprod[ijp]) { /* */
7953: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
7954: if(ijp <=cptcovprod) { /* Product */
7955: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
7956: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
7957: /* 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)]); */
7958: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
7959: }else{ /* Vn is dummy and Vm is quanti */
7960: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
7961: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7962: }
7963: }else{ /* Vn*Vm Vn is quanti */
7964: if(DummyV[Tvard[ijp][2]]==0){
7965: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
7966: }else{ /* Both quanti */
7967: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7968: }
1.237 brouard 7969: }
1.268 brouard 7970: ijp++;
1.237 brouard 7971: }
1.268 brouard 7972: } /* end Tprod */
1.237 brouard 7973: } else{ /* simple covariate */
1.264 brouard 7974: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 7975: if(Dummy[j]==0){
7976: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
7977: }else{ /* quantitative */
7978: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 7979: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 7980: }
1.237 brouard 7981: } /* end simple */
7982: } /* end j */
1.223 brouard 7983: }else{
7984: i=i-ncovmodel;
7985: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
7986: fprintf(ficgp," (1.");
7987: }
1.227 brouard 7988:
1.223 brouard 7989: if(ng != 1){
7990: fprintf(ficgp,")/(1");
1.227 brouard 7991:
1.264 brouard 7992: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 7993: if(nagesqr==0)
1.264 brouard 7994: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 7995: else /* nagesqr =1 */
1.264 brouard 7996: 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 7997:
1.223 brouard 7998: ij=1;
7999: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 8000: if(cptcovage >0){
8001: if((j-2)==Tage[ij]) { /* Bug valgrind */
8002: if(ij <=cptcovage) { /* Bug valgrind */
8003: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
8004: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
8005: ij++;
8006: }
8007: }
8008: }else
8009: 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 8010: }
8011: fprintf(ficgp,")");
8012: }
8013: fprintf(ficgp,")");
8014: if(ng ==2)
1.276 brouard 8015: 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 8016: else /* ng= 3 */
1.276 brouard 8017: 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 8018: }else{ /* end ng <> 1 */
8019: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 8020: 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 8021: }
8022: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
8023: fprintf(ficgp,",");
8024: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
8025: fprintf(ficgp,",");
8026: i=i+ncovmodel;
8027: } /* end k */
8028: } /* end k2 */
1.276 brouard 8029: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
8030: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.264 brouard 8031: } /* end k1 */
1.223 brouard 8032: } /* end ng */
8033: /* avoid: */
8034: fflush(ficgp);
1.126 brouard 8035: } /* end gnuplot */
8036:
8037:
8038: /*************** Moving average **************/
1.219 brouard 8039: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 8040: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 8041:
1.222 brouard 8042: int i, cpt, cptcod;
8043: int modcovmax =1;
8044: int mobilavrange, mob;
8045: int iage=0;
1.288 ! brouard 8046: int firstA1=0, firstA2=0;
1.222 brouard 8047:
1.266 brouard 8048: double sum=0., sumr=0.;
1.222 brouard 8049: double age;
1.266 brouard 8050: double *sumnewp, *sumnewm, *sumnewmr;
8051: double *agemingood, *agemaxgood;
8052: double *agemingoodr, *agemaxgoodr;
1.222 brouard 8053:
8054:
1.278 brouard 8055: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
8056: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 8057:
8058: sumnewp = vector(1,ncovcombmax);
8059: sumnewm = vector(1,ncovcombmax);
1.266 brouard 8060: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 8061: agemingood = vector(1,ncovcombmax);
1.266 brouard 8062: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 8063: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 8064: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 8065:
8066: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 8067: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 8068: sumnewp[cptcod]=0.;
1.266 brouard 8069: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
8070: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 8071: }
8072: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
8073:
1.266 brouard 8074: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
8075: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 8076: else mobilavrange=mobilav;
8077: for (age=bage; age<=fage; age++)
8078: for (i=1; i<=nlstate;i++)
8079: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
8080: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8081: /* We keep the original values on the extreme ages bage, fage and for
8082: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
8083: we use a 5 terms etc. until the borders are no more concerned.
8084: */
8085: for (mob=3;mob <=mobilavrange;mob=mob+2){
8086: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 8087: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
8088: sumnewm[cptcod]=0.;
8089: for (i=1; i<=nlstate;i++){
1.222 brouard 8090: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
8091: for (cpt=1;cpt<=(mob-1)/2;cpt++){
8092: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
8093: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
8094: }
8095: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 8096: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8097: } /* end i */
8098: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
8099: } /* end cptcod */
1.222 brouard 8100: }/* end age */
8101: }/* end mob */
1.266 brouard 8102: }else{
8103: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 8104: return -1;
1.266 brouard 8105: }
8106:
8107: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 8108: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
8109: if(invalidvarcomb[cptcod]){
8110: printf("\nCombination (%d) ignored because no cases \n",cptcod);
8111: continue;
8112: }
1.219 brouard 8113:
1.266 brouard 8114: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
8115: sumnewm[cptcod]=0.;
8116: sumnewmr[cptcod]=0.;
8117: for (i=1; i<=nlstate;i++){
8118: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8119: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8120: }
8121: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8122: agemingoodr[cptcod]=age;
8123: }
8124: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8125: agemingood[cptcod]=age;
8126: }
8127: } /* age */
8128: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 8129: sumnewm[cptcod]=0.;
1.266 brouard 8130: sumnewmr[cptcod]=0.;
1.222 brouard 8131: for (i=1; i<=nlstate;i++){
8132: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8133: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8134: }
8135: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8136: agemaxgoodr[cptcod]=age;
1.222 brouard 8137: }
8138: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 8139: agemaxgood[cptcod]=age;
8140: }
8141: } /* age */
8142: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
8143: /* but they will change */
1.288 ! brouard 8144: firstA1=0;firstA2=0;
1.266 brouard 8145: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
8146: sumnewm[cptcod]=0.;
8147: sumnewmr[cptcod]=0.;
8148: for (i=1; i<=nlstate;i++){
8149: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8150: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8151: }
8152: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8153: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8154: agemaxgoodr[cptcod]=age; /* age min */
8155: for (i=1; i<=nlstate;i++)
8156: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8157: }else{ /* bad we change the value with the values of good ages */
8158: for (i=1; i<=nlstate;i++){
8159: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8160: } /* i */
8161: } /* end bad */
8162: }else{
8163: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8164: agemaxgood[cptcod]=age;
8165: }else{ /* bad we change the value with the values of good ages */
8166: for (i=1; i<=nlstate;i++){
8167: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8168: } /* i */
8169: } /* end bad */
8170: }/* end else */
8171: sum=0.;sumr=0.;
8172: for (i=1; i<=nlstate;i++){
8173: sum+=mobaverage[(int)age][i][cptcod];
8174: sumr+=probs[(int)age][i][cptcod];
8175: }
8176: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 ! brouard 8177: if(!firstA1){
! 8178: firstA1=1;
! 8179: printf("Moving average A1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you increase bage=%d. Others in log file...\n",cptcod,sumr, (int)age, (int)bage);
! 8180: }
! 8181: fprintf(ficlog,"Moving average A1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you increase bage=%d\n",cptcod,sumr, (int)age, (int)bage);
1.266 brouard 8182: } /* end bad */
8183: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8184: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 ! brouard 8185: if(!firstA2){
! 8186: firstA2=1;
! 8187: printf("Moving average A2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase bage=%d. Others in log file...\n",cptcod,sumr, (int)age, (int)bage);
! 8188: }
! 8189: fprintf(ficlog,"Moving average A2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase bage=%d\n",cptcod,sumr, (int)age, (int)bage);
1.222 brouard 8190: } /* end bad */
8191: }/* age */
1.266 brouard 8192:
8193: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8194: sumnewm[cptcod]=0.;
1.266 brouard 8195: sumnewmr[cptcod]=0.;
1.222 brouard 8196: for (i=1; i<=nlstate;i++){
8197: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8198: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8199: }
8200: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8201: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8202: agemingoodr[cptcod]=age;
8203: for (i=1; i<=nlstate;i++)
8204: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8205: }else{ /* bad we change the value with the values of good ages */
8206: for (i=1; i<=nlstate;i++){
8207: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8208: } /* i */
8209: } /* end bad */
8210: }else{
8211: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8212: agemingood[cptcod]=age;
8213: }else{ /* bad */
8214: for (i=1; i<=nlstate;i++){
8215: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8216: } /* i */
8217: } /* end bad */
8218: }/* end else */
8219: sum=0.;sumr=0.;
8220: for (i=1; i<=nlstate;i++){
8221: sum+=mobaverage[(int)age][i][cptcod];
8222: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8223: }
1.266 brouard 8224: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8225: 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 8226: } /* end bad */
8227: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8228: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8229: 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 8230: } /* end bad */
8231: }/* age */
1.266 brouard 8232:
1.222 brouard 8233:
8234: for (age=bage; age<=fage; age++){
1.235 brouard 8235: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8236: sumnewp[cptcod]=0.;
8237: sumnewm[cptcod]=0.;
8238: for (i=1; i<=nlstate;i++){
8239: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8240: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8241: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8242: }
8243: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8244: }
8245: /* printf("\n"); */
8246: /* } */
1.266 brouard 8247:
1.222 brouard 8248: /* brutal averaging */
1.266 brouard 8249: /* for (i=1; i<=nlstate;i++){ */
8250: /* for (age=1; age<=bage; age++){ */
8251: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8252: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8253: /* } */
8254: /* for (age=fage; age<=AGESUP; age++){ */
8255: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8256: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8257: /* } */
8258: /* } /\* end i status *\/ */
8259: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8260: /* for (age=1; age<=AGESUP; age++){ */
8261: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8262: /* mobaverage[(int)age][i][cptcod]=0.; */
8263: /* } */
8264: /* } */
1.222 brouard 8265: }/* end cptcod */
1.266 brouard 8266: free_vector(agemaxgoodr,1, ncovcombmax);
8267: free_vector(agemaxgood,1, ncovcombmax);
8268: free_vector(agemingood,1, ncovcombmax);
8269: free_vector(agemingoodr,1, ncovcombmax);
8270: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8271: free_vector(sumnewm,1, ncovcombmax);
8272: free_vector(sumnewp,1, ncovcombmax);
8273: return 0;
8274: }/* End movingaverage */
1.218 brouard 8275:
1.126 brouard 8276:
8277: /************** Forecasting ******************/
1.269 brouard 8278: 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 8279: /* proj1, year, month, day of starting projection
8280: agemin, agemax range of age
8281: dateprev1 dateprev2 range of dates during which prevalence is computed
8282: anproj2 year of en of projection (same day and month as proj1).
8283: */
1.267 brouard 8284: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8285: double agec; /* generic age */
8286: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
8287: double *popeffectif,*popcount;
8288: double ***p3mat;
1.218 brouard 8289: /* double ***mobaverage; */
1.126 brouard 8290: char fileresf[FILENAMELENGTH];
8291:
8292: agelim=AGESUP;
1.211 brouard 8293: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8294: in each health status at the date of interview (if between dateprev1 and dateprev2).
8295: We still use firstpass and lastpass as another selection.
8296: */
1.214 brouard 8297: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8298: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8299:
1.201 brouard 8300: strcpy(fileresf,"F_");
8301: strcat(fileresf,fileresu);
1.126 brouard 8302: if((ficresf=fopen(fileresf,"w"))==NULL) {
8303: printf("Problem with forecast resultfile: %s\n", fileresf);
8304: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8305: }
1.235 brouard 8306: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8307: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8308:
1.225 brouard 8309: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8310:
8311:
8312: stepsize=(int) (stepm+YEARM-1)/YEARM;
8313: if (stepm<=12) stepsize=1;
8314: if(estepm < stepm){
8315: printf ("Problem %d lower than %d\n",estepm, stepm);
8316: }
1.270 brouard 8317: else{
8318: hstepm=estepm;
8319: }
8320: if(estepm > stepm){ /* Yes every two year */
8321: stepsize=2;
8322: }
1.126 brouard 8323:
8324: hstepm=hstepm/stepm;
8325: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8326: fractional in yp1 */
8327: anprojmean=yp;
8328: yp2=modf((yp1*12),&yp);
8329: mprojmean=yp;
8330: yp1=modf((yp2*30.5),&yp);
8331: jprojmean=yp;
8332: if(jprojmean==0) jprojmean=1;
8333: if(mprojmean==0) jprojmean=1;
8334:
1.227 brouard 8335: i1=pow(2,cptcoveff);
1.126 brouard 8336: if (cptcovn < 1){i1=1;}
8337:
8338: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
8339:
8340: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8341:
1.126 brouard 8342: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8343: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8344: for(k=1; k<=i1;k++){
1.253 brouard 8345: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8346: continue;
1.227 brouard 8347: if(invalidvarcomb[k]){
8348: printf("\nCombination (%d) projection ignored because no cases \n",k);
8349: continue;
8350: }
8351: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8352: for(j=1;j<=cptcoveff;j++) {
8353: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8354: }
1.235 brouard 8355: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8356: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8357: }
1.227 brouard 8358: fprintf(ficresf," yearproj age");
8359: for(j=1; j<=nlstate+ndeath;j++){
8360: for(i=1; i<=nlstate;i++)
8361: fprintf(ficresf," p%d%d",i,j);
8362: fprintf(ficresf," wp.%d",j);
8363: }
8364: for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {
8365: fprintf(ficresf,"\n");
8366: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
1.270 brouard 8367: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8368: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8369: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8370: nhstepm = nhstepm/hstepm;
8371: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8372: oldm=oldms;savm=savms;
1.268 brouard 8373: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8374: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8375: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8376: for (h=0; h<=nhstepm; h++){
8377: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8378: break;
8379: }
8380: }
8381: fprintf(ficresf,"\n");
8382: for(j=1;j<=cptcoveff;j++)
8383: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8384: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
8385:
8386: for(j=1; j<=nlstate+ndeath;j++) {
8387: ppij=0.;
8388: for(i=1; i<=nlstate;i++) {
1.278 brouard 8389: if (mobilav>=1)
8390: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
8391: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
8392: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
8393: }
1.268 brouard 8394: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8395: } /* end i */
8396: fprintf(ficresf," %.3f", ppij);
8397: }/* end j */
1.227 brouard 8398: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8399: } /* end agec */
1.266 brouard 8400: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8401: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8402: } /* end yearp */
8403: } /* end k */
1.219 brouard 8404:
1.126 brouard 8405: fclose(ficresf);
1.215 brouard 8406: printf("End of Computing forecasting \n");
8407: fprintf(ficlog,"End of Computing forecasting\n");
8408:
1.126 brouard 8409: }
8410:
1.269 brouard 8411: /************** Back Forecasting ******************/
8412: 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 8413: /* back1, year, month, day of starting backection
8414: agemin, agemax range of age
8415: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8416: anback2 year of end of backprojection (same day and month as back1).
8417: prevacurrent and prev are prevalences.
1.267 brouard 8418: */
8419: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8420: double agec; /* generic age */
1.268 brouard 8421: double agelim, ppij, ppi, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
1.267 brouard 8422: double *popeffectif,*popcount;
8423: double ***p3mat;
8424: /* double ***mobaverage; */
8425: char fileresfb[FILENAMELENGTH];
8426:
1.268 brouard 8427: agelim=AGEINF;
1.267 brouard 8428: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8429: in each health status at the date of interview (if between dateprev1 and dateprev2).
8430: We still use firstpass and lastpass as another selection.
8431: */
8432: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8433: /* firstpass, lastpass, stepm, weightopt, model); */
8434:
8435: /*Do we need to compute prevalence again?*/
8436:
8437: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8438:
8439: strcpy(fileresfb,"FB_");
8440: strcat(fileresfb,fileresu);
8441: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8442: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8443: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8444: }
8445: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8446: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8447:
8448: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8449:
8450:
8451: stepsize=(int) (stepm+YEARM-1)/YEARM;
8452: if (stepm<=12) stepsize=1;
8453: if(estepm < stepm){
8454: printf ("Problem %d lower than %d\n",estepm, stepm);
8455: }
1.270 brouard 8456: else{
8457: hstepm=estepm;
8458: }
8459: if(estepm >= stepm){ /* Yes every two year */
8460: stepsize=2;
8461: }
1.267 brouard 8462:
8463: hstepm=hstepm/stepm;
8464: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8465: fractional in yp1 */
8466: anprojmean=yp;
8467: yp2=modf((yp1*12),&yp);
8468: mprojmean=yp;
8469: yp1=modf((yp2*30.5),&yp);
8470: jprojmean=yp;
8471: if(jprojmean==0) jprojmean=1;
8472: if(mprojmean==0) jprojmean=1;
8473:
8474: i1=pow(2,cptcoveff);
8475: if (cptcovn < 1){i1=1;}
8476:
8477: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.268 brouard 8478: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8479:
8480: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8481:
8482: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8483: for(k=1; k<=i1;k++){
8484: if(i1 != 1 && TKresult[nres]!= k)
8485: continue;
8486: if(invalidvarcomb[k]){
8487: printf("\nCombination (%d) projection ignored because no cases \n",k);
8488: continue;
8489: }
1.268 brouard 8490: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8491: for(j=1;j<=cptcoveff;j++) {
8492: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8493: }
8494: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8495: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8496: }
8497: fprintf(ficresfb," yearbproj age");
8498: for(j=1; j<=nlstate+ndeath;j++){
8499: for(i=1; i<=nlstate;i++)
1.268 brouard 8500: fprintf(ficresfb," b%d%d",i,j);
8501: fprintf(ficresfb," b.%d",j);
1.267 brouard 8502: }
8503: for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) {
8504: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8505: fprintf(ficresfb,"\n");
8506: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp);
1.273 brouard 8507: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 8508: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8509: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8510: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8511: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8512: nhstepm = nhstepm/hstepm;
8513: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8514: oldm=oldms;savm=savms;
1.268 brouard 8515: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8516: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8517: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8518: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8519: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8520: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8521: for (h=0; h<=nhstepm; h++){
1.268 brouard 8522: if (h*hstepm/YEARM*stepm ==-yearp) {
8523: break;
8524: }
8525: }
8526: fprintf(ficresfb,"\n");
8527: for(j=1;j<=cptcoveff;j++)
8528: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8529: fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec-h*hstepm/YEARM*stepm);
8530: for(i=1; i<=nlstate+ndeath;i++) {
8531: ppij=0.;ppi=0.;
8532: for(j=1; j<=nlstate;j++) {
8533: /* if (mobilav==1) */
1.269 brouard 8534: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8535: ppi=ppi+prevacurrent[(int)agec][j][k];
8536: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8537: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8538: /* else { */
8539: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8540: /* } */
1.268 brouard 8541: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8542: } /* end j */
8543: if(ppi <0.99){
8544: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8545: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8546: }
8547: fprintf(ficresfb," %.3f", ppij);
8548: }/* end j */
1.267 brouard 8549: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8550: } /* end agec */
8551: } /* end yearp */
8552: } /* end k */
1.217 brouard 8553:
1.267 brouard 8554: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8555:
1.267 brouard 8556: fclose(ficresfb);
8557: printf("End of Computing Back forecasting \n");
8558: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8559:
1.267 brouard 8560: }
1.217 brouard 8561:
1.269 brouard 8562: /* Variance of prevalence limit: varprlim */
8563: void varprlim(char fileresu[], int nresult, double ***prevacurrent, int mobilavproj, double bage, double fage, double **prlim, int *ncvyearp, double ftolpl, double p[], double **matcov, double *delti, int stepm, int cptcoveff){
1.288 ! brouard 8564: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 8565:
8566: char fileresvpl[FILENAMELENGTH];
8567: FILE *ficresvpl;
8568: double **oldm, **savm;
8569: double **varpl; /* Variances of prevalence limits by age */
8570: int i1, k, nres, j ;
8571:
8572: strcpy(fileresvpl,"VPL_");
8573: strcat(fileresvpl,fileresu);
8574: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 ! brouard 8575: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 8576: exit(0);
8577: }
1.288 ! brouard 8578: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
! 8579: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 8580:
8581: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8582: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8583:
8584: i1=pow(2,cptcoveff);
8585: if (cptcovn < 1){i1=1;}
8586:
8587: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8588: for(k=1; k<=i1;k++){
8589: if(i1 != 1 && TKresult[nres]!= k)
8590: continue;
8591: fprintf(ficresvpl,"\n#****** ");
8592: printf("\n#****** ");
8593: fprintf(ficlog,"\n#****** ");
8594: for(j=1;j<=cptcoveff;j++) {
8595: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8596: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8597: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8598: }
8599: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8600: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8601: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8602: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8603: }
8604: fprintf(ficresvpl,"******\n");
8605: printf("******\n");
8606: fprintf(ficlog,"******\n");
8607:
8608: varpl=matrix(1,nlstate,(int) bage, (int) fage);
8609: oldm=oldms;savm=savms;
8610: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
8611: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
8612: /*}*/
8613: }
8614:
8615: fclose(ficresvpl);
1.288 ! brouard 8616: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
! 8617: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 8618:
8619: }
8620: /* Variance of back prevalence: varbprlim */
8621: 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){
8622: /*------- Variance of back (stable) prevalence------*/
8623:
8624: char fileresvbl[FILENAMELENGTH];
8625: FILE *ficresvbl;
8626:
8627: double **oldm, **savm;
8628: double **varbpl; /* Variances of back prevalence limits by age */
8629: int i1, k, nres, j ;
8630:
8631: strcpy(fileresvbl,"VBL_");
8632: strcat(fileresvbl,fileresu);
8633: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
8634: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
8635: exit(0);
8636: }
8637: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
8638: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
8639:
8640:
8641: i1=pow(2,cptcoveff);
8642: if (cptcovn < 1){i1=1;}
8643:
8644: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8645: for(k=1; k<=i1;k++){
8646: if(i1 != 1 && TKresult[nres]!= k)
8647: continue;
8648: fprintf(ficresvbl,"\n#****** ");
8649: printf("\n#****** ");
8650: fprintf(ficlog,"\n#****** ");
8651: for(j=1;j<=cptcoveff;j++) {
8652: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8653: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8654: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8655: }
8656: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8657: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8658: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8659: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8660: }
8661: fprintf(ficresvbl,"******\n");
8662: printf("******\n");
8663: fprintf(ficlog,"******\n");
8664:
8665: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
8666: oldm=oldms;savm=savms;
8667:
8668: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
8669: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
8670: /*}*/
8671: }
8672:
8673: fclose(ficresvbl);
8674: printf("done variance-covariance of back prevalence\n");fflush(stdout);
8675: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
8676:
8677: } /* End of varbprlim */
8678:
1.126 brouard 8679: /************** Forecasting *****not tested NB*************/
1.227 brouard 8680: /* 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 8681:
1.227 brouard 8682: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8683: /* int *popage; */
8684: /* double calagedatem, agelim, kk1, kk2; */
8685: /* double *popeffectif,*popcount; */
8686: /* double ***p3mat,***tabpop,***tabpopprev; */
8687: /* /\* double ***mobaverage; *\/ */
8688: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8689:
1.227 brouard 8690: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8691: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8692: /* agelim=AGESUP; */
8693: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8694:
1.227 brouard 8695: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8696:
8697:
1.227 brouard 8698: /* strcpy(filerespop,"POP_"); */
8699: /* strcat(filerespop,fileresu); */
8700: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8701: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8702: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8703: /* } */
8704: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8705: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8706:
1.227 brouard 8707: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8708:
1.227 brouard 8709: /* /\* if (mobilav!=0) { *\/ */
8710: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8711: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8712: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8713: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8714: /* /\* } *\/ */
8715: /* /\* } *\/ */
1.126 brouard 8716:
1.227 brouard 8717: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8718: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8719:
1.227 brouard 8720: /* agelim=AGESUP; */
1.126 brouard 8721:
1.227 brouard 8722: /* hstepm=1; */
8723: /* hstepm=hstepm/stepm; */
1.218 brouard 8724:
1.227 brouard 8725: /* if (popforecast==1) { */
8726: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8727: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8728: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8729: /* } */
8730: /* popage=ivector(0,AGESUP); */
8731: /* popeffectif=vector(0,AGESUP); */
8732: /* popcount=vector(0,AGESUP); */
1.126 brouard 8733:
1.227 brouard 8734: /* i=1; */
8735: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8736:
1.227 brouard 8737: /* imx=i; */
8738: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8739: /* } */
1.218 brouard 8740:
1.227 brouard 8741: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8742: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8743: /* k=k+1; */
8744: /* fprintf(ficrespop,"\n#******"); */
8745: /* for(j=1;j<=cptcoveff;j++) { */
8746: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8747: /* } */
8748: /* fprintf(ficrespop,"******\n"); */
8749: /* fprintf(ficrespop,"# Age"); */
8750: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8751: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8752:
1.227 brouard 8753: /* for (cpt=0; cpt<=0;cpt++) { */
8754: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8755:
1.227 brouard 8756: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8757: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8758: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8759:
1.227 brouard 8760: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8761: /* oldm=oldms;savm=savms; */
8762: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8763:
1.227 brouard 8764: /* for (h=0; h<=nhstepm; h++){ */
8765: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8766: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8767: /* } */
8768: /* for(j=1; j<=nlstate+ndeath;j++) { */
8769: /* kk1=0.;kk2=0; */
8770: /* for(i=1; i<=nlstate;i++) { */
8771: /* if (mobilav==1) */
8772: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8773: /* else { */
8774: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8775: /* } */
8776: /* } */
8777: /* if (h==(int)(calagedatem+12*cpt)){ */
8778: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8779: /* /\*fprintf(ficrespop," %.3f", kk1); */
8780: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8781: /* } */
8782: /* } */
8783: /* for(i=1; i<=nlstate;i++){ */
8784: /* kk1=0.; */
8785: /* for(j=1; j<=nlstate;j++){ */
8786: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8787: /* } */
8788: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8789: /* } */
1.218 brouard 8790:
1.227 brouard 8791: /* if (h==(int)(calagedatem+12*cpt)) */
8792: /* for(j=1; j<=nlstate;j++) */
8793: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8794: /* } */
8795: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8796: /* } */
8797: /* } */
1.218 brouard 8798:
1.227 brouard 8799: /* /\******\/ */
1.218 brouard 8800:
1.227 brouard 8801: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8802: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8803: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8804: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8805: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8806:
1.227 brouard 8807: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8808: /* oldm=oldms;savm=savms; */
8809: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8810: /* for (h=0; h<=nhstepm; h++){ */
8811: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8812: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8813: /* } */
8814: /* for(j=1; j<=nlstate+ndeath;j++) { */
8815: /* kk1=0.;kk2=0; */
8816: /* for(i=1; i<=nlstate;i++) { */
8817: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8818: /* } */
8819: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8820: /* } */
8821: /* } */
8822: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8823: /* } */
8824: /* } */
8825: /* } */
8826: /* } */
1.218 brouard 8827:
1.227 brouard 8828: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8829:
1.227 brouard 8830: /* if (popforecast==1) { */
8831: /* free_ivector(popage,0,AGESUP); */
8832: /* free_vector(popeffectif,0,AGESUP); */
8833: /* free_vector(popcount,0,AGESUP); */
8834: /* } */
8835: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8836: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8837: /* fclose(ficrespop); */
8838: /* } /\* End of popforecast *\/ */
1.218 brouard 8839:
1.126 brouard 8840: int fileappend(FILE *fichier, char *optionfich)
8841: {
8842: if((fichier=fopen(optionfich,"a"))==NULL) {
8843: printf("Problem with file: %s\n", optionfich);
8844: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8845: return (0);
8846: }
8847: fflush(fichier);
8848: return (1);
8849: }
8850:
8851:
8852: /**************** function prwizard **********************/
8853: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8854: {
8855:
8856: /* Wizard to print covariance matrix template */
8857:
1.164 brouard 8858: char ca[32], cb[32];
8859: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8860: int numlinepar;
8861:
8862: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8863: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8864: for(i=1; i <=nlstate; i++){
8865: jj=0;
8866: for(j=1; j <=nlstate+ndeath; j++){
8867: if(j==i) continue;
8868: jj++;
8869: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8870: printf("%1d%1d",i,j);
8871: fprintf(ficparo,"%1d%1d",i,j);
8872: for(k=1; k<=ncovmodel;k++){
8873: /* printf(" %lf",param[i][j][k]); */
8874: /* fprintf(ficparo," %lf",param[i][j][k]); */
8875: printf(" 0.");
8876: fprintf(ficparo," 0.");
8877: }
8878: printf("\n");
8879: fprintf(ficparo,"\n");
8880: }
8881: }
8882: printf("# Scales (for hessian or gradient estimation)\n");
8883: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8884: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8885: for(i=1; i <=nlstate; i++){
8886: jj=0;
8887: for(j=1; j <=nlstate+ndeath; j++){
8888: if(j==i) continue;
8889: jj++;
8890: fprintf(ficparo,"%1d%1d",i,j);
8891: printf("%1d%1d",i,j);
8892: fflush(stdout);
8893: for(k=1; k<=ncovmodel;k++){
8894: /* printf(" %le",delti3[i][j][k]); */
8895: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8896: printf(" 0.");
8897: fprintf(ficparo," 0.");
8898: }
8899: numlinepar++;
8900: printf("\n");
8901: fprintf(ficparo,"\n");
8902: }
8903: }
8904: printf("# Covariance matrix\n");
8905: /* # 121 Var(a12)\n\ */
8906: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8907: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
8908: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
8909: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
8910: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
8911: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
8912: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8913: fflush(stdout);
8914: fprintf(ficparo,"# Covariance matrix\n");
8915: /* # 121 Var(a12)\n\ */
8916: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8917: /* # ...\n\ */
8918: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8919:
8920: for(itimes=1;itimes<=2;itimes++){
8921: jj=0;
8922: for(i=1; i <=nlstate; i++){
8923: for(j=1; j <=nlstate+ndeath; j++){
8924: if(j==i) continue;
8925: for(k=1; k<=ncovmodel;k++){
8926: jj++;
8927: ca[0]= k+'a'-1;ca[1]='\0';
8928: if(itimes==1){
8929: printf("#%1d%1d%d",i,j,k);
8930: fprintf(ficparo,"#%1d%1d%d",i,j,k);
8931: }else{
8932: printf("%1d%1d%d",i,j,k);
8933: fprintf(ficparo,"%1d%1d%d",i,j,k);
8934: /* printf(" %.5le",matcov[i][j]); */
8935: }
8936: ll=0;
8937: for(li=1;li <=nlstate; li++){
8938: for(lj=1;lj <=nlstate+ndeath; lj++){
8939: if(lj==li) continue;
8940: for(lk=1;lk<=ncovmodel;lk++){
8941: ll++;
8942: if(ll<=jj){
8943: cb[0]= lk +'a'-1;cb[1]='\0';
8944: if(ll<jj){
8945: if(itimes==1){
8946: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8947: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8948: }else{
8949: printf(" 0.");
8950: fprintf(ficparo," 0.");
8951: }
8952: }else{
8953: if(itimes==1){
8954: printf(" Var(%s%1d%1d)",ca,i,j);
8955: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
8956: }else{
8957: printf(" 0.");
8958: fprintf(ficparo," 0.");
8959: }
8960: }
8961: }
8962: } /* end lk */
8963: } /* end lj */
8964: } /* end li */
8965: printf("\n");
8966: fprintf(ficparo,"\n");
8967: numlinepar++;
8968: } /* end k*/
8969: } /*end j */
8970: } /* end i */
8971: } /* end itimes */
8972:
8973: } /* end of prwizard */
8974: /******************* Gompertz Likelihood ******************************/
8975: double gompertz(double x[])
8976: {
8977: double A,B,L=0.0,sump=0.,num=0.;
8978: int i,n=0; /* n is the size of the sample */
8979:
1.220 brouard 8980: for (i=1;i<=imx ; i++) {
1.126 brouard 8981: sump=sump+weight[i];
8982: /* sump=sump+1;*/
8983: num=num+1;
8984: }
8985:
8986:
8987: /* for (i=0; i<=imx; i++)
8988: 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]);*/
8989:
8990: for (i=1;i<=imx ; i++)
8991: {
8992: if (cens[i] == 1 && wav[i]>1)
8993: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
8994:
8995: if (cens[i] == 0 && wav[i]>1)
8996: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
8997: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
8998:
8999: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9000: if (wav[i] > 1 ) { /* ??? */
9001: L=L+A*weight[i];
9002: /* 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]);*/
9003: }
9004: }
9005:
9006: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9007:
9008: return -2*L*num/sump;
9009: }
9010:
1.136 brouard 9011: #ifdef GSL
9012: /******************* Gompertz_f Likelihood ******************************/
9013: double gompertz_f(const gsl_vector *v, void *params)
9014: {
9015: double A,B,LL=0.0,sump=0.,num=0.;
9016: double *x= (double *) v->data;
9017: int i,n=0; /* n is the size of the sample */
9018:
9019: for (i=0;i<=imx-1 ; i++) {
9020: sump=sump+weight[i];
9021: /* sump=sump+1;*/
9022: num=num+1;
9023: }
9024:
9025:
9026: /* for (i=0; i<=imx; i++)
9027: 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]);*/
9028: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
9029: for (i=1;i<=imx ; i++)
9030: {
9031: if (cens[i] == 1 && wav[i]>1)
9032: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
9033:
9034: if (cens[i] == 0 && wav[i]>1)
9035: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
9036: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
9037:
9038: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
9039: if (wav[i] > 1 ) { /* ??? */
9040: LL=LL+A*weight[i];
9041: /* 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]);*/
9042: }
9043: }
9044:
9045: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
9046: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
9047:
9048: return -2*LL*num/sump;
9049: }
9050: #endif
9051:
1.126 brouard 9052: /******************* Printing html file ***********/
1.201 brouard 9053: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 9054: int lastpass, int stepm, int weightopt, char model[],\
9055: int imx, double p[],double **matcov,double agemortsup){
9056: int i,k;
9057:
9058: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
9059: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
9060: for (i=1;i<=2;i++)
9061: 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 9062: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 9063: fprintf(fichtm,"</ul>");
9064:
9065: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
9066:
9067: 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>");
9068:
9069: for (k=agegomp;k<(agemortsup-2);k++)
9070: 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]);
9071:
9072:
9073: fflush(fichtm);
9074: }
9075:
9076: /******************* Gnuplot file **************/
1.201 brouard 9077: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 9078:
9079: char dirfileres[132],optfileres[132];
1.164 brouard 9080:
1.126 brouard 9081: int ng;
9082:
9083:
9084: /*#ifdef windows */
9085: fprintf(ficgp,"cd \"%s\" \n",pathc);
9086: /*#endif */
9087:
9088:
9089: strcpy(dirfileres,optionfilefiname);
9090: strcpy(optfileres,"vpl");
1.199 brouard 9091: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 9092: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 9093: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 9094: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 9095: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
9096:
9097: }
9098:
1.136 brouard 9099: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
9100: {
1.126 brouard 9101:
1.136 brouard 9102: /*-------- data file ----------*/
9103: FILE *fic;
9104: char dummy[]=" ";
1.240 brouard 9105: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 9106: int lstra;
1.136 brouard 9107: int linei, month, year,iout;
9108: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 9109: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 9110: char *stratrunc;
1.223 brouard 9111:
1.240 brouard 9112: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
9113: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 9114:
1.240 brouard 9115: for(v=1; v <=ncovcol;v++){
9116: DummyV[v]=0;
9117: FixedV[v]=0;
9118: }
9119: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
9120: DummyV[v]=1;
9121: FixedV[v]=0;
9122: }
9123: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
9124: DummyV[v]=0;
9125: FixedV[v]=1;
9126: }
9127: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
9128: DummyV[v]=1;
9129: FixedV[v]=1;
9130: }
9131: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
9132: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
9133: 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]);
9134: }
1.126 brouard 9135:
1.136 brouard 9136: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 9137: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
9138: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 9139: }
1.126 brouard 9140:
1.136 brouard 9141: i=1;
9142: linei=0;
9143: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
9144: linei=linei+1;
9145: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
9146: if(line[j] == '\t')
9147: line[j] = ' ';
9148: }
9149: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
9150: ;
9151: };
9152: line[j+1]=0; /* Trims blanks at end of line */
9153: if(line[0]=='#'){
9154: fprintf(ficlog,"Comment line\n%s\n",line);
9155: printf("Comment line\n%s\n",line);
9156: continue;
9157: }
9158: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9159: strcpy(line, linetmp);
1.223 brouard 9160:
9161: /* Loops on waves */
9162: for (j=maxwav;j>=1;j--){
9163: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9164: cutv(stra, strb, line, ' ');
9165: if(strb[0]=='.') { /* Missing value */
9166: lval=-1;
9167: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9168: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9169: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9170: 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);
9171: 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);
9172: return 1;
9173: }
9174: }else{
9175: errno=0;
9176: /* what_kind_of_number(strb); */
9177: dval=strtod(strb,&endptr);
9178: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9179: /* if(strb != endptr && *endptr == '\0') */
9180: /* dval=dlval; */
9181: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9182: if( strb[0]=='\0' || (*endptr != '\0')){
9183: 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);
9184: 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);
9185: return 1;
9186: }
9187: cotqvar[j][iv][i]=dval;
9188: cotvar[j][ntv+iv][i]=dval;
9189: }
9190: strcpy(line,stra);
1.223 brouard 9191: }/* end loop ntqv */
1.225 brouard 9192:
1.223 brouard 9193: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9194: cutv(stra, strb, line, ' ');
9195: if(strb[0]=='.') { /* Missing value */
9196: lval=-1;
9197: }else{
9198: errno=0;
9199: lval=strtol(strb,&endptr,10);
9200: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9201: if( strb[0]=='\0' || (*endptr != '\0')){
9202: 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);
9203: 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);
9204: return 1;
9205: }
9206: }
9207: if(lval <-1 || lval >1){
9208: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9209: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9210: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9211: For example, for multinomial values like 1, 2 and 3,\n \
9212: build V1=0 V2=0 for the reference value (1),\n \
9213: V1=1 V2=0 for (2) \n \
1.223 brouard 9214: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9215: output of IMaCh is often meaningless.\n \
1.223 brouard 9216: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9217: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9218: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9219: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9220: For example, for multinomial values like 1, 2 and 3,\n \
9221: build V1=0 V2=0 for the reference value (1),\n \
9222: V1=1 V2=0 for (2) \n \
1.223 brouard 9223: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9224: output of IMaCh is often meaningless.\n \
1.223 brouard 9225: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 9226: return 1;
9227: }
9228: cotvar[j][iv][i]=(double)(lval);
9229: strcpy(line,stra);
1.223 brouard 9230: }/* end loop ntv */
1.225 brouard 9231:
1.223 brouard 9232: /* Statuses at wave */
1.137 brouard 9233: cutv(stra, strb, line, ' ');
1.223 brouard 9234: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9235: lval=-1;
1.136 brouard 9236: }else{
1.238 brouard 9237: errno=0;
9238: lval=strtol(strb,&endptr,10);
9239: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9240: if( strb[0]=='\0' || (*endptr != '\0')){
9241: 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);
9242: 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);
9243: return 1;
9244: }
1.136 brouard 9245: }
1.225 brouard 9246:
1.136 brouard 9247: s[j][i]=lval;
1.225 brouard 9248:
1.223 brouard 9249: /* Date of Interview */
1.136 brouard 9250: strcpy(line,stra);
9251: cutv(stra, strb,line,' ');
1.169 brouard 9252: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9253: }
1.169 brouard 9254: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9255: month=99;
9256: year=9999;
1.136 brouard 9257: }else{
1.225 brouard 9258: 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);
9259: 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);
9260: return 1;
1.136 brouard 9261: }
9262: anint[j][i]= (double) year;
9263: mint[j][i]= (double)month;
9264: strcpy(line,stra);
1.223 brouard 9265: } /* End loop on waves */
1.225 brouard 9266:
1.223 brouard 9267: /* Date of death */
1.136 brouard 9268: cutv(stra, strb,line,' ');
1.169 brouard 9269: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9270: }
1.169 brouard 9271: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9272: month=99;
9273: year=9999;
9274: }else{
1.141 brouard 9275: 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 9276: 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);
9277: return 1;
1.136 brouard 9278: }
9279: andc[i]=(double) year;
9280: moisdc[i]=(double) month;
9281: strcpy(line,stra);
9282:
1.223 brouard 9283: /* Date of birth */
1.136 brouard 9284: cutv(stra, strb,line,' ');
1.169 brouard 9285: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9286: }
1.169 brouard 9287: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9288: month=99;
9289: year=9999;
9290: }else{
1.141 brouard 9291: 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);
9292: 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 9293: return 1;
1.136 brouard 9294: }
9295: if (year==9999) {
1.141 brouard 9296: 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);
9297: 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 9298: return 1;
9299:
1.136 brouard 9300: }
9301: annais[i]=(double)(year);
9302: moisnais[i]=(double)(month);
9303: strcpy(line,stra);
1.225 brouard 9304:
1.223 brouard 9305: /* Sample weight */
1.136 brouard 9306: cutv(stra, strb,line,' ');
9307: errno=0;
9308: dval=strtod(strb,&endptr);
9309: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9310: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9311: 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 9312: fflush(ficlog);
9313: return 1;
9314: }
9315: weight[i]=dval;
9316: strcpy(line,stra);
1.225 brouard 9317:
1.223 brouard 9318: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9319: cutv(stra, strb, line, ' ');
9320: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9321: lval=-1;
1.223 brouard 9322: }else{
1.225 brouard 9323: errno=0;
9324: /* what_kind_of_number(strb); */
9325: dval=strtod(strb,&endptr);
9326: /* if(strb != endptr && *endptr == '\0') */
9327: /* dval=dlval; */
9328: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9329: if( strb[0]=='\0' || (*endptr != '\0')){
9330: 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);
9331: 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);
9332: return 1;
9333: }
9334: coqvar[iv][i]=dval;
1.226 brouard 9335: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9336: }
9337: strcpy(line,stra);
9338: }/* end loop nqv */
1.136 brouard 9339:
1.223 brouard 9340: /* Covariate values */
1.136 brouard 9341: for (j=ncovcol;j>=1;j--){
9342: cutv(stra, strb,line,' ');
1.223 brouard 9343: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9344: lval=-1;
1.136 brouard 9345: }else{
1.225 brouard 9346: errno=0;
9347: lval=strtol(strb,&endptr,10);
9348: if( strb[0]=='\0' || (*endptr != '\0')){
9349: 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);
9350: 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);
9351: return 1;
9352: }
1.136 brouard 9353: }
9354: if(lval <-1 || lval >1){
1.225 brouard 9355: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9356: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9357: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9358: For example, for multinomial values like 1, 2 and 3,\n \
9359: build V1=0 V2=0 for the reference value (1),\n \
9360: V1=1 V2=0 for (2) \n \
1.136 brouard 9361: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9362: output of IMaCh is often meaningless.\n \
1.136 brouard 9363: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9364: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9365: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9366: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9367: For example, for multinomial values like 1, 2 and 3,\n \
9368: build V1=0 V2=0 for the reference value (1),\n \
9369: V1=1 V2=0 for (2) \n \
1.136 brouard 9370: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9371: output of IMaCh is often meaningless.\n \
1.136 brouard 9372: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9373: return 1;
1.136 brouard 9374: }
9375: covar[j][i]=(double)(lval);
9376: strcpy(line,stra);
9377: }
9378: lstra=strlen(stra);
1.225 brouard 9379:
1.136 brouard 9380: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9381: stratrunc = &(stra[lstra-9]);
9382: num[i]=atol(stratrunc);
9383: }
9384: else
9385: num[i]=atol(stra);
9386: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9387: 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;}*/
9388:
9389: i=i+1;
9390: } /* End loop reading data */
1.225 brouard 9391:
1.136 brouard 9392: *imax=i-1; /* Number of individuals */
9393: fclose(fic);
1.225 brouard 9394:
1.136 brouard 9395: return (0);
1.164 brouard 9396: /* endread: */
1.225 brouard 9397: printf("Exiting readdata: ");
9398: fclose(fic);
9399: return (1);
1.223 brouard 9400: }
1.126 brouard 9401:
1.234 brouard 9402: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9403: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9404: while (*p2 == ' ')
1.234 brouard 9405: p2++;
9406: /* while ((*p1++ = *p2++) !=0) */
9407: /* ; */
9408: /* do */
9409: /* while (*p2 == ' ') */
9410: /* p2++; */
9411: /* while (*p1++ == *p2++); */
9412: *stri=p2;
1.145 brouard 9413: }
9414:
1.235 brouard 9415: int decoderesult ( char resultline[], int nres)
1.230 brouard 9416: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9417: {
1.235 brouard 9418: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9419: char resultsav[MAXLINE];
1.234 brouard 9420: int resultmodel[MAXLINE];
9421: int modelresult[MAXLINE];
1.230 brouard 9422: char stra[80], strb[80], strc[80], strd[80],stre[80];
9423:
1.234 brouard 9424: removefirstspace(&resultline);
1.233 brouard 9425: printf("decoderesult:%s\n",resultline);
1.230 brouard 9426:
9427: if (strstr(resultline,"v") !=0){
9428: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9429: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9430: return 1;
9431: }
9432: trimbb(resultsav, resultline);
9433: if (strlen(resultsav) >1){
9434: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9435: }
1.253 brouard 9436: if(j == 0){ /* Resultline but no = */
9437: TKresult[nres]=0; /* Combination for the nresult and the model */
9438: return (0);
9439: }
9440:
1.234 brouard 9441: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
9442: 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);
9443: 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);
9444: }
9445: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9446: if(nbocc(resultsav,'=') >1){
9447: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
9448: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
9449: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9450: }else
9451: cutl(strc,strd,resultsav,'=');
1.230 brouard 9452: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9453:
1.230 brouard 9454: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9455: Tvarsel[k]=atoi(strc);
9456: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9457: /* cptcovsel++; */
9458: if (nbocc(stra,'=') >0)
9459: strcpy(resultsav,stra); /* and analyzes it */
9460: }
1.235 brouard 9461: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9462: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9463: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9464: match=0;
1.236 brouard 9465: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9466: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9467: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9468: match=1;
9469: break;
9470: }
9471: }
9472: if(match == 0){
9473: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9474: }
9475: }
9476: }
1.235 brouard 9477: /* Checking for missing or useless values in comparison of current model needs */
9478: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9479: match=0;
1.235 brouard 9480: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9481: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9482: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9483: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9484: ++match;
9485: }
9486: }
9487: }
9488: if(match == 0){
9489: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9490: }else if(match > 1){
9491: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9492: }
9493: }
1.235 brouard 9494:
1.234 brouard 9495: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9496: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9497: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9498: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9499: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9500: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9501: /* 1 0 0 0 */
9502: /* 2 1 0 0 */
9503: /* 3 0 1 0 */
9504: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9505: /* 5 0 0 1 */
9506: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9507: /* 7 0 1 1 */
9508: /* 8 1 1 1 */
1.237 brouard 9509: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9510: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9511: /* V5*age V5 known which value for nres? */
9512: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9513: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9514: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9515: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9516: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9517: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9518: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9519: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9520: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9521: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9522: k4++;;
9523: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9524: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9525: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9526: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9527: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9528: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9529: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9530: k4q++;;
9531: }
9532: }
1.234 brouard 9533:
1.235 brouard 9534: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9535: return (0);
9536: }
1.235 brouard 9537:
1.230 brouard 9538: int decodemodel( char model[], int lastobs)
9539: /**< This routine decodes the model and returns:
1.224 brouard 9540: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9541: * - nagesqr = 1 if age*age in the model, otherwise 0.
9542: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9543: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9544: * - cptcovage number of covariates with age*products =2
9545: * - cptcovs number of simple covariates
9546: * - 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
9547: * which is a new column after the 9 (ncovcol) variables.
9548: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9549: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9550: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9551: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9552: */
1.136 brouard 9553: {
1.238 brouard 9554: int i, j, k, ks, v;
1.227 brouard 9555: int j1, k1, k2, k3, k4;
1.136 brouard 9556: char modelsav[80];
1.145 brouard 9557: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9558: char *strpt;
1.136 brouard 9559:
1.145 brouard 9560: /*removespace(model);*/
1.136 brouard 9561: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9562: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9563: if (strstr(model,"AGE") !=0){
1.192 brouard 9564: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9565: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9566: return 1;
9567: }
1.141 brouard 9568: if (strstr(model,"v") !=0){
9569: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9570: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9571: return 1;
9572: }
1.187 brouard 9573: strcpy(modelsav,model);
9574: if ((strpt=strstr(model,"age*age")) !=0){
9575: printf(" strpt=%s, model=%s\n",strpt, model);
9576: if(strpt != model){
1.234 brouard 9577: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9578: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9579: corresponding column of parameters.\n",model);
1.234 brouard 9580: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9581: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9582: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9583: return 1;
1.225 brouard 9584: }
1.187 brouard 9585: nagesqr=1;
9586: if (strstr(model,"+age*age") !=0)
1.234 brouard 9587: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9588: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9589: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9590: else
1.234 brouard 9591: substrchaine(modelsav, model, "age*age");
1.187 brouard 9592: }else
9593: nagesqr=0;
9594: if (strlen(modelsav) >1){
9595: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9596: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9597: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9598: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9599: * cst, age and age*age
9600: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9601: /* including age products which are counted in cptcovage.
9602: * but the covariates which are products must be treated
9603: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9604: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9605: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9606:
9607:
1.187 brouard 9608: /* Design
9609: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9610: * < ncovcol=8 >
9611: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9612: * k= 1 2 3 4 5 6 7 8
9613: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9614: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9615: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9616: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9617: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9618: * Tage[++cptcovage]=k
9619: * if products, new covar are created after ncovcol with k1
9620: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9621: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9622: * 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
9623: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9624: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9625: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9626: * < ncovcol=8 >
9627: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9628: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9629: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9630: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9631: * p Tprod[1]@2={ 6, 5}
9632: *p Tvard[1][1]@4= {7, 8, 5, 6}
9633: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9634: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9635: *How to reorganize?
9636: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9637: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9638: * {2, 1, 4, 8, 5, 6, 3, 7}
9639: * Struct []
9640: */
1.225 brouard 9641:
1.187 brouard 9642: /* This loop fills the array Tvar from the string 'model'.*/
9643: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9644: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9645: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9646: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9647: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9648: /* k=1 Tvar[1]=2 (from V2) */
9649: /* k=5 Tvar[5] */
9650: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9651: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9652: /* } */
1.198 brouard 9653: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9654: /*
9655: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9656: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9657: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9658: }
1.187 brouard 9659: cptcovage=0;
9660: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9661: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9662: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9663: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9664: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9665: /*scanf("%d",i);*/
9666: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9667: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9668: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9669: /* covar is not filled and then is empty */
9670: cptcovprod--;
9671: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9672: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9673: Typevar[k]=1; /* 1 for age product */
9674: cptcovage++; /* Sums the number of covariates which include age as a product */
9675: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9676: /*printf("stre=%s ", stre);*/
9677: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9678: cptcovprod--;
9679: cutl(stre,strb,strc,'V');
9680: Tvar[k]=atoi(stre);
9681: Typevar[k]=1; /* 1 for age product */
9682: cptcovage++;
9683: Tage[cptcovage]=k;
9684: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9685: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9686: cptcovn++;
9687: cptcovprodnoage++;k1++;
9688: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9689: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9690: because this model-covariate is a construction we invent a new column
9691: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9692: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9693: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9694: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9695: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9696: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9697: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9698: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9699: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9700: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9701: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9702: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9703: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9704: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9705: for (i=1; i<=lastobs;i++){
9706: /* Computes the new covariate which is a product of
9707: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9708: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9709: }
9710: } /* End age is not in the model */
9711: } /* End if model includes a product */
9712: else { /* no more sum */
9713: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9714: /* scanf("%d",i);*/
9715: cutl(strd,strc,strb,'V');
9716: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9717: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9718: Tvar[k]=atoi(strd);
9719: Typevar[k]=0; /* 0 for simple covariates */
9720: }
9721: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9722: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9723: scanf("%d",i);*/
1.187 brouard 9724: } /* end of loop + on total covariates */
9725: } /* end if strlen(modelsave == 0) age*age might exist */
9726: } /* end if strlen(model == 0) */
1.136 brouard 9727:
9728: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9729: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9730:
1.136 brouard 9731: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9732: printf("cptcovprod=%d ", cptcovprod);
9733: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9734: scanf("%d ",i);*/
9735:
9736:
1.230 brouard 9737: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9738: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9739: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9740: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9741: k = 1 2 3 4 5 6 7 8 9
9742: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9743: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9744: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9745: Dummy[k] 1 0 0 0 3 1 1 2 3
9746: Tmodelind[combination of covar]=k;
1.225 brouard 9747: */
9748: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9749: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9750: /* 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 9751: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9752: printf("Model=%s\n\
9753: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9754: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9755: 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);
9756: fprintf(ficlog,"Model=%s\n\
9757: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9758: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9759: Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model);
1.285 brouard 9760: for(k=-1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9761: 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 */
9762: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9763: Fixed[k]= 0;
9764: Dummy[k]= 0;
1.225 brouard 9765: ncoveff++;
1.232 brouard 9766: ncovf++;
1.234 brouard 9767: nsd++;
9768: modell[k].maintype= FTYPE;
9769: TvarsD[nsd]=Tvar[k];
9770: TvarsDind[nsd]=k;
9771: TvarF[ncovf]=Tvar[k];
9772: TvarFind[ncovf]=k;
9773: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9774: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9775: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
9776: Fixed[k]= 0;
9777: Dummy[k]= 0;
9778: ncoveff++;
9779: ncovf++;
9780: modell[k].maintype= FTYPE;
9781: TvarF[ncovf]=Tvar[k];
9782: TvarFind[ncovf]=k;
1.230 brouard 9783: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 9784: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 9785: }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 9786: Fixed[k]= 0;
9787: Dummy[k]= 1;
1.230 brouard 9788: nqfveff++;
1.234 brouard 9789: modell[k].maintype= FTYPE;
9790: modell[k].subtype= FQ;
9791: nsq++;
9792: TvarsQ[nsq]=Tvar[k];
9793: TvarsQind[nsq]=k;
1.232 brouard 9794: ncovf++;
1.234 brouard 9795: TvarF[ncovf]=Tvar[k];
9796: TvarFind[ncovf]=k;
1.231 brouard 9797: 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 9798: 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 9799: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 9800: Fixed[k]= 1;
9801: Dummy[k]= 0;
1.225 brouard 9802: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 9803: modell[k].maintype= VTYPE;
9804: modell[k].subtype= VD;
9805: nsd++;
9806: TvarsD[nsd]=Tvar[k];
9807: TvarsDind[nsd]=k;
9808: ncovv++; /* Only simple time varying variables */
9809: TvarV[ncovv]=Tvar[k];
1.242 brouard 9810: 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 9811: 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 */
9812: 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 9813: 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);
9814: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 9815: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 9816: Fixed[k]= 1;
9817: Dummy[k]= 1;
9818: nqtveff++;
9819: modell[k].maintype= VTYPE;
9820: modell[k].subtype= VQ;
9821: ncovv++; /* Only simple time varying variables */
9822: nsq++;
9823: TvarsQ[nsq]=Tvar[k];
9824: TvarsQind[nsq]=k;
9825: TvarV[ncovv]=Tvar[k];
1.242 brouard 9826: 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 9827: 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 */
9828: 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 9829: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9830: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9831: 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 9832: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9833: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9834: ncova++;
9835: TvarA[ncova]=Tvar[k];
9836: TvarAind[ncova]=k;
1.231 brouard 9837: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9838: Fixed[k]= 2;
9839: Dummy[k]= 2;
9840: modell[k].maintype= ATYPE;
9841: modell[k].subtype= APFD;
9842: /* ncoveff++; */
1.227 brouard 9843: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 9844: Fixed[k]= 2;
9845: Dummy[k]= 3;
9846: modell[k].maintype= ATYPE;
9847: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
9848: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 9849: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 9850: Fixed[k]= 3;
9851: Dummy[k]= 2;
9852: modell[k].maintype= ATYPE;
9853: modell[k].subtype= APVD; /* Product age * varying dummy */
9854: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 9855: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9856: Fixed[k]= 3;
9857: Dummy[k]= 3;
9858: modell[k].maintype= ATYPE;
9859: modell[k].subtype= APVQ; /* Product age * varying quantitative */
9860: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 9861: }
9862: }else if (Typevar[k] == 2) { /* product without age */
9863: k1=Tposprod[k];
9864: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 9865: if(Tvard[k1][2] <=ncovcol){
9866: Fixed[k]= 1;
9867: Dummy[k]= 0;
9868: modell[k].maintype= FTYPE;
9869: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
9870: ncovf++; /* Fixed variables without age */
9871: TvarF[ncovf]=Tvar[k];
9872: TvarFind[ncovf]=k;
9873: }else if(Tvard[k1][2] <=ncovcol+nqv){
9874: Fixed[k]= 0; /* or 2 ?*/
9875: Dummy[k]= 1;
9876: modell[k].maintype= FTYPE;
9877: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
9878: ncovf++; /* Varying variables without age */
9879: TvarF[ncovf]=Tvar[k];
9880: TvarFind[ncovf]=k;
9881: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9882: Fixed[k]= 1;
9883: Dummy[k]= 0;
9884: modell[k].maintype= VTYPE;
9885: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
9886: ncovv++; /* Varying variables without age */
9887: TvarV[ncovv]=Tvar[k];
9888: TvarVind[ncovv]=k;
9889: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9890: Fixed[k]= 1;
9891: Dummy[k]= 1;
9892: modell[k].maintype= VTYPE;
9893: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
9894: ncovv++; /* Varying variables without age */
9895: TvarV[ncovv]=Tvar[k];
9896: TvarVind[ncovv]=k;
9897: }
1.227 brouard 9898: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 9899: if(Tvard[k1][2] <=ncovcol){
9900: Fixed[k]= 0; /* or 2 ?*/
9901: Dummy[k]= 1;
9902: modell[k].maintype= FTYPE;
9903: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
9904: ncovf++; /* Fixed variables without age */
9905: TvarF[ncovf]=Tvar[k];
9906: TvarFind[ncovf]=k;
9907: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9908: Fixed[k]= 1;
9909: Dummy[k]= 1;
9910: modell[k].maintype= VTYPE;
9911: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
9912: ncovv++; /* Varying variables without age */
9913: TvarV[ncovv]=Tvar[k];
9914: TvarVind[ncovv]=k;
9915: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9916: Fixed[k]= 1;
9917: Dummy[k]= 1;
9918: modell[k].maintype= VTYPE;
9919: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
9920: ncovv++; /* Varying variables without age */
9921: TvarV[ncovv]=Tvar[k];
9922: TvarVind[ncovv]=k;
9923: ncovv++; /* Varying variables without age */
9924: TvarV[ncovv]=Tvar[k];
9925: TvarVind[ncovv]=k;
9926: }
1.227 brouard 9927: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 9928: if(Tvard[k1][2] <=ncovcol){
9929: Fixed[k]= 1;
9930: Dummy[k]= 1;
9931: modell[k].maintype= VTYPE;
9932: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
9933: ncovv++; /* Varying variables without age */
9934: TvarV[ncovv]=Tvar[k];
9935: TvarVind[ncovv]=k;
9936: }else if(Tvard[k1][2] <=ncovcol+nqv){
9937: Fixed[k]= 1;
9938: Dummy[k]= 1;
9939: modell[k].maintype= VTYPE;
9940: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
9941: ncovv++; /* Varying variables without age */
9942: TvarV[ncovv]=Tvar[k];
9943: TvarVind[ncovv]=k;
9944: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9945: Fixed[k]= 1;
9946: Dummy[k]= 0;
9947: modell[k].maintype= VTYPE;
9948: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
9949: ncovv++; /* Varying variables without age */
9950: TvarV[ncovv]=Tvar[k];
9951: TvarVind[ncovv]=k;
9952: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9953: Fixed[k]= 1;
9954: Dummy[k]= 1;
9955: modell[k].maintype= VTYPE;
9956: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
9957: ncovv++; /* Varying variables without age */
9958: TvarV[ncovv]=Tvar[k];
9959: TvarVind[ncovv]=k;
9960: }
1.227 brouard 9961: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9962: if(Tvard[k1][2] <=ncovcol){
9963: Fixed[k]= 1;
9964: Dummy[k]= 1;
9965: modell[k].maintype= VTYPE;
9966: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
9967: ncovv++; /* Varying variables without age */
9968: TvarV[ncovv]=Tvar[k];
9969: TvarVind[ncovv]=k;
9970: }else if(Tvard[k1][2] <=ncovcol+nqv){
9971: Fixed[k]= 1;
9972: Dummy[k]= 1;
9973: modell[k].maintype= VTYPE;
9974: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
9975: ncovv++; /* Varying variables without age */
9976: TvarV[ncovv]=Tvar[k];
9977: TvarVind[ncovv]=k;
9978: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9979: Fixed[k]= 1;
9980: Dummy[k]= 1;
9981: modell[k].maintype= VTYPE;
9982: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
9983: ncovv++; /* Varying variables without age */
9984: TvarV[ncovv]=Tvar[k];
9985: TvarVind[ncovv]=k;
9986: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9987: Fixed[k]= 1;
9988: Dummy[k]= 1;
9989: modell[k].maintype= VTYPE;
9990: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
9991: ncovv++; /* Varying variables without age */
9992: TvarV[ncovv]=Tvar[k];
9993: TvarVind[ncovv]=k;
9994: }
1.227 brouard 9995: }else{
1.240 brouard 9996: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9997: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9998: } /*end k1*/
1.225 brouard 9999: }else{
1.226 brouard 10000: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
10001: 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 10002: }
1.227 brouard 10003: 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 10004: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 10005: 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]);
10006: }
10007: /* Searching for doublons in the model */
10008: for(k1=1; k1<= cptcovt;k1++){
10009: for(k2=1; k2 <k1;k2++){
1.285 brouard 10010: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
10011: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 10012: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
10013: if(Tvar[k1]==Tvar[k2]){
1.285 brouard 10014: printf("Error duplication in the model=%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[k1],Dummy[k1]);
10015: fprintf(ficlog,"Error duplication in the model=%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[k1],Dummy[k1]); fflush(ficlog);
1.234 brouard 10016: return(1);
10017: }
10018: }else if (Typevar[k1] ==2){
10019: k3=Tposprod[k1];
10020: k4=Tposprod[k2];
10021: 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])) ){
10022: 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]]);
10023: 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);
10024: return(1);
10025: }
10026: }
1.227 brouard 10027: }
10028: }
1.225 brouard 10029: }
10030: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
10031: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 10032: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
10033: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 10034: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 10035: /*endread:*/
1.225 brouard 10036: printf("Exiting decodemodel: ");
10037: return (1);
1.136 brouard 10038: }
10039:
1.169 brouard 10040: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 10041: {/* Check ages at death */
1.136 brouard 10042: int i, m;
1.218 brouard 10043: int firstone=0;
10044:
1.136 brouard 10045: for (i=1; i<=imx; i++) {
10046: for(m=2; (m<= maxwav); m++) {
10047: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
10048: anint[m][i]=9999;
1.216 brouard 10049: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
10050: s[m][i]=-1;
1.136 brouard 10051: }
10052: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 10053: *nberr = *nberr + 1;
1.218 brouard 10054: if(firstone == 0){
10055: firstone=1;
1.260 brouard 10056: 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 10057: }
1.262 brouard 10058: 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 10059: s[m][i]=-1; /* Droping the death status */
1.136 brouard 10060: }
10061: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 10062: (*nberr)++;
1.259 brouard 10063: 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 10064: 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 10065: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 10066: }
10067: }
10068: }
10069:
10070: for (i=1; i<=imx; i++) {
10071: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
10072: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 10073: 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 10074: if (s[m][i] >= nlstate+1) {
1.169 brouard 10075: if(agedc[i]>0){
10076: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 10077: agev[m][i]=agedc[i];
1.214 brouard 10078: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 10079: }else {
1.136 brouard 10080: if ((int)andc[i]!=9999){
10081: nbwarn++;
10082: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
10083: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
10084: agev[m][i]=-1;
10085: }
10086: }
1.169 brouard 10087: } /* agedc > 0 */
1.214 brouard 10088: } /* end if */
1.136 brouard 10089: else if(s[m][i] !=9){ /* Standard case, age in fractional
10090: years but with the precision of a month */
10091: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
10092: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
10093: agev[m][i]=1;
10094: else if(agev[m][i] < *agemin){
10095: *agemin=agev[m][i];
10096: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
10097: }
10098: else if(agev[m][i] >*agemax){
10099: *agemax=agev[m][i];
1.156 brouard 10100: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 10101: }
10102: /*agev[m][i]=anint[m][i]-annais[i];*/
10103: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 10104: } /* en if 9*/
1.136 brouard 10105: else { /* =9 */
1.214 brouard 10106: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 10107: agev[m][i]=1;
10108: s[m][i]=-1;
10109: }
10110: }
1.214 brouard 10111: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 10112: agev[m][i]=1;
1.214 brouard 10113: else{
10114: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10115: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
10116: agev[m][i]=0;
10117: }
10118: } /* End for lastpass */
10119: }
1.136 brouard 10120:
10121: for (i=1; i<=imx; i++) {
10122: for(m=firstpass; (m<=lastpass); m++){
10123: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 10124: (*nberr)++;
1.136 brouard 10125: 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);
10126: 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);
10127: return 1;
10128: }
10129: }
10130: }
10131:
10132: /*for (i=1; i<=imx; i++){
10133: for (m=firstpass; (m<lastpass); m++){
10134: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
10135: }
10136:
10137: }*/
10138:
10139:
1.139 brouard 10140: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
10141: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 10142:
10143: return (0);
1.164 brouard 10144: /* endread:*/
1.136 brouard 10145: printf("Exiting calandcheckages: ");
10146: return (1);
10147: }
10148:
1.172 brouard 10149: #if defined(_MSC_VER)
10150: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10151: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
10152: //#include "stdafx.h"
10153: //#include <stdio.h>
10154: //#include <tchar.h>
10155: //#include <windows.h>
10156: //#include <iostream>
10157: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10158:
10159: LPFN_ISWOW64PROCESS fnIsWow64Process;
10160:
10161: BOOL IsWow64()
10162: {
10163: BOOL bIsWow64 = FALSE;
10164:
10165: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10166: // (HANDLE, PBOOL);
10167:
10168: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10169:
10170: HMODULE module = GetModuleHandle(_T("kernel32"));
10171: const char funcName[] = "IsWow64Process";
10172: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10173: GetProcAddress(module, funcName);
10174:
10175: if (NULL != fnIsWow64Process)
10176: {
10177: if (!fnIsWow64Process(GetCurrentProcess(),
10178: &bIsWow64))
10179: //throw std::exception("Unknown error");
10180: printf("Unknown error\n");
10181: }
10182: return bIsWow64 != FALSE;
10183: }
10184: #endif
1.177 brouard 10185:
1.191 brouard 10186: void syscompilerinfo(int logged)
1.167 brouard 10187: {
10188: /* #include "syscompilerinfo.h"*/
1.185 brouard 10189: /* command line Intel compiler 32bit windows, XP compatible:*/
10190: /* /GS /W3 /Gy
10191: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10192: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10193: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10194: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10195: */
10196: /* 64 bits */
1.185 brouard 10197: /*
10198: /GS /W3 /Gy
10199: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10200: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10201: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10202: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10203: /* Optimization are useless and O3 is slower than O2 */
10204: /*
10205: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10206: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10207: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10208: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10209: */
1.186 brouard 10210: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10211: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10212: /PDB:"visual studio
10213: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10214: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10215: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10216: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10217: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10218: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10219: uiAccess='false'"
10220: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10221: /NOLOGO /TLBID:1
10222: */
1.177 brouard 10223: #if defined __INTEL_COMPILER
1.178 brouard 10224: #if defined(__GNUC__)
10225: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10226: #endif
1.177 brouard 10227: #elif defined(__GNUC__)
1.179 brouard 10228: #ifndef __APPLE__
1.174 brouard 10229: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10230: #endif
1.177 brouard 10231: struct utsname sysInfo;
1.178 brouard 10232: int cross = CROSS;
10233: if (cross){
10234: printf("Cross-");
1.191 brouard 10235: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10236: }
1.174 brouard 10237: #endif
10238:
1.171 brouard 10239: #include <stdint.h>
1.178 brouard 10240:
1.191 brouard 10241: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10242: #if defined(__clang__)
1.191 brouard 10243: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10244: #endif
10245: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10246: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10247: #endif
10248: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10249: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10250: #endif
10251: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10252: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10253: #endif
10254: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10255: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10256: #endif
10257: #if defined(_MSC_VER)
1.191 brouard 10258: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10259: #endif
10260: #if defined(__PGI)
1.191 brouard 10261: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10262: #endif
10263: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10264: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10265: #endif
1.191 brouard 10266: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10267:
1.167 brouard 10268: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10269: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10270: // Windows (x64 and x86)
1.191 brouard 10271: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10272: #elif __unix__ // all unices, not all compilers
10273: // Unix
1.191 brouard 10274: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10275: #elif __linux__
10276: // linux
1.191 brouard 10277: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10278: #elif __APPLE__
1.174 brouard 10279: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10280: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10281: #endif
10282:
10283: /* __MINGW32__ */
10284: /* __CYGWIN__ */
10285: /* __MINGW64__ */
10286: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10287: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10288: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10289: /* _WIN64 // Defined for applications for Win64. */
10290: /* _M_X64 // Defined for compilations that target x64 processors. */
10291: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10292:
1.167 brouard 10293: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10294: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10295: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10296: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10297: #else
1.191 brouard 10298: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10299: #endif
10300:
1.169 brouard 10301: #if defined(__GNUC__)
10302: # if defined(__GNUC_PATCHLEVEL__)
10303: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10304: + __GNUC_MINOR__ * 100 \
10305: + __GNUC_PATCHLEVEL__)
10306: # else
10307: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10308: + __GNUC_MINOR__ * 100)
10309: # endif
1.174 brouard 10310: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10311: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10312:
10313: if (uname(&sysInfo) != -1) {
10314: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10315: 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 10316: }
10317: else
10318: perror("uname() error");
1.179 brouard 10319: //#ifndef __INTEL_COMPILER
10320: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10321: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10322: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10323: #endif
1.169 brouard 10324: #endif
1.172 brouard 10325:
1.286 brouard 10326: // void main ()
1.172 brouard 10327: // {
1.169 brouard 10328: #if defined(_MSC_VER)
1.174 brouard 10329: if (IsWow64()){
1.191 brouard 10330: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10331: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10332: }
10333: else{
1.191 brouard 10334: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10335: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10336: }
1.172 brouard 10337: // printf("\nPress Enter to continue...");
10338: // getchar();
10339: // }
10340:
1.169 brouard 10341: #endif
10342:
1.167 brouard 10343:
1.219 brouard 10344: }
1.136 brouard 10345:
1.219 brouard 10346: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 ! brouard 10347: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.235 brouard 10348: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10349: /* double ftolpl = 1.e-10; */
1.180 brouard 10350: double age, agebase, agelim;
1.203 brouard 10351: double tot;
1.180 brouard 10352:
1.202 brouard 10353: strcpy(filerespl,"PL_");
10354: strcat(filerespl,fileresu);
10355: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 ! brouard 10356: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
! 10357: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 10358: }
1.288 ! brouard 10359: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
! 10360: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10361: pstamp(ficrespl);
1.288 ! brouard 10362: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10363: fprintf(ficrespl,"#Age ");
10364: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10365: fprintf(ficrespl,"\n");
1.180 brouard 10366:
1.219 brouard 10367: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10368:
1.219 brouard 10369: agebase=ageminpar;
10370: agelim=agemaxpar;
1.180 brouard 10371:
1.227 brouard 10372: /* i1=pow(2,ncoveff); */
1.234 brouard 10373: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10374: if (cptcovn < 1){i1=1;}
1.180 brouard 10375:
1.238 brouard 10376: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10377: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10378: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10379: continue;
1.235 brouard 10380:
1.238 brouard 10381: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10382: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10383: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10384: /* k=k+1; */
10385: /* to clean */
10386: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10387: fprintf(ficrespl,"#******");
10388: printf("#******");
10389: fprintf(ficlog,"#******");
10390: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10391: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10392: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10393: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10394: }
10395: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10396: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10397: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10398: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10399: }
10400: fprintf(ficrespl,"******\n");
10401: printf("******\n");
10402: fprintf(ficlog,"******\n");
10403: if(invalidvarcomb[k]){
10404: printf("\nCombination (%d) ignored because no case \n",k);
10405: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10406: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10407: continue;
10408: }
1.219 brouard 10409:
1.238 brouard 10410: fprintf(ficrespl,"#Age ");
10411: for(j=1;j<=cptcoveff;j++) {
10412: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10413: }
10414: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10415: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10416:
1.238 brouard 10417: for (age=agebase; age<=agelim; age++){
10418: /* for (age=agebase; age<=agebase; age++){ */
10419: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10420: fprintf(ficrespl,"%.0f ",age );
10421: for(j=1;j<=cptcoveff;j++)
10422: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10423: tot=0.;
10424: for(i=1; i<=nlstate;i++){
10425: tot += prlim[i][i];
10426: fprintf(ficrespl," %.5f", prlim[i][i]);
10427: }
10428: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10429: } /* Age */
10430: /* was end of cptcod */
10431: } /* cptcov */
10432: } /* nres */
1.219 brouard 10433: return 0;
1.180 brouard 10434: }
10435:
1.218 brouard 10436: int back_prevalence_limit(double *p, double **bprlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp, double dateprev1,double dateprev2, int firstpass, int lastpass, int mobilavproj){
1.288 ! brouard 10437: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 10438:
10439: /* Computes the back prevalence limit for any combination of covariate values
10440: * at any age between ageminpar and agemaxpar
10441: */
1.235 brouard 10442: int i, j, k, i1, nres=0 ;
1.217 brouard 10443: /* double ftolpl = 1.e-10; */
10444: double age, agebase, agelim;
10445: double tot;
1.218 brouard 10446: /* double ***mobaverage; */
10447: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10448:
10449: strcpy(fileresplb,"PLB_");
10450: strcat(fileresplb,fileresu);
10451: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 ! brouard 10452: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
! 10453: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 10454: }
1.288 ! brouard 10455: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
! 10456: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 10457: pstamp(ficresplb);
1.288 ! brouard 10458: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 10459: fprintf(ficresplb,"#Age ");
10460: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10461: fprintf(ficresplb,"\n");
10462:
1.218 brouard 10463:
10464: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10465:
10466: agebase=ageminpar;
10467: agelim=agemaxpar;
10468:
10469:
1.227 brouard 10470: i1=pow(2,cptcoveff);
1.218 brouard 10471: if (cptcovn < 1){i1=1;}
1.227 brouard 10472:
1.238 brouard 10473: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10474: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10475: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10476: continue;
10477: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10478: fprintf(ficresplb,"#******");
10479: printf("#******");
10480: fprintf(ficlog,"#******");
10481: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10482: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10483: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10484: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10485: }
10486: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10487: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10488: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10489: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10490: }
10491: fprintf(ficresplb,"******\n");
10492: printf("******\n");
10493: fprintf(ficlog,"******\n");
10494: if(invalidvarcomb[k]){
10495: printf("\nCombination (%d) ignored because no cases \n",k);
10496: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10497: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10498: continue;
10499: }
1.218 brouard 10500:
1.238 brouard 10501: fprintf(ficresplb,"#Age ");
10502: for(j=1;j<=cptcoveff;j++) {
10503: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10504: }
10505: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10506: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10507:
10508:
1.238 brouard 10509: for (age=agebase; age<=agelim; age++){
10510: /* for (age=agebase; age<=agebase; age++){ */
10511: if(mobilavproj > 0){
10512: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10513: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10514: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10515: }else if (mobilavproj == 0){
10516: 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);
10517: 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);
10518: exit(1);
10519: }else{
10520: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10521: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10522: /* printf("TOTOT\n"); */
10523: /* exit(1); */
1.238 brouard 10524: }
10525: fprintf(ficresplb,"%.0f ",age );
10526: for(j=1;j<=cptcoveff;j++)
10527: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10528: tot=0.;
10529: for(i=1; i<=nlstate;i++){
10530: tot += bprlim[i][i];
10531: fprintf(ficresplb," %.5f", bprlim[i][i]);
10532: }
10533: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10534: } /* Age */
10535: /* was end of cptcod */
1.255 brouard 10536: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10537: } /* end of any combination */
10538: } /* end of nres */
1.218 brouard 10539: /* hBijx(p, bage, fage); */
10540: /* fclose(ficrespijb); */
10541:
10542: return 0;
1.217 brouard 10543: }
1.218 brouard 10544:
1.180 brouard 10545: int hPijx(double *p, int bage, int fage){
10546: /*------------- h Pij x at various ages ------------*/
10547:
10548: int stepsize;
10549: int agelim;
10550: int hstepm;
10551: int nhstepm;
1.235 brouard 10552: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10553:
10554: double agedeb;
10555: double ***p3mat;
10556:
1.201 brouard 10557: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10558: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10559: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10560: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10561: }
10562: printf("Computing pij: result on file '%s' \n", filerespij);
10563: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10564:
10565: stepsize=(int) (stepm+YEARM-1)/YEARM;
10566: /*if (stepm<=24) stepsize=2;*/
10567:
10568: agelim=AGESUP;
10569: hstepm=stepsize*YEARM; /* Every year of age */
10570: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10571:
1.180 brouard 10572: /* hstepm=1; aff par mois*/
10573: pstamp(ficrespij);
10574: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10575: i1= pow(2,cptcoveff);
1.218 brouard 10576: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10577: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10578: /* k=k+1; */
1.235 brouard 10579: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10580: for(k=1; k<=i1;k++){
1.253 brouard 10581: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10582: continue;
1.183 brouard 10583: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10584: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10585: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10586: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10587: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10588: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10589: }
1.183 brouard 10590: fprintf(ficrespij,"******\n");
10591:
10592: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10593: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10594: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10595:
10596: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10597:
1.183 brouard 10598: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10599: oldm=oldms;savm=savms;
1.235 brouard 10600: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10601: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10602: for(i=1; i<=nlstate;i++)
10603: for(j=1; j<=nlstate+ndeath;j++)
10604: fprintf(ficrespij," %1d-%1d",i,j);
10605: fprintf(ficrespij,"\n");
10606: for (h=0; h<=nhstepm; h++){
10607: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10608: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10609: for(i=1; i<=nlstate;i++)
10610: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10611: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10612: fprintf(ficrespij,"\n");
10613: }
1.183 brouard 10614: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10615: fprintf(ficrespij,"\n");
10616: }
1.180 brouard 10617: /*}*/
10618: }
1.218 brouard 10619: return 0;
1.180 brouard 10620: }
1.218 brouard 10621:
10622: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10623: /*------------- h Bij x at various ages ------------*/
10624:
10625: int stepsize;
1.218 brouard 10626: /* int agelim; */
10627: int ageminl;
1.217 brouard 10628: int hstepm;
10629: int nhstepm;
1.238 brouard 10630: int h, i, i1, j, k, nres;
1.218 brouard 10631:
1.217 brouard 10632: double agedeb;
10633: double ***p3mat;
1.218 brouard 10634:
10635: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10636: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10637: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10638: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10639: }
10640: printf("Computing pij back: result on file '%s' \n", filerespijb);
10641: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10642:
10643: stepsize=(int) (stepm+YEARM-1)/YEARM;
10644: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10645:
1.218 brouard 10646: /* agelim=AGESUP; */
10647: ageminl=30;
10648: hstepm=stepsize*YEARM; /* Every year of age */
10649: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10650:
10651: /* hstepm=1; aff par mois*/
10652: pstamp(ficrespijb);
1.255 brouard 10653: 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 10654: i1= pow(2,cptcoveff);
1.218 brouard 10655: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10656: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10657: /* k=k+1; */
1.238 brouard 10658: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10659: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10660: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10661: continue;
10662: fprintf(ficrespijb,"\n#****** ");
10663: for(j=1;j<=cptcoveff;j++)
10664: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10665: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10666: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10667: }
10668: fprintf(ficrespijb,"******\n");
1.264 brouard 10669: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10670: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10671: continue;
10672: }
10673:
10674: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10675: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10676: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
10677: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10678: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
10679:
10680: /* nhstepm=nhstepm*YEARM; aff par mois*/
10681:
1.266 brouard 10682: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10683: /* and memory limitations if stepm is small */
10684:
1.238 brouard 10685: /* oldm=oldms;savm=savms; */
10686: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10687: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10688: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10689: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10690: for(i=1; i<=nlstate;i++)
10691: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10692: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10693: fprintf(ficrespijb,"\n");
1.238 brouard 10694: for (h=0; h<=nhstepm; h++){
10695: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10696: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10697: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10698: for(i=1; i<=nlstate;i++)
10699: for(j=1; j<=nlstate+ndeath;j++)
10700: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10701: fprintf(ficrespijb,"\n");
10702: }
10703: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10704: fprintf(ficrespijb,"\n");
10705: } /* end age deb */
10706: } /* end combination */
10707: } /* end nres */
1.218 brouard 10708: return 0;
10709: } /* hBijx */
1.217 brouard 10710:
1.180 brouard 10711:
1.136 brouard 10712: /***********************************************/
10713: /**************** Main Program *****************/
10714: /***********************************************/
10715:
10716: int main(int argc, char *argv[])
10717: {
10718: #ifdef GSL
10719: const gsl_multimin_fminimizer_type *T;
10720: size_t iteri = 0, it;
10721: int rval = GSL_CONTINUE;
10722: int status = GSL_SUCCESS;
10723: double ssval;
10724: #endif
10725: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.164 brouard 10726: int i,j, k, n=MAXN,iter=0,m,size=100, cptcod;
1.209 brouard 10727: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10728: int jj, ll, li, lj, lk;
1.136 brouard 10729: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10730: int num_filled;
1.136 brouard 10731: int itimes;
10732: int NDIM=2;
10733: int vpopbased=0;
1.235 brouard 10734: int nres=0;
1.258 brouard 10735: int endishere=0;
1.277 brouard 10736: int noffset=0;
1.274 brouard 10737: int ncurrv=0; /* Temporary variable */
10738:
1.164 brouard 10739: char ca[32], cb[32];
1.136 brouard 10740: /* FILE *fichtm; *//* Html File */
10741: /* FILE *ficgp;*/ /*Gnuplot File */
10742: struct stat info;
1.191 brouard 10743: double agedeb=0.;
1.194 brouard 10744:
10745: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10746: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10747:
1.165 brouard 10748: double fret;
1.191 brouard 10749: double dum=0.; /* Dummy variable */
1.136 brouard 10750: double ***p3mat;
1.218 brouard 10751: /* double ***mobaverage; */
1.164 brouard 10752:
10753: char line[MAXLINE];
1.197 brouard 10754: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10755:
1.234 brouard 10756: char modeltemp[MAXLINE];
1.230 brouard 10757: char resultline[MAXLINE];
10758:
1.136 brouard 10759: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10760: char *tok, *val; /* pathtot */
1.136 brouard 10761: int firstobs=1, lastobs=10;
1.195 brouard 10762: int c, h , cpt, c2;
1.191 brouard 10763: int jl=0;
10764: int i1, j1, jk, stepsize=0;
1.194 brouard 10765: int count=0;
10766:
1.164 brouard 10767: int *tab;
1.136 brouard 10768: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.217 brouard 10769: int backcast=0;
1.136 brouard 10770: int mobilav=0,popforecast=0;
1.191 brouard 10771: int hstepm=0, nhstepm=0;
1.136 brouard 10772: int agemortsup;
10773: float sumlpop=0.;
10774: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
10775: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
10776:
1.191 brouard 10777: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 10778: double ftolpl=FTOL;
10779: double **prlim;
1.217 brouard 10780: double **bprlim;
1.136 brouard 10781: double ***param; /* Matrix of parameters */
1.251 brouard 10782: double ***paramstart; /* Matrix of starting parameter values */
10783: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 10784: double **matcov; /* Matrix of covariance */
1.203 brouard 10785: double **hess; /* Hessian matrix */
1.136 brouard 10786: double ***delti3; /* Scale */
10787: double *delti; /* Scale */
10788: double ***eij, ***vareij;
10789: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 10790:
1.136 brouard 10791: double *epj, vepp;
1.164 brouard 10792:
1.273 brouard 10793: double dateprev1, dateprev2;
10794: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0;
10795: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0;
1.217 brouard 10796:
1.136 brouard 10797: double **ximort;
1.145 brouard 10798: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 10799: int *dcwave;
10800:
1.164 brouard 10801: char z[1]="c";
1.136 brouard 10802:
10803: /*char *strt;*/
10804: char strtend[80];
1.126 brouard 10805:
1.164 brouard 10806:
1.126 brouard 10807: /* setlocale (LC_ALL, ""); */
10808: /* bindtextdomain (PACKAGE, LOCALEDIR); */
10809: /* textdomain (PACKAGE); */
10810: /* setlocale (LC_CTYPE, ""); */
10811: /* setlocale (LC_MESSAGES, ""); */
10812:
10813: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 10814: rstart_time = time(NULL);
10815: /* (void) gettimeofday(&start_time,&tzp);*/
10816: start_time = *localtime(&rstart_time);
1.126 brouard 10817: curr_time=start_time;
1.157 brouard 10818: /*tml = *localtime(&start_time.tm_sec);*/
10819: /* strcpy(strstart,asctime(&tml)); */
10820: strcpy(strstart,asctime(&start_time));
1.126 brouard 10821:
10822: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 10823: /* tp.tm_sec = tp.tm_sec +86400; */
10824: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 10825: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
10826: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
10827: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 10828: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 10829: /* strt=asctime(&tmg); */
10830: /* printf("Time(after) =%s",strstart); */
10831: /* (void) time (&time_value);
10832: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
10833: * tm = *localtime(&time_value);
10834: * strstart=asctime(&tm);
10835: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
10836: */
10837:
10838: nberr=0; /* Number of errors and warnings */
10839: nbwarn=0;
1.184 brouard 10840: #ifdef WIN32
10841: _getcwd(pathcd, size);
10842: #else
1.126 brouard 10843: getcwd(pathcd, size);
1.184 brouard 10844: #endif
1.191 brouard 10845: syscompilerinfo(0);
1.196 brouard 10846: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 10847: if(argc <=1){
10848: printf("\nEnter the parameter file name: ");
1.205 brouard 10849: if(!fgets(pathr,FILENAMELENGTH,stdin)){
10850: printf("ERROR Empty parameter file name\n");
10851: goto end;
10852: }
1.126 brouard 10853: i=strlen(pathr);
10854: if(pathr[i-1]=='\n')
10855: pathr[i-1]='\0';
1.156 brouard 10856: i=strlen(pathr);
1.205 brouard 10857: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 10858: pathr[i-1]='\0';
1.205 brouard 10859: }
10860: i=strlen(pathr);
10861: if( i==0 ){
10862: printf("ERROR Empty parameter file name\n");
10863: goto end;
10864: }
10865: for (tok = pathr; tok != NULL; ){
1.126 brouard 10866: printf("Pathr |%s|\n",pathr);
10867: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
10868: printf("val= |%s| pathr=%s\n",val,pathr);
10869: strcpy (pathtot, val);
10870: if(pathr[0] == '\0') break; /* Dirty */
10871: }
10872: }
1.281 brouard 10873: else if (argc<=2){
10874: strcpy(pathtot,argv[1]);
10875: }
1.126 brouard 10876: else{
10877: strcpy(pathtot,argv[1]);
1.281 brouard 10878: strcpy(z,argv[2]);
10879: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 10880: }
10881: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
10882: /*cygwin_split_path(pathtot,path,optionfile);
10883: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
10884: /* cutv(path,optionfile,pathtot,'\\');*/
10885:
10886: /* Split argv[0], imach program to get pathimach */
10887: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
10888: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10889: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10890: /* strcpy(pathimach,argv[0]); */
10891: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
10892: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
10893: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 10894: #ifdef WIN32
10895: _chdir(path); /* Can be a relative path */
10896: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
10897: #else
1.126 brouard 10898: chdir(path); /* Can be a relative path */
1.184 brouard 10899: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
10900: #endif
10901: printf("Current directory %s!\n",pathcd);
1.126 brouard 10902: strcpy(command,"mkdir ");
10903: strcat(command,optionfilefiname);
10904: if((outcmd=system(command)) != 0){
1.169 brouard 10905: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 10906: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
10907: /* fclose(ficlog); */
10908: /* exit(1); */
10909: }
10910: /* if((imk=mkdir(optionfilefiname))<0){ */
10911: /* perror("mkdir"); */
10912: /* } */
10913:
10914: /*-------- arguments in the command line --------*/
10915:
1.186 brouard 10916: /* Main Log file */
1.126 brouard 10917: strcat(filelog, optionfilefiname);
10918: strcat(filelog,".log"); /* */
10919: if((ficlog=fopen(filelog,"w"))==NULL) {
10920: printf("Problem with logfile %s\n",filelog);
10921: goto end;
10922: }
10923: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 10924: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 10925: fprintf(ficlog,"\nEnter the parameter file name: \n");
10926: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
10927: path=%s \n\
10928: optionfile=%s\n\
10929: optionfilext=%s\n\
1.156 brouard 10930: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 10931:
1.197 brouard 10932: syscompilerinfo(1);
1.167 brouard 10933:
1.126 brouard 10934: printf("Local time (at start):%s",strstart);
10935: fprintf(ficlog,"Local time (at start): %s",strstart);
10936: fflush(ficlog);
10937: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 10938: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 10939:
10940: /* */
10941: strcpy(fileres,"r");
10942: strcat(fileres, optionfilefiname);
1.201 brouard 10943: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 10944: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 10945: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 10946:
1.186 brouard 10947: /* Main ---------arguments file --------*/
1.126 brouard 10948:
10949: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 10950: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
10951: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 10952: fflush(ficlog);
1.149 brouard 10953: /* goto end; */
10954: exit(70);
1.126 brouard 10955: }
10956:
10957: strcpy(filereso,"o");
1.201 brouard 10958: strcat(filereso,fileresu);
1.126 brouard 10959: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
10960: printf("Problem with Output resultfile: %s\n", filereso);
10961: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
10962: fflush(ficlog);
10963: goto end;
10964: }
1.278 brouard 10965: /*-------- Rewriting parameter file ----------*/
10966: strcpy(rfileres,"r"); /* "Rparameterfile */
10967: strcat(rfileres,optionfilefiname); /* Parameter file first name */
10968: strcat(rfileres,"."); /* */
10969: strcat(rfileres,optionfilext); /* Other files have txt extension */
10970: if((ficres =fopen(rfileres,"w"))==NULL) {
10971: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
10972: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
10973: fflush(ficlog);
10974: goto end;
10975: }
10976: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 10977:
1.278 brouard 10978:
1.126 brouard 10979: /* Reads comments: lines beginning with '#' */
10980: numlinepar=0;
1.277 brouard 10981: /* Is it a BOM UTF-8 Windows file? */
10982: /* First parameter line */
1.197 brouard 10983: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 10984: noffset=0;
10985: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10986: {
10987: noffset=noffset+3;
10988: printf("# File is an UTF8 Bom.\n"); // 0xBF
10989: }
10990: else if( line[0] == (char)0xFE && line[1] == (char)0xFF)
10991: {
10992: noffset=noffset+2;
10993: printf("# File is an UTF16BE BOM file\n");
10994: }
10995: else if( line[0] == 0 && line[1] == 0)
10996: {
10997: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10998: noffset=noffset+4;
10999: printf("# File is an UTF16BE BOM file\n");
11000: }
11001: } else{
11002: ;/*printf(" Not a BOM file\n");*/
11003: }
11004:
1.197 brouard 11005: /* If line starts with a # it is a comment */
1.277 brouard 11006: if (line[noffset] == '#') {
1.197 brouard 11007: numlinepar++;
11008: fputs(line,stdout);
11009: fputs(line,ficparo);
1.278 brouard 11010: fputs(line,ficres);
1.197 brouard 11011: fputs(line,ficlog);
11012: continue;
11013: }else
11014: break;
11015: }
11016: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
11017: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
11018: if (num_filled != 5) {
11019: printf("Should be 5 parameters\n");
1.283 brouard 11020: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 11021: }
1.126 brouard 11022: numlinepar++;
1.197 brouard 11023: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 11024: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11025: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
11026: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 11027: }
11028: /* Second parameter line */
11029: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 11030: /* while(fscanf(ficpar,"%[^\n]", line)) { */
11031: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 11032: if (line[0] == '#') {
11033: numlinepar++;
1.283 brouard 11034: printf("%s",line);
11035: fprintf(ficres,"%s",line);
11036: fprintf(ficparo,"%s",line);
11037: fprintf(ficlog,"%s",line);
1.197 brouard 11038: continue;
11039: }else
11040: break;
11041: }
1.223 brouard 11042: 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", \
11043: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
11044: if (num_filled != 11) {
11045: 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 11046: printf("but line=%s\n",line);
1.283 brouard 11047: 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");
11048: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 11049: }
1.286 brouard 11050: if( lastpass > maxwav){
11051: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11052: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
11053: fflush(ficlog);
11054: goto end;
11055: }
11056: 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 11057: fprintf(ficparo,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, mle, weightopt);
1.286 brouard 11058: fprintf(ficres,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, 0, weightopt);
1.283 brouard 11059: 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 11060: }
1.203 brouard 11061: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 11062: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 11063: /* Third parameter line */
11064: while(fgets(line, MAXLINE, ficpar)) {
11065: /* If line starts with a # it is a comment */
11066: if (line[0] == '#') {
11067: numlinepar++;
1.283 brouard 11068: printf("%s",line);
11069: fprintf(ficres,"%s",line);
11070: fprintf(ficparo,"%s",line);
11071: fprintf(ficlog,"%s",line);
1.197 brouard 11072: continue;
11073: }else
11074: break;
11075: }
1.201 brouard 11076: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.279 brouard 11077: if (num_filled != 1){
11078: printf("ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
11079: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age' %s\n",num_filled, line);
1.197 brouard 11080: model[0]='\0';
11081: goto end;
11082: }
11083: else{
11084: if (model[0]=='+'){
11085: for(i=1; i<=strlen(model);i++)
11086: modeltemp[i-1]=model[i];
1.201 brouard 11087: strcpy(model,modeltemp);
1.197 brouard 11088: }
11089: }
1.199 brouard 11090: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 11091: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 11092: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
11093: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
11094: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 11095: }
11096: /* 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); */
11097: /* numlinepar=numlinepar+3; /\* In general *\/ */
11098: /* 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 11099: /* 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); */
11100: /* 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 11101: fflush(ficlog);
1.190 brouard 11102: /* if(model[0]=='#'|| model[0]== '\0'){ */
11103: if(model[0]=='#'){
1.279 brouard 11104: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
11105: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
11106: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 11107: if(mle != -1){
1.279 brouard 11108: 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 11109: exit(1);
11110: }
11111: }
1.126 brouard 11112: while((c=getc(ficpar))=='#' && c!= EOF){
11113: ungetc(c,ficpar);
11114: fgets(line, MAXLINE, ficpar);
11115: numlinepar++;
1.195 brouard 11116: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
11117: z[0]=line[1];
11118: }
11119: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 11120: fputs(line, stdout);
11121: //puts(line);
1.126 brouard 11122: fputs(line,ficparo);
11123: fputs(line,ficlog);
11124: }
11125: ungetc(c,ficpar);
11126:
11127:
1.145 brouard 11128: covar=matrix(0,NCOVMAX,1,n); /**< used in readdata */
1.268 brouard 11129: if(nqv>=1)coqvar=matrix(1,nqv,1,n); /**< Fixed quantitative covariate */
11130: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,1,n); /**< Time varying quantitative covariate */
11131: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,1,n); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 11132: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
11133: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
11134: v1+v2*age+v2*v3 makes cptcovn = 3
11135: */
11136: if (strlen(model)>1)
1.187 brouard 11137: 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 11138: else
1.187 brouard 11139: ncovmodel=2; /* Constant and age */
1.133 brouard 11140: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
11141: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 11142: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
11143: 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);
11144: 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);
11145: fflush(stdout);
11146: fclose (ficlog);
11147: goto end;
11148: }
1.126 brouard 11149: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11150: delti=delti3[1][1];
11151: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
11152: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 11153: /* We could also provide initial parameters values giving by simple logistic regression
11154: * only one way, that is without matrix product. We will have nlstate maximizations */
11155: /* for(i=1;i<nlstate;i++){ */
11156: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11157: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11158: /* } */
1.126 brouard 11159: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 11160: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
11161: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11162: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11163: fclose (ficparo);
11164: fclose (ficlog);
11165: goto end;
11166: exit(0);
1.220 brouard 11167: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 11168: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 11169: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
11170: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 11171: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
11172: matcov=matrix(1,npar,1,npar);
1.203 brouard 11173: hess=matrix(1,npar,1,npar);
1.220 brouard 11174: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 11175: /* Read guessed parameters */
1.126 brouard 11176: /* Reads comments: lines beginning with '#' */
11177: while((c=getc(ficpar))=='#' && c!= EOF){
11178: ungetc(c,ficpar);
11179: fgets(line, MAXLINE, ficpar);
11180: numlinepar++;
1.141 brouard 11181: fputs(line,stdout);
1.126 brouard 11182: fputs(line,ficparo);
11183: fputs(line,ficlog);
11184: }
11185: ungetc(c,ficpar);
11186:
11187: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 11188: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 11189: for(i=1; i <=nlstate; i++){
1.234 brouard 11190: j=0;
1.126 brouard 11191: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 11192: if(jj==i) continue;
11193: j++;
11194: fscanf(ficpar,"%1d%1d",&i1,&j1);
11195: if ((i1 != i) || (j1 != jj)){
11196: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 11197: It might be a problem of design; if ncovcol and the model are correct\n \
11198: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 11199: exit(1);
11200: }
11201: fprintf(ficparo,"%1d%1d",i1,j1);
11202: if(mle==1)
11203: printf("%1d%1d",i,jj);
11204: fprintf(ficlog,"%1d%1d",i,jj);
11205: for(k=1; k<=ncovmodel;k++){
11206: fscanf(ficpar," %lf",¶m[i][j][k]);
11207: if(mle==1){
11208: printf(" %lf",param[i][j][k]);
11209: fprintf(ficlog," %lf",param[i][j][k]);
11210: }
11211: else
11212: fprintf(ficlog," %lf",param[i][j][k]);
11213: fprintf(ficparo," %lf",param[i][j][k]);
11214: }
11215: fscanf(ficpar,"\n");
11216: numlinepar++;
11217: if(mle==1)
11218: printf("\n");
11219: fprintf(ficlog,"\n");
11220: fprintf(ficparo,"\n");
1.126 brouard 11221: }
11222: }
11223: fflush(ficlog);
1.234 brouard 11224:
1.251 brouard 11225: /* Reads parameters values */
1.126 brouard 11226: p=param[1][1];
1.251 brouard 11227: pstart=paramstart[1][1];
1.126 brouard 11228:
11229: /* Reads comments: lines beginning with '#' */
11230: while((c=getc(ficpar))=='#' && c!= EOF){
11231: ungetc(c,ficpar);
11232: fgets(line, MAXLINE, ficpar);
11233: numlinepar++;
1.141 brouard 11234: fputs(line,stdout);
1.126 brouard 11235: fputs(line,ficparo);
11236: fputs(line,ficlog);
11237: }
11238: ungetc(c,ficpar);
11239:
11240: for(i=1; i <=nlstate; i++){
11241: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11242: fscanf(ficpar,"%1d%1d",&i1,&j1);
11243: if ( (i1-i) * (j1-j) != 0){
11244: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11245: exit(1);
11246: }
11247: printf("%1d%1d",i,j);
11248: fprintf(ficparo,"%1d%1d",i1,j1);
11249: fprintf(ficlog,"%1d%1d",i1,j1);
11250: for(k=1; k<=ncovmodel;k++){
11251: fscanf(ficpar,"%le",&delti3[i][j][k]);
11252: printf(" %le",delti3[i][j][k]);
11253: fprintf(ficparo," %le",delti3[i][j][k]);
11254: fprintf(ficlog," %le",delti3[i][j][k]);
11255: }
11256: fscanf(ficpar,"\n");
11257: numlinepar++;
11258: printf("\n");
11259: fprintf(ficparo,"\n");
11260: fprintf(ficlog,"\n");
1.126 brouard 11261: }
11262: }
11263: fflush(ficlog);
1.234 brouard 11264:
1.145 brouard 11265: /* Reads covariance matrix */
1.126 brouard 11266: delti=delti3[1][1];
1.220 brouard 11267:
11268:
1.126 brouard 11269: /* 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 11270:
1.126 brouard 11271: /* Reads comments: lines beginning with '#' */
11272: while((c=getc(ficpar))=='#' && c!= EOF){
11273: ungetc(c,ficpar);
11274: fgets(line, MAXLINE, ficpar);
11275: numlinepar++;
1.141 brouard 11276: fputs(line,stdout);
1.126 brouard 11277: fputs(line,ficparo);
11278: fputs(line,ficlog);
11279: }
11280: ungetc(c,ficpar);
1.220 brouard 11281:
1.126 brouard 11282: matcov=matrix(1,npar,1,npar);
1.203 brouard 11283: hess=matrix(1,npar,1,npar);
1.131 brouard 11284: for(i=1; i <=npar; i++)
11285: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11286:
1.194 brouard 11287: /* Scans npar lines */
1.126 brouard 11288: for(i=1; i <=npar; i++){
1.226 brouard 11289: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11290: if(count != 3){
1.226 brouard 11291: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11292: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11293: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11294: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11295: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11296: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11297: exit(1);
1.220 brouard 11298: }else{
1.226 brouard 11299: if(mle==1)
11300: printf("%1d%1d%d",i1,j1,jk);
11301: }
11302: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11303: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11304: for(j=1; j <=i; j++){
1.226 brouard 11305: fscanf(ficpar," %le",&matcov[i][j]);
11306: if(mle==1){
11307: printf(" %.5le",matcov[i][j]);
11308: }
11309: fprintf(ficlog," %.5le",matcov[i][j]);
11310: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11311: }
11312: fscanf(ficpar,"\n");
11313: numlinepar++;
11314: if(mle==1)
1.220 brouard 11315: printf("\n");
1.126 brouard 11316: fprintf(ficlog,"\n");
11317: fprintf(ficparo,"\n");
11318: }
1.194 brouard 11319: /* End of read covariance matrix npar lines */
1.126 brouard 11320: for(i=1; i <=npar; i++)
11321: for(j=i+1;j<=npar;j++)
1.226 brouard 11322: matcov[i][j]=matcov[j][i];
1.126 brouard 11323:
11324: if(mle==1)
11325: printf("\n");
11326: fprintf(ficlog,"\n");
11327:
11328: fflush(ficlog);
11329:
11330: } /* End of mle != -3 */
1.218 brouard 11331:
1.186 brouard 11332: /* Main data
11333: */
1.126 brouard 11334: n= lastobs;
11335: num=lvector(1,n);
11336: moisnais=vector(1,n);
11337: annais=vector(1,n);
11338: moisdc=vector(1,n);
11339: andc=vector(1,n);
1.220 brouard 11340: weight=vector(1,n);
1.126 brouard 11341: agedc=vector(1,n);
11342: cod=ivector(1,n);
1.220 brouard 11343: for(i=1;i<=n;i++){
1.234 brouard 11344: num[i]=0;
11345: moisnais[i]=0;
11346: annais[i]=0;
11347: moisdc[i]=0;
11348: andc[i]=0;
11349: agedc[i]=0;
11350: cod[i]=0;
11351: weight[i]=1.0; /* Equal weights, 1 by default */
11352: }
1.126 brouard 11353: mint=matrix(1,maxwav,1,n);
11354: anint=matrix(1,maxwav,1,n);
1.131 brouard 11355: s=imatrix(1,maxwav+1,1,n); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11356: tab=ivector(1,NCOVMAX);
1.144 brouard 11357: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11358: 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 11359:
1.136 brouard 11360: /* Reads data from file datafile */
11361: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11362: goto end;
11363:
11364: /* Calculation of the number of parameters from char model */
1.234 brouard 11365: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11366: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11367: k=3 V4 Tvar[k=3]= 4 (from V4)
11368: k=2 V1 Tvar[k=2]= 1 (from V1)
11369: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11370: */
11371:
11372: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11373: TvarsDind=ivector(1,NCOVMAX); /* */
11374: TvarsD=ivector(1,NCOVMAX); /* */
11375: TvarsQind=ivector(1,NCOVMAX); /* */
11376: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11377: TvarF=ivector(1,NCOVMAX); /* */
11378: TvarFind=ivector(1,NCOVMAX); /* */
11379: TvarV=ivector(1,NCOVMAX); /* */
11380: TvarVind=ivector(1,NCOVMAX); /* */
11381: TvarA=ivector(1,NCOVMAX); /* */
11382: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11383: TvarFD=ivector(1,NCOVMAX); /* */
11384: TvarFDind=ivector(1,NCOVMAX); /* */
11385: TvarFQ=ivector(1,NCOVMAX); /* */
11386: TvarFQind=ivector(1,NCOVMAX); /* */
11387: TvarVD=ivector(1,NCOVMAX); /* */
11388: TvarVDind=ivector(1,NCOVMAX); /* */
11389: TvarVQ=ivector(1,NCOVMAX); /* */
11390: TvarVQind=ivector(1,NCOVMAX); /* */
11391:
1.230 brouard 11392: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11393: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11394: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11395: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11396: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11397: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11398: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11399: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11400: */
11401: /* For model-covariate k tells which data-covariate to use but
11402: because this model-covariate is a construction we invent a new column
11403: ncovcol + k1
11404: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11405: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11406: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11407: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11408: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11409: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11410: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11411: */
1.145 brouard 11412: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11413: 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 11414: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11415: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11416: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11417: 4 covariates (3 plus signs)
11418: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11419: */
1.230 brouard 11420: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11421: * individual dummy, fixed or varying:
11422: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11423: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11424: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11425: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11426: * Tmodelind[1]@9={9,0,3,2,}*/
11427: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11428: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11429: * individual quantitative, fixed or varying:
11430: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11431: * 3, 1, 0, 0, 0, 0, 0, 0},
11432: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11433: /* Main decodemodel */
11434:
1.187 brouard 11435:
1.223 brouard 11436: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11437: goto end;
11438:
1.137 brouard 11439: if((double)(lastobs-imx)/(double)imx > 1.10){
11440: nbwarn++;
11441: 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);
11442: 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);
11443: }
1.136 brouard 11444: /* if(mle==1){*/
1.137 brouard 11445: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11446: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11447: }
11448:
11449: /*-calculation of age at interview from date of interview and age at death -*/
11450: agev=matrix(1,maxwav,1,imx);
11451:
11452: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11453: goto end;
11454:
1.126 brouard 11455:
1.136 brouard 11456: agegomp=(int)agemin;
11457: free_vector(moisnais,1,n);
11458: free_vector(annais,1,n);
1.126 brouard 11459: /* free_matrix(mint,1,maxwav,1,n);
11460: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11461: /* free_vector(moisdc,1,n); */
11462: /* free_vector(andc,1,n); */
1.145 brouard 11463: /* */
11464:
1.126 brouard 11465: wav=ivector(1,imx);
1.214 brouard 11466: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11467: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11468: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11469: 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.*/
11470: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11471: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11472:
11473: /* Concatenates waves */
1.214 brouard 11474: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11475: Death is a valid wave (if date is known).
11476: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11477: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11478: and mw[mi+1][i]. dh depends on stepm.
11479: */
11480:
1.126 brouard 11481: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11482: /* Concatenates waves */
1.145 brouard 11483:
1.215 brouard 11484: free_vector(moisdc,1,n);
11485: free_vector(andc,1,n);
11486:
1.126 brouard 11487: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11488: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11489: ncodemax[1]=1;
1.145 brouard 11490: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11491: cptcoveff=0;
1.220 brouard 11492: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11493: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11494: }
11495:
11496: ncovcombmax=pow(2,cptcoveff);
11497: invalidvarcomb=ivector(1, ncovcombmax);
11498: for(i=1;i<ncovcombmax;i++)
11499: invalidvarcomb[i]=0;
11500:
1.211 brouard 11501: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11502: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11503: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11504:
1.200 brouard 11505: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11506: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11507: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11508: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11509: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11510: * (currently 0 or 1) in the data.
11511: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11512: * corresponding modality (h,j).
11513: */
11514:
1.145 brouard 11515: h=0;
11516: /*if (cptcovn > 0) */
1.126 brouard 11517: m=pow(2,cptcoveff);
11518:
1.144 brouard 11519: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11520: * For k=4 covariates, h goes from 1 to m=2**k
11521: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11522: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11523: * h\k 1 2 3 4
1.143 brouard 11524: *______________________________
11525: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11526: * 2 2 1 1 1
11527: * 3 i=2 1 2 1 1
11528: * 4 2 2 1 1
11529: * 5 i=3 1 i=2 1 2 1
11530: * 6 2 1 2 1
11531: * 7 i=4 1 2 2 1
11532: * 8 2 2 2 1
1.197 brouard 11533: * 9 i=5 1 i=3 1 i=2 1 2
11534: * 10 2 1 1 2
11535: * 11 i=6 1 2 1 2
11536: * 12 2 2 1 2
11537: * 13 i=7 1 i=4 1 2 2
11538: * 14 2 1 2 2
11539: * 15 i=8 1 2 2 2
11540: * 16 2 2 2 2
1.143 brouard 11541: */
1.212 brouard 11542: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11543: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11544: * and the value of each covariate?
11545: * V1=1, V2=1, V3=2, V4=1 ?
11546: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11547: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11548: * In order to get the real value in the data, we use nbcode
11549: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11550: * We are keeping this crazy system in order to be able (in the future?)
11551: * to have more than 2 values (0 or 1) for a covariate.
11552: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11553: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11554: * bbbbbbbb
11555: * 76543210
11556: * h-1 00000101 (6-1=5)
1.219 brouard 11557: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11558: * &
11559: * 1 00000001 (1)
1.219 brouard 11560: * 00000000 = 1 & ((h-1) >> (k-1))
11561: * +1= 00000001 =1
1.211 brouard 11562: *
11563: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11564: * h' 1101 =2^3+2^2+0x2^1+2^0
11565: * >>k' 11
11566: * & 00000001
11567: * = 00000001
11568: * +1 = 00000010=2 = codtabm(14,3)
11569: * Reverse h=6 and m=16?
11570: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11571: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11572: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11573: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11574: * V3=decodtabm(14,3,2**4)=2
11575: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11576: *(h-1) >> (j-1) 0011 =13 >> 2
11577: * &1 000000001
11578: * = 000000001
11579: * +1= 000000010 =2
11580: * 2211
11581: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11582: * V3=2
1.220 brouard 11583: * codtabm and decodtabm are identical
1.211 brouard 11584: */
11585:
1.145 brouard 11586:
11587: free_ivector(Ndum,-1,NCOVMAX);
11588:
11589:
1.126 brouard 11590:
1.186 brouard 11591: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11592: strcpy(optionfilegnuplot,optionfilefiname);
11593: if(mle==-3)
1.201 brouard 11594: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11595: strcat(optionfilegnuplot,".gp");
11596:
11597: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11598: printf("Problem with file %s",optionfilegnuplot);
11599: }
11600: else{
1.204 brouard 11601: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11602: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11603: //fprintf(ficgp,"set missing 'NaNq'\n");
11604: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11605: }
11606: /* fclose(ficgp);*/
1.186 brouard 11607:
11608:
11609: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11610:
11611: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11612: if(mle==-3)
1.201 brouard 11613: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11614: strcat(optionfilehtm,".htm");
11615: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11616: printf("Problem with %s \n",optionfilehtm);
11617: exit(0);
1.126 brouard 11618: }
11619:
11620: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11621: strcat(optionfilehtmcov,"-cov.htm");
11622: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11623: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11624: }
11625: else{
11626: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11627: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11628: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11629: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11630: }
11631:
1.213 brouard 11632: 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 11633: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11634: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11635: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11636: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11637: \n\
11638: <hr size=\"2\" color=\"#EC5E5E\">\
11639: <ul><li><h4>Parameter files</h4>\n\
11640: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11641: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11642: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11643: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11644: - Date and time at start: %s</ul>\n",\
11645: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11646: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11647: fileres,fileres,\
11648: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11649: fflush(fichtm);
11650:
11651: strcpy(pathr,path);
11652: strcat(pathr,optionfilefiname);
1.184 brouard 11653: #ifdef WIN32
11654: _chdir(optionfilefiname); /* Move to directory named optionfile */
11655: #else
1.126 brouard 11656: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11657: #endif
11658:
1.126 brouard 11659:
1.220 brouard 11660: /* Calculates basic frequencies. Computes observed prevalence at single age
11661: and for any valid combination of covariates
1.126 brouard 11662: and prints on file fileres'p'. */
1.251 brouard 11663: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11664: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11665:
11666: fprintf(fichtm,"\n");
1.286 brouard 11667: fprintf(fichtm,"<h4>Parameter line 2</h4><ul><li>Tolerance for the convergence of the likelihood: ftol=%g \n<li>Interval for the elementary matrix (in month): stepm=%d",\
1.274 brouard 11668: ftol, stepm);
11669: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
11670: ncurrv=1;
11671: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
11672: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
11673: ncurrv=i;
11674: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
11675: fprintf(fichtm,"\n<li> Number of time varying (wave varying) covariates: ntv=%d ", ntv);
11676: ncurrv=i;
11677: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
11678: fprintf(fichtm,"\n<li>Number of quantitative time varying covariates: nqtv=%d ", nqtv);
11679: ncurrv=i;
11680: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
11681: 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", \
11682: nlstate, ndeath, maxwav, mle, weightopt);
11683:
11684: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
11685: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
11686:
11687:
11688: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Total number of observations=%d <br>\n\
1.126 brouard 11689: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11690: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 11691: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 11692: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 11693: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11694: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11695: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11696: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11697:
1.126 brouard 11698: /* For Powell, parameters are in a vector p[] starting at p[1]
11699: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11700: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11701:
11702: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11703: /* For mortality only */
1.126 brouard 11704: if (mle==-3){
1.136 brouard 11705: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11706: for(i=1;i<=NDIM;i++)
11707: for(j=1;j<=NDIM;j++)
11708: ximort[i][j]=0.;
1.186 brouard 11709: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.126 brouard 11710: cens=ivector(1,n);
11711: ageexmed=vector(1,n);
11712: agecens=vector(1,n);
11713: dcwave=ivector(1,n);
1.223 brouard 11714:
1.126 brouard 11715: for (i=1; i<=imx; i++){
11716: dcwave[i]=-1;
11717: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11718: if (s[m][i]>nlstate) {
11719: dcwave[i]=m;
11720: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11721: break;
11722: }
1.126 brouard 11723: }
1.226 brouard 11724:
1.126 brouard 11725: for (i=1; i<=imx; i++) {
11726: if (wav[i]>0){
1.226 brouard 11727: ageexmed[i]=agev[mw[1][i]][i];
11728: j=wav[i];
11729: agecens[i]=1.;
11730:
11731: if (ageexmed[i]> 1 && wav[i] > 0){
11732: agecens[i]=agev[mw[j][i]][i];
11733: cens[i]= 1;
11734: }else if (ageexmed[i]< 1)
11735: cens[i]= -1;
11736: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11737: cens[i]=0 ;
1.126 brouard 11738: }
11739: else cens[i]=-1;
11740: }
11741:
11742: for (i=1;i<=NDIM;i++) {
11743: for (j=1;j<=NDIM;j++)
1.226 brouard 11744: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 11745: }
11746:
1.145 brouard 11747: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 11748: /*printf("%lf %lf", p[1], p[2]);*/
11749:
11750:
1.136 brouard 11751: #ifdef GSL
11752: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 11753: #else
1.126 brouard 11754: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 11755: #endif
1.201 brouard 11756: strcpy(filerespow,"POW-MORT_");
11757: strcat(filerespow,fileresu);
1.126 brouard 11758: if((ficrespow=fopen(filerespow,"w"))==NULL) {
11759: printf("Problem with resultfile: %s\n", filerespow);
11760: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
11761: }
1.136 brouard 11762: #ifdef GSL
11763: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 11764: #else
1.126 brouard 11765: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 11766: #endif
1.126 brouard 11767: /* for (i=1;i<=nlstate;i++)
11768: for(j=1;j<=nlstate+ndeath;j++)
11769: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
11770: */
11771: fprintf(ficrespow,"\n");
1.136 brouard 11772: #ifdef GSL
11773: /* gsl starts here */
11774: T = gsl_multimin_fminimizer_nmsimplex;
11775: gsl_multimin_fminimizer *sfm = NULL;
11776: gsl_vector *ss, *x;
11777: gsl_multimin_function minex_func;
11778:
11779: /* Initial vertex size vector */
11780: ss = gsl_vector_alloc (NDIM);
11781:
11782: if (ss == NULL){
11783: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
11784: }
11785: /* Set all step sizes to 1 */
11786: gsl_vector_set_all (ss, 0.001);
11787:
11788: /* Starting point */
1.126 brouard 11789:
1.136 brouard 11790: x = gsl_vector_alloc (NDIM);
11791:
11792: if (x == NULL){
11793: gsl_vector_free(ss);
11794: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
11795: }
11796:
11797: /* Initialize method and iterate */
11798: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 11799: /* gsl_vector_set(x, 0, 0.0268); */
11800: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 11801: gsl_vector_set(x, 0, p[1]);
11802: gsl_vector_set(x, 1, p[2]);
11803:
11804: minex_func.f = &gompertz_f;
11805: minex_func.n = NDIM;
11806: minex_func.params = (void *)&p; /* ??? */
11807:
11808: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
11809: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
11810:
11811: printf("Iterations beginning .....\n\n");
11812: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
11813:
11814: iteri=0;
11815: while (rval == GSL_CONTINUE){
11816: iteri++;
11817: status = gsl_multimin_fminimizer_iterate(sfm);
11818:
11819: if (status) printf("error: %s\n", gsl_strerror (status));
11820: fflush(0);
11821:
11822: if (status)
11823: break;
11824:
11825: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
11826: ssval = gsl_multimin_fminimizer_size (sfm);
11827:
11828: if (rval == GSL_SUCCESS)
11829: printf ("converged to a local maximum at\n");
11830:
11831: printf("%5d ", iteri);
11832: for (it = 0; it < NDIM; it++){
11833: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
11834: }
11835: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
11836: }
11837:
11838: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
11839:
11840: gsl_vector_free(x); /* initial values */
11841: gsl_vector_free(ss); /* inital step size */
11842: for (it=0; it<NDIM; it++){
11843: p[it+1]=gsl_vector_get(sfm->x,it);
11844: fprintf(ficrespow," %.12lf", p[it]);
11845: }
11846: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
11847: #endif
11848: #ifdef POWELL
11849: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
11850: #endif
1.126 brouard 11851: fclose(ficrespow);
11852:
1.203 brouard 11853: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 11854:
11855: for(i=1; i <=NDIM; i++)
11856: for(j=i+1;j<=NDIM;j++)
1.220 brouard 11857: matcov[i][j]=matcov[j][i];
1.126 brouard 11858:
11859: printf("\nCovariance matrix\n ");
1.203 brouard 11860: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 11861: for(i=1; i <=NDIM; i++) {
11862: for(j=1;j<=NDIM;j++){
1.220 brouard 11863: printf("%f ",matcov[i][j]);
11864: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 11865: }
1.203 brouard 11866: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 11867: }
11868:
11869: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 11870: for (i=1;i<=NDIM;i++) {
1.126 brouard 11871: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 11872: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
11873: }
1.126 brouard 11874: lsurv=vector(1,AGESUP);
11875: lpop=vector(1,AGESUP);
11876: tpop=vector(1,AGESUP);
11877: lsurv[agegomp]=100000;
11878:
11879: for (k=agegomp;k<=AGESUP;k++) {
11880: agemortsup=k;
11881: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
11882: }
11883:
11884: for (k=agegomp;k<agemortsup;k++)
11885: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
11886:
11887: for (k=agegomp;k<agemortsup;k++){
11888: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
11889: sumlpop=sumlpop+lpop[k];
11890: }
11891:
11892: tpop[agegomp]=sumlpop;
11893: for (k=agegomp;k<(agemortsup-3);k++){
11894: /* tpop[k+1]=2;*/
11895: tpop[k+1]=tpop[k]-lpop[k];
11896: }
11897:
11898:
11899: printf("\nAge lx qx dx Lx Tx e(x)\n");
11900: for (k=agegomp;k<(agemortsup-2);k++)
11901: 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]);
11902:
11903:
11904: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 11905: ageminpar=50;
11906: agemaxpar=100;
1.194 brouard 11907: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
11908: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11909: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11910: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
11911: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11912: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11913: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 11914: }else{
11915: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
11916: 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 11917: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 11918: }
1.201 brouard 11919: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 11920: stepm, weightopt,\
11921: model,imx,p,matcov,agemortsup);
11922:
11923: free_vector(lsurv,1,AGESUP);
11924: free_vector(lpop,1,AGESUP);
11925: free_vector(tpop,1,AGESUP);
1.220 brouard 11926: free_matrix(ximort,1,NDIM,1,NDIM);
1.136 brouard 11927: free_ivector(cens,1,n);
11928: free_vector(agecens,1,n);
11929: free_ivector(dcwave,1,n);
1.220 brouard 11930: #ifdef GSL
1.136 brouard 11931: #endif
1.186 brouard 11932: } /* Endof if mle==-3 mortality only */
1.205 brouard 11933: /* Standard */
11934: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
11935: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11936: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 11937: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 11938: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11939: for (k=1; k<=npar;k++)
11940: printf(" %d %8.5f",k,p[k]);
11941: printf("\n");
1.205 brouard 11942: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
11943: /* mlikeli uses func not funcone */
1.247 brouard 11944: /* for(i=1;i<nlstate;i++){ */
11945: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11946: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11947: /* } */
1.205 brouard 11948: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
11949: }
11950: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
11951: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11952: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
11953: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11954: }
11955: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 11956: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11957: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11958: for (k=1; k<=npar;k++)
11959: printf(" %d %8.5f",k,p[k]);
11960: printf("\n");
11961:
11962: /*--------- results files --------------*/
1.283 brouard 11963: /* 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 11964:
11965:
11966: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11967: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11968: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11969: for(i=1,jk=1; i <=nlstate; i++){
11970: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 11971: if (k != i) {
11972: printf("%d%d ",i,k);
11973: fprintf(ficlog,"%d%d ",i,k);
11974: fprintf(ficres,"%1d%1d ",i,k);
11975: for(j=1; j <=ncovmodel; j++){
11976: printf("%12.7f ",p[jk]);
11977: fprintf(ficlog,"%12.7f ",p[jk]);
11978: fprintf(ficres,"%12.7f ",p[jk]);
11979: jk++;
11980: }
11981: printf("\n");
11982: fprintf(ficlog,"\n");
11983: fprintf(ficres,"\n");
11984: }
1.126 brouard 11985: }
11986: }
1.203 brouard 11987: if(mle != 0){
11988: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 11989: ftolhess=ftol; /* Usually correct */
1.203 brouard 11990: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
11991: 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");
11992: 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");
11993: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 11994: for(k=1; k <=(nlstate+ndeath); k++){
11995: if (k != i) {
11996: printf("%d%d ",i,k);
11997: fprintf(ficlog,"%d%d ",i,k);
11998: for(j=1; j <=ncovmodel; j++){
11999: 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]));
12000: 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]));
12001: jk++;
12002: }
12003: printf("\n");
12004: fprintf(ficlog,"\n");
12005: }
12006: }
1.193 brouard 12007: }
1.203 brouard 12008: } /* end of hesscov and Wald tests */
1.225 brouard 12009:
1.203 brouard 12010: /* */
1.126 brouard 12011: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
12012: printf("# Scales (for hessian or gradient estimation)\n");
12013: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
12014: for(i=1,jk=1; i <=nlstate; i++){
12015: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 12016: if (j!=i) {
12017: fprintf(ficres,"%1d%1d",i,j);
12018: printf("%1d%1d",i,j);
12019: fprintf(ficlog,"%1d%1d",i,j);
12020: for(k=1; k<=ncovmodel;k++){
12021: printf(" %.5e",delti[jk]);
12022: fprintf(ficlog," %.5e",delti[jk]);
12023: fprintf(ficres," %.5e",delti[jk]);
12024: jk++;
12025: }
12026: printf("\n");
12027: fprintf(ficlog,"\n");
12028: fprintf(ficres,"\n");
12029: }
1.126 brouard 12030: }
12031: }
12032:
12033: 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 12034: if(mle >= 1) /* To big for the screen */
1.126 brouard 12035: 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");
12036: 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");
12037: /* # 121 Var(a12)\n\ */
12038: /* # 122 Cov(b12,a12) Var(b12)\n\ */
12039: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
12040: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
12041: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
12042: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
12043: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
12044: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
12045:
12046:
12047: /* Just to have a covariance matrix which will be more understandable
12048: even is we still don't want to manage dictionary of variables
12049: */
12050: for(itimes=1;itimes<=2;itimes++){
12051: jj=0;
12052: for(i=1; i <=nlstate; i++){
1.225 brouard 12053: for(j=1; j <=nlstate+ndeath; j++){
12054: if(j==i) continue;
12055: for(k=1; k<=ncovmodel;k++){
12056: jj++;
12057: ca[0]= k+'a'-1;ca[1]='\0';
12058: if(itimes==1){
12059: if(mle>=1)
12060: printf("#%1d%1d%d",i,j,k);
12061: fprintf(ficlog,"#%1d%1d%d",i,j,k);
12062: fprintf(ficres,"#%1d%1d%d",i,j,k);
12063: }else{
12064: if(mle>=1)
12065: printf("%1d%1d%d",i,j,k);
12066: fprintf(ficlog,"%1d%1d%d",i,j,k);
12067: fprintf(ficres,"%1d%1d%d",i,j,k);
12068: }
12069: ll=0;
12070: for(li=1;li <=nlstate; li++){
12071: for(lj=1;lj <=nlstate+ndeath; lj++){
12072: if(lj==li) continue;
12073: for(lk=1;lk<=ncovmodel;lk++){
12074: ll++;
12075: if(ll<=jj){
12076: cb[0]= lk +'a'-1;cb[1]='\0';
12077: if(ll<jj){
12078: if(itimes==1){
12079: if(mle>=1)
12080: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12081: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12082: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
12083: }else{
12084: if(mle>=1)
12085: printf(" %.5e",matcov[jj][ll]);
12086: fprintf(ficlog," %.5e",matcov[jj][ll]);
12087: fprintf(ficres," %.5e",matcov[jj][ll]);
12088: }
12089: }else{
12090: if(itimes==1){
12091: if(mle>=1)
12092: printf(" Var(%s%1d%1d)",ca,i,j);
12093: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
12094: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
12095: }else{
12096: if(mle>=1)
12097: printf(" %.7e",matcov[jj][ll]);
12098: fprintf(ficlog," %.7e",matcov[jj][ll]);
12099: fprintf(ficres," %.7e",matcov[jj][ll]);
12100: }
12101: }
12102: }
12103: } /* end lk */
12104: } /* end lj */
12105: } /* end li */
12106: if(mle>=1)
12107: printf("\n");
12108: fprintf(ficlog,"\n");
12109: fprintf(ficres,"\n");
12110: numlinepar++;
12111: } /* end k*/
12112: } /*end j */
1.126 brouard 12113: } /* end i */
12114: } /* end itimes */
12115:
12116: fflush(ficlog);
12117: fflush(ficres);
1.225 brouard 12118: while(fgets(line, MAXLINE, ficpar)) {
12119: /* If line starts with a # it is a comment */
12120: if (line[0] == '#') {
12121: numlinepar++;
12122: fputs(line,stdout);
12123: fputs(line,ficparo);
12124: fputs(line,ficlog);
12125: continue;
12126: }else
12127: break;
12128: }
12129:
1.209 brouard 12130: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
12131: /* ungetc(c,ficpar); */
12132: /* fgets(line, MAXLINE, ficpar); */
12133: /* fputs(line,stdout); */
12134: /* fputs(line,ficparo); */
12135: /* } */
12136: /* ungetc(c,ficpar); */
1.126 brouard 12137:
12138: estepm=0;
1.209 brouard 12139: 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 12140:
12141: if (num_filled != 6) {
12142: 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);
12143: 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);
12144: goto end;
12145: }
12146: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
12147: }
12148: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
12149: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
12150:
1.209 brouard 12151: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 12152: if (estepm==0 || estepm < stepm) estepm=stepm;
12153: if (fage <= 2) {
12154: bage = ageminpar;
12155: fage = agemaxpar;
12156: }
12157:
12158: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 12159: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
12160: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 12161:
1.186 brouard 12162: /* Other stuffs, more or less useful */
1.254 brouard 12163: while(fgets(line, MAXLINE, ficpar)) {
12164: /* If line starts with a # it is a comment */
12165: if (line[0] == '#') {
12166: numlinepar++;
12167: fputs(line,stdout);
12168: fputs(line,ficparo);
12169: fputs(line,ficlog);
12170: continue;
12171: }else
12172: break;
12173: }
12174:
12175: 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){
12176:
12177: if (num_filled != 7) {
12178: 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);
12179: 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);
12180: goto end;
12181: }
12182: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
12183: 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);
12184: 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);
12185: 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 12186: }
1.254 brouard 12187:
12188: while(fgets(line, MAXLINE, ficpar)) {
12189: /* If line starts with a # it is a comment */
12190: if (line[0] == '#') {
12191: numlinepar++;
12192: fputs(line,stdout);
12193: fputs(line,ficparo);
12194: fputs(line,ficlog);
12195: continue;
12196: }else
12197: break;
1.126 brouard 12198: }
12199:
12200:
12201: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
12202: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
12203:
1.254 brouard 12204: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
12205: if (num_filled != 1) {
12206: 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);
12207: 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);
12208: goto end;
12209: }
12210: printf("pop_based=%d\n",popbased);
12211: fprintf(ficlog,"pop_based=%d\n",popbased);
12212: fprintf(ficparo,"pop_based=%d\n",popbased);
12213: fprintf(ficres,"pop_based=%d\n",popbased);
12214: }
12215:
1.258 brouard 12216: /* Results */
12217: nresult=0;
12218: do{
12219: if(!fgets(line, MAXLINE, ficpar)){
12220: endishere=1;
12221: parameterline=14;
12222: }else if (line[0] == '#') {
12223: /* If line starts with a # it is a comment */
1.254 brouard 12224: numlinepar++;
12225: fputs(line,stdout);
12226: fputs(line,ficparo);
12227: fputs(line,ficlog);
12228: continue;
1.258 brouard 12229: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12230: parameterline=11;
12231: else if(sscanf(line,"backcast=%[^\n]\n",modeltemp))
12232: parameterline=12;
12233: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
12234: parameterline=13;
12235: else{
12236: parameterline=14;
1.254 brouard 12237: }
1.258 brouard 12238: switch (parameterline){
12239: case 11:
12240: 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){
12241: if (num_filled != 8) {
12242: 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);
12243: 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);
12244: goto end;
12245: }
12246: 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);
12247: 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);
12248: 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);
12249: 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);
12250: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12251: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
12252: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
12253:
1.258 brouard 12254: }
1.254 brouard 12255: break;
1.258 brouard 12256: case 12:
12257: /*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);*/
12258: 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){
12259: if (num_filled != 8) {
1.262 brouard 12260: 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);
12261: 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 12262: goto end;
12263: }
12264: 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);
12265: 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);
12266: 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);
12267: 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);
12268: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 12269: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
12270: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.258 brouard 12271: }
1.230 brouard 12272: break;
1.258 brouard 12273: case 13:
12274: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
12275: if (num_filled == 0){
12276: resultline[0]='\0';
12277: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12278: 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);
12279: break;
12280: } else if (num_filled != 1){
12281: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12282: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12283: }
12284: nresult++; /* Sum of resultlines */
12285: printf("Result %d: result=%s\n",nresult, resultline);
12286: if(nresult > MAXRESULTLINES){
12287: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12288: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12289: goto end;
12290: }
12291: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
12292: fprintf(ficparo,"result: %s\n",resultline);
12293: fprintf(ficres,"result: %s\n",resultline);
12294: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 12295: break;
1.258 brouard 12296: case 14:
1.259 brouard 12297: if(ncovmodel >2 && nresult==0 ){
12298: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12299: goto end;
12300: }
1.259 brouard 12301: break;
1.258 brouard 12302: default:
12303: nresult=1;
12304: decoderesult(".",nresult ); /* No covariate */
12305: }
12306: } /* End switch parameterline */
12307: }while(endishere==0); /* End do */
1.126 brouard 12308:
1.230 brouard 12309: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12310: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12311:
12312: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12313: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12314: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12315: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12316: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12317: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12318: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12319: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12320: }else{
1.270 brouard 12321: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
12322: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, backcast, pathc,p, (int)anproj1-bage, (int)anback1-fage);
1.220 brouard 12323: }
12324: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.258 brouard 12325: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,backcast, estepm, \
1.273 brouard 12326: jprev1,mprev1,anprev1,dateprev1, dateproj1, dateback1,jprev2,mprev2,anprev2,dateprev2,dateproj2, dateback2);
1.220 brouard 12327:
1.225 brouard 12328: /*------------ free_vector -------------*/
12329: /* chdir(path); */
1.220 brouard 12330:
1.215 brouard 12331: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12332: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12333: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12334: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.126 brouard 12335: free_lvector(num,1,n);
12336: free_vector(agedc,1,n);
12337: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12338: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12339: fclose(ficparo);
12340: fclose(ficres);
1.220 brouard 12341:
12342:
1.186 brouard 12343: /* Other results (useful)*/
1.220 brouard 12344:
12345:
1.126 brouard 12346: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12347: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12348: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12349: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12350: fclose(ficrespl);
12351:
12352: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12353: /*#include "hpijx.h"*/
12354: hPijx(p, bage, fage);
1.145 brouard 12355: fclose(ficrespij);
1.227 brouard 12356:
1.220 brouard 12357: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12358: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12359: k=1;
1.126 brouard 12360: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12361:
1.269 brouard 12362: /* Prevalence for each covariate combination in probs[age][status][cov] */
12363: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12364: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12365: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12366: for(k=1;k<=ncovcombmax;k++)
12367: probs[i][j][k]=0.;
1.269 brouard 12368: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
12369: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12370: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 12371: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12372: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12373: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12374: for(k=1;k<=ncovcombmax;k++)
12375: mobaverages[i][j][k]=0.;
1.219 brouard 12376: mobaverage=mobaverages;
12377: if (mobilav!=0) {
1.235 brouard 12378: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12379: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12380: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12381: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12382: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12383: }
1.269 brouard 12384: } else if (mobilavproj !=0) {
1.235 brouard 12385: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12386: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12387: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12388: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12389: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12390: }
1.269 brouard 12391: }else{
12392: printf("Internal error moving average\n");
12393: fflush(stdout);
12394: exit(1);
1.219 brouard 12395: }
12396: }/* end if moving average */
1.227 brouard 12397:
1.126 brouard 12398: /*---------- Forecasting ------------------*/
12399: if(prevfcast==1){
12400: /* if(stepm ==1){*/
1.269 brouard 12401: prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
1.126 brouard 12402: }
1.269 brouard 12403:
12404: /* Backcasting */
1.217 brouard 12405: if(backcast==1){
1.219 brouard 12406: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12407: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12408: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12409:
12410: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12411:
12412: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 12413:
1.219 brouard 12414: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12415: fclose(ficresplb);
12416:
1.222 brouard 12417: hBijx(p, bage, fage, mobaverage);
12418: fclose(ficrespijb);
1.219 brouard 12419:
1.269 brouard 12420: prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2,
12421: mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff);
12422: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12423:
12424:
1.269 brouard 12425: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12426: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12427: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12428: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.269 brouard 12429: } /* end Backcasting */
1.268 brouard 12430:
1.186 brouard 12431:
12432: /* ------ Other prevalence ratios------------ */
1.126 brouard 12433:
1.215 brouard 12434: free_ivector(wav,1,imx);
12435: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12436: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12437: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12438:
12439:
1.127 brouard 12440: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12441:
1.201 brouard 12442: strcpy(filerese,"E_");
12443: strcat(filerese,fileresu);
1.126 brouard 12444: if((ficreseij=fopen(filerese,"w"))==NULL) {
12445: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12446: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12447: }
1.208 brouard 12448: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12449: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12450:
12451: pstamp(ficreseij);
1.219 brouard 12452:
1.235 brouard 12453: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12454: if (cptcovn < 1){i1=1;}
12455:
12456: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12457: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12458: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12459: continue;
1.219 brouard 12460: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12461: printf("\n#****** ");
1.225 brouard 12462: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12463: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12464: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12465: }
12466: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12467: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12468: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12469: }
12470: fprintf(ficreseij,"******\n");
1.235 brouard 12471: printf("******\n");
1.219 brouard 12472:
12473: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12474: oldm=oldms;savm=savms;
1.235 brouard 12475: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12476:
1.219 brouard 12477: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12478: }
12479: fclose(ficreseij);
1.208 brouard 12480: printf("done evsij\n");fflush(stdout);
12481: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 12482:
1.218 brouard 12483:
1.227 brouard 12484: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12485:
1.201 brouard 12486: strcpy(filerest,"T_");
12487: strcat(filerest,fileresu);
1.127 brouard 12488: if((ficrest=fopen(filerest,"w"))==NULL) {
12489: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12490: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12491: }
1.208 brouard 12492: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12493: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12494: strcpy(fileresstde,"STDE_");
12495: strcat(fileresstde,fileresu);
1.126 brouard 12496: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12497: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12498: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12499: }
1.227 brouard 12500: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12501: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12502:
1.201 brouard 12503: strcpy(filerescve,"CVE_");
12504: strcat(filerescve,fileresu);
1.126 brouard 12505: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12506: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12507: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12508: }
1.227 brouard 12509: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12510: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12511:
1.201 brouard 12512: strcpy(fileresv,"V_");
12513: strcat(fileresv,fileresu);
1.126 brouard 12514: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12515: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12516: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12517: }
1.227 brouard 12518: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12519: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12520:
1.235 brouard 12521: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12522: if (cptcovn < 1){i1=1;}
12523:
12524: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12525: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12526: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12527: continue;
1.242 brouard 12528: printf("\n#****** Result for:");
12529: fprintf(ficrest,"\n#****** Result for:");
12530: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12531: for(j=1;j<=cptcoveff;j++){
12532: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12533: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12534: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12535: }
1.235 brouard 12536: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12537: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12538: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12539: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12540: }
1.208 brouard 12541: fprintf(ficrest,"******\n");
1.227 brouard 12542: fprintf(ficlog,"******\n");
12543: printf("******\n");
1.208 brouard 12544:
12545: fprintf(ficresstdeij,"\n#****** ");
12546: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12547: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12548: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12549: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12550: }
1.235 brouard 12551: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12552: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12553: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12554: }
1.208 brouard 12555: fprintf(ficresstdeij,"******\n");
12556: fprintf(ficrescveij,"******\n");
12557:
12558: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12559: /* pstamp(ficresvij); */
1.225 brouard 12560: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12561: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12562: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12563: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12564: }
1.208 brouard 12565: fprintf(ficresvij,"******\n");
12566:
12567: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12568: oldm=oldms;savm=savms;
1.235 brouard 12569: printf(" cvevsij ");
12570: fprintf(ficlog, " cvevsij ");
12571: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12572: printf(" end cvevsij \n ");
12573: fprintf(ficlog, " end cvevsij \n ");
12574:
12575: /*
12576: */
12577: /* goto endfree; */
12578:
12579: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12580: pstamp(ficrest);
12581:
1.269 brouard 12582: epj=vector(1,nlstate+1);
1.208 brouard 12583: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12584: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12585: cptcod= 0; /* To be deleted */
12586: printf("varevsij vpopbased=%d \n",vpopbased);
12587: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12588: 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 12589: 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 ");
12590: if(vpopbased==1)
12591: 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);
12592: else
1.288 ! brouard 12593: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12594: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12595: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12596: fprintf(ficrest,"\n");
12597: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 ! brouard 12598: printf("Computing age specific forward period (stable) prevalences in each health state \n");
! 12599: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 12600: for(age=bage; age <=fage ;age++){
1.235 brouard 12601: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12602: if (vpopbased==1) {
12603: if(mobilav ==0){
12604: for(i=1; i<=nlstate;i++)
12605: prlim[i][i]=probs[(int)age][i][k];
12606: }else{ /* mobilav */
12607: for(i=1; i<=nlstate;i++)
12608: prlim[i][i]=mobaverage[(int)age][i][k];
12609: }
12610: }
1.219 brouard 12611:
1.227 brouard 12612: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12613: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12614: /* printf(" age %4.0f ",age); */
12615: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12616: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12617: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12618: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12619: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12620: }
12621: epj[nlstate+1] +=epj[j];
12622: }
12623: /* printf(" age %4.0f \n",age); */
1.219 brouard 12624:
1.227 brouard 12625: for(i=1, vepp=0.;i <=nlstate;i++)
12626: for(j=1;j <=nlstate;j++)
12627: vepp += vareij[i][j][(int)age];
12628: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12629: for(j=1;j <=nlstate;j++){
12630: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12631: }
12632: fprintf(ficrest,"\n");
12633: }
1.208 brouard 12634: } /* End vpopbased */
1.269 brouard 12635: free_vector(epj,1,nlstate+1);
1.208 brouard 12636: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12637: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 12638: printf("done selection\n");fflush(stdout);
12639: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12640:
1.235 brouard 12641: } /* End k selection */
1.227 brouard 12642:
12643: printf("done State-specific expectancies\n");fflush(stdout);
12644: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12645:
1.288 ! brouard 12646: /* variance-covariance of forward period prevalence*/
1.269 brouard 12647: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12648:
1.227 brouard 12649:
12650: free_vector(weight,1,n);
12651: free_imatrix(Tvard,1,NCOVMAX,1,2);
12652: free_imatrix(s,1,maxwav+1,1,n);
12653: free_matrix(anint,1,maxwav,1,n);
12654: free_matrix(mint,1,maxwav,1,n);
12655: free_ivector(cod,1,n);
12656: free_ivector(tab,1,NCOVMAX);
12657: fclose(ficresstdeij);
12658: fclose(ficrescveij);
12659: fclose(ficresvij);
12660: fclose(ficrest);
12661: fclose(ficpar);
12662:
12663:
1.126 brouard 12664: /*---------- End : free ----------------*/
1.219 brouard 12665: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 12666: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
12667: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12668: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12669: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12670: } /* mle==-3 arrives here for freeing */
1.227 brouard 12671: /* endfree:*/
12672: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12673: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12674: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.268 brouard 12675: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,1,n);
12676: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,1,n);
12677: if(nqv>=1)free_matrix(coqvar,1,nqv,1,n);
1.227 brouard 12678: free_matrix(covar,0,NCOVMAX,1,n);
12679: free_matrix(matcov,1,npar,1,npar);
12680: free_matrix(hess,1,npar,1,npar);
12681: /*free_vector(delti,1,npar);*/
12682: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12683: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 12684: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 12685: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12686:
12687: free_ivector(ncodemax,1,NCOVMAX);
12688: free_ivector(ncodemaxwundef,1,NCOVMAX);
12689: free_ivector(Dummy,-1,NCOVMAX);
12690: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 12691: free_ivector(DummyV,1,NCOVMAX);
12692: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 12693: free_ivector(Typevar,-1,NCOVMAX);
12694: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 12695: free_ivector(TvarsQ,1,NCOVMAX);
12696: free_ivector(TvarsQind,1,NCOVMAX);
12697: free_ivector(TvarsD,1,NCOVMAX);
12698: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 12699: free_ivector(TvarFD,1,NCOVMAX);
12700: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 12701: free_ivector(TvarF,1,NCOVMAX);
12702: free_ivector(TvarFind,1,NCOVMAX);
12703: free_ivector(TvarV,1,NCOVMAX);
12704: free_ivector(TvarVind,1,NCOVMAX);
12705: free_ivector(TvarA,1,NCOVMAX);
12706: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 12707: free_ivector(TvarFQ,1,NCOVMAX);
12708: free_ivector(TvarFQind,1,NCOVMAX);
12709: free_ivector(TvarVD,1,NCOVMAX);
12710: free_ivector(TvarVDind,1,NCOVMAX);
12711: free_ivector(TvarVQ,1,NCOVMAX);
12712: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 12713: free_ivector(Tvarsel,1,NCOVMAX);
12714: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 12715: free_ivector(Tposprod,1,NCOVMAX);
12716: free_ivector(Tprod,1,NCOVMAX);
12717: free_ivector(Tvaraff,1,NCOVMAX);
12718: free_ivector(invalidvarcomb,1,ncovcombmax);
12719: free_ivector(Tage,1,NCOVMAX);
12720: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 12721: free_ivector(TmodelInvind,1,NCOVMAX);
12722: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 12723:
12724: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
12725: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 12726: fflush(fichtm);
12727: fflush(ficgp);
12728:
1.227 brouard 12729:
1.126 brouard 12730: if((nberr >0) || (nbwarn>0)){
1.216 brouard 12731: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
12732: 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 12733: }else{
12734: printf("End of Imach\n");
12735: fprintf(ficlog,"End of Imach\n");
12736: }
12737: printf("See log file on %s\n",filelog);
12738: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 12739: /*(void) gettimeofday(&end_time,&tzp);*/
12740: rend_time = time(NULL);
12741: end_time = *localtime(&rend_time);
12742: /* tml = *localtime(&end_time.tm_sec); */
12743: strcpy(strtend,asctime(&end_time));
1.126 brouard 12744: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
12745: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 12746: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 12747:
1.157 brouard 12748: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
12749: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
12750: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 12751: /* printf("Total time was %d uSec.\n", total_usecs);*/
12752: /* if(fileappend(fichtm,optionfilehtm)){ */
12753: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12754: fclose(fichtm);
12755: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12756: fclose(fichtmcov);
12757: fclose(ficgp);
12758: fclose(ficlog);
12759: /*------ End -----------*/
1.227 brouard 12760:
1.281 brouard 12761:
12762: /* Executes gnuplot */
1.227 brouard 12763:
12764: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 12765: #ifdef WIN32
1.227 brouard 12766: if (_chdir(pathcd) != 0)
12767: printf("Can't move to directory %s!\n",path);
12768: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 12769: #else
1.227 brouard 12770: if(chdir(pathcd) != 0)
12771: printf("Can't move to directory %s!\n", path);
12772: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 12773: #endif
1.126 brouard 12774: printf("Current directory %s!\n",pathcd);
12775: /*strcat(plotcmd,CHARSEPARATOR);*/
12776: sprintf(plotcmd,"gnuplot");
1.157 brouard 12777: #ifdef _WIN32
1.126 brouard 12778: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
12779: #endif
12780: if(!stat(plotcmd,&info)){
1.158 brouard 12781: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12782: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 12783: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 12784: }else
12785: strcpy(pplotcmd,plotcmd);
1.157 brouard 12786: #ifdef __unix
1.126 brouard 12787: strcpy(plotcmd,GNUPLOTPROGRAM);
12788: if(!stat(plotcmd,&info)){
1.158 brouard 12789: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12790: }else
12791: strcpy(pplotcmd,plotcmd);
12792: #endif
12793: }else
12794: strcpy(pplotcmd,plotcmd);
12795:
12796: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 12797: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.227 brouard 12798:
1.126 brouard 12799: if((outcmd=system(plotcmd)) != 0){
1.158 brouard 12800: printf("gnuplot command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 12801: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 12802: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.150 brouard 12803: if((outcmd=system(plotcmd)) != 0)
1.153 brouard 12804: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.126 brouard 12805: }
1.158 brouard 12806: printf(" Successful, please wait...");
1.126 brouard 12807: while (z[0] != 'q') {
12808: /* chdir(path); */
1.154 brouard 12809: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 12810: scanf("%s",z);
12811: /* if (z[0] == 'c') system("./imach"); */
12812: if (z[0] == 'e') {
1.158 brouard 12813: #ifdef __APPLE__
1.152 brouard 12814: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 12815: #elif __linux
12816: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 12817: #else
1.152 brouard 12818: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 12819: #endif
12820: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
12821: system(pplotcmd);
1.126 brouard 12822: }
12823: else if (z[0] == 'g') system(plotcmd);
12824: else if (z[0] == 'q') exit(0);
12825: }
1.227 brouard 12826: end:
1.126 brouard 12827: while (z[0] != 'q') {
1.195 brouard 12828: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 12829: scanf("%s",z);
12830: }
1.283 brouard 12831: printf("End\n");
1.282 brouard 12832: exit(0);
1.126 brouard 12833: }
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