Annotation of imach/src/imach.c, revision 1.264
1.264 ! brouard 1: /* $Id: imach.c,v 1.263 2017/04/24 15:23:15 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.264 ! brouard 4: Revision 1.263 2017/04/24 15:23:15 brouard
! 5: Summary: to save
! 6:
1.263 brouard 7: Revision 1.262 2017/04/18 16:48:12 brouard
8: *** empty log message ***
9:
1.262 brouard 10: Revision 1.261 2017/04/05 10:14:09 brouard
11: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
12:
1.261 brouard 13: Revision 1.260 2017/04/04 17:46:59 brouard
14: Summary: Gnuplot indexations fixed (humm)
15:
1.260 brouard 16: Revision 1.259 2017/04/04 13:01:16 brouard
17: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
18:
1.259 brouard 19: Revision 1.258 2017/04/03 10:17:47 brouard
20: Summary: Version 0.99r12
21:
22: Some cleanings, conformed with updated documentation.
23:
1.258 brouard 24: Revision 1.257 2017/03/29 16:53:30 brouard
25: Summary: Temp
26:
1.257 brouard 27: Revision 1.256 2017/03/27 05:50:23 brouard
28: Summary: Temporary
29:
1.256 brouard 30: Revision 1.255 2017/03/08 16:02:28 brouard
31: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
32:
1.255 brouard 33: Revision 1.254 2017/03/08 07:13:00 brouard
34: Summary: Fixing data parameter line
35:
1.254 brouard 36: Revision 1.253 2016/12/15 11:59:41 brouard
37: Summary: 0.99 in progress
38:
1.253 brouard 39: Revision 1.252 2016/09/15 21:15:37 brouard
40: *** empty log message ***
41:
1.252 brouard 42: Revision 1.251 2016/09/15 15:01:13 brouard
43: Summary: not working
44:
1.251 brouard 45: Revision 1.250 2016/09/08 16:07:27 brouard
46: Summary: continue
47:
1.250 brouard 48: Revision 1.249 2016/09/07 17:14:18 brouard
49: Summary: Starting values from frequencies
50:
1.249 brouard 51: Revision 1.248 2016/09/07 14:10:18 brouard
52: *** empty log message ***
53:
1.248 brouard 54: Revision 1.247 2016/09/02 11:11:21 brouard
55: *** empty log message ***
56:
1.247 brouard 57: Revision 1.246 2016/09/02 08:49:22 brouard
58: *** empty log message ***
59:
1.246 brouard 60: Revision 1.245 2016/09/02 07:25:01 brouard
61: *** empty log message ***
62:
1.245 brouard 63: Revision 1.244 2016/09/02 07:17:34 brouard
64: *** empty log message ***
65:
1.244 brouard 66: Revision 1.243 2016/09/02 06:45:35 brouard
67: *** empty log message ***
68:
1.243 brouard 69: Revision 1.242 2016/08/30 15:01:20 brouard
70: Summary: Fixing a lots
71:
1.242 brouard 72: Revision 1.241 2016/08/29 17:17:25 brouard
73: Summary: gnuplot problem in Back projection to fix
74:
1.241 brouard 75: Revision 1.240 2016/08/29 07:53:18 brouard
76: Summary: Better
77:
1.240 brouard 78: Revision 1.239 2016/08/26 15:51:03 brouard
79: Summary: Improvement in Powell output in order to copy and paste
80:
81: Author:
82:
1.239 brouard 83: Revision 1.238 2016/08/26 14:23:35 brouard
84: Summary: Starting tests of 0.99
85:
1.238 brouard 86: Revision 1.237 2016/08/26 09:20:19 brouard
87: Summary: to valgrind
88:
1.237 brouard 89: Revision 1.236 2016/08/25 10:50:18 brouard
90: *** empty log message ***
91:
1.236 brouard 92: Revision 1.235 2016/08/25 06:59:23 brouard
93: *** empty log message ***
94:
1.235 brouard 95: Revision 1.234 2016/08/23 16:51:20 brouard
96: *** empty log message ***
97:
1.234 brouard 98: Revision 1.233 2016/08/23 07:40:50 brouard
99: Summary: not working
100:
1.233 brouard 101: Revision 1.232 2016/08/22 14:20:21 brouard
102: Summary: not working
103:
1.232 brouard 104: Revision 1.231 2016/08/22 07:17:15 brouard
105: Summary: not working
106:
1.231 brouard 107: Revision 1.230 2016/08/22 06:55:53 brouard
108: Summary: Not working
109:
1.230 brouard 110: Revision 1.229 2016/07/23 09:45:53 brouard
111: Summary: Completing for func too
112:
1.229 brouard 113: Revision 1.228 2016/07/22 17:45:30 brouard
114: Summary: Fixing some arrays, still debugging
115:
1.227 brouard 116: Revision 1.226 2016/07/12 18:42:34 brouard
117: Summary: temp
118:
1.226 brouard 119: Revision 1.225 2016/07/12 08:40:03 brouard
120: Summary: saving but not running
121:
1.225 brouard 122: Revision 1.224 2016/07/01 13:16:01 brouard
123: Summary: Fixes
124:
1.224 brouard 125: Revision 1.223 2016/02/19 09:23:35 brouard
126: Summary: temporary
127:
1.223 brouard 128: Revision 1.222 2016/02/17 08:14:50 brouard
129: Summary: Probably last 0.98 stable version 0.98r6
130:
1.222 brouard 131: Revision 1.221 2016/02/15 23:35:36 brouard
132: Summary: minor bug
133:
1.220 brouard 134: Revision 1.219 2016/02/15 00:48:12 brouard
135: *** empty log message ***
136:
1.219 brouard 137: Revision 1.218 2016/02/12 11:29:23 brouard
138: Summary: 0.99 Back projections
139:
1.218 brouard 140: Revision 1.217 2015/12/23 17:18:31 brouard
141: Summary: Experimental backcast
142:
1.217 brouard 143: Revision 1.216 2015/12/18 17:32:11 brouard
144: Summary: 0.98r4 Warning and status=-2
145:
146: Version 0.98r4 is now:
147: - displaying an error when status is -1, date of interview unknown and date of death known;
148: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
149: Older changes concerning s=-2, dating from 2005 have been supersed.
150:
1.216 brouard 151: Revision 1.215 2015/12/16 08:52:24 brouard
152: Summary: 0.98r4 working
153:
1.215 brouard 154: Revision 1.214 2015/12/16 06:57:54 brouard
155: Summary: temporary not working
156:
1.214 brouard 157: Revision 1.213 2015/12/11 18:22:17 brouard
158: Summary: 0.98r4
159:
1.213 brouard 160: Revision 1.212 2015/11/21 12:47:24 brouard
161: Summary: minor typo
162:
1.212 brouard 163: Revision 1.211 2015/11/21 12:41:11 brouard
164: Summary: 0.98r3 with some graph of projected cross-sectional
165:
166: Author: Nicolas Brouard
167:
1.211 brouard 168: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 169: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 170: Summary: Adding ftolpl parameter
171: Author: N Brouard
172:
173: We had difficulties to get smoothed confidence intervals. It was due
174: to the period prevalence which wasn't computed accurately. The inner
175: parameter ftolpl is now an outer parameter of the .imach parameter
176: file after estepm. If ftolpl is small 1.e-4 and estepm too,
177: computation are long.
178:
1.209 brouard 179: Revision 1.208 2015/11/17 14:31:57 brouard
180: Summary: temporary
181:
1.208 brouard 182: Revision 1.207 2015/10/27 17:36:57 brouard
183: *** empty log message ***
184:
1.207 brouard 185: Revision 1.206 2015/10/24 07:14:11 brouard
186: *** empty log message ***
187:
1.206 brouard 188: Revision 1.205 2015/10/23 15:50:53 brouard
189: Summary: 0.98r3 some clarification for graphs on likelihood contributions
190:
1.205 brouard 191: Revision 1.204 2015/10/01 16:20:26 brouard
192: Summary: Some new graphs of contribution to likelihood
193:
1.204 brouard 194: Revision 1.203 2015/09/30 17:45:14 brouard
195: Summary: looking at better estimation of the hessian
196:
197: Also a better criteria for convergence to the period prevalence And
198: therefore adding the number of years needed to converge. (The
199: prevalence in any alive state shold sum to one
200:
1.203 brouard 201: Revision 1.202 2015/09/22 19:45:16 brouard
202: Summary: Adding some overall graph on contribution to likelihood. Might change
203:
1.202 brouard 204: Revision 1.201 2015/09/15 17:34:58 brouard
205: Summary: 0.98r0
206:
207: - Some new graphs like suvival functions
208: - Some bugs fixed like model=1+age+V2.
209:
1.201 brouard 210: Revision 1.200 2015/09/09 16:53:55 brouard
211: Summary: Big bug thanks to Flavia
212:
213: Even model=1+age+V2. did not work anymore
214:
1.200 brouard 215: Revision 1.199 2015/09/07 14:09:23 brouard
216: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
217:
1.199 brouard 218: Revision 1.198 2015/09/03 07:14:39 brouard
219: Summary: 0.98q5 Flavia
220:
1.198 brouard 221: Revision 1.197 2015/09/01 18:24:39 brouard
222: *** empty log message ***
223:
1.197 brouard 224: Revision 1.196 2015/08/18 23:17:52 brouard
225: Summary: 0.98q5
226:
1.196 brouard 227: Revision 1.195 2015/08/18 16:28:39 brouard
228: Summary: Adding a hack for testing purpose
229:
230: After reading the title, ftol and model lines, if the comment line has
231: a q, starting with #q, the answer at the end of the run is quit. It
232: permits to run test files in batch with ctest. The former workaround was
233: $ echo q | imach foo.imach
234:
1.195 brouard 235: Revision 1.194 2015/08/18 13:32:00 brouard
236: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
237:
1.194 brouard 238: Revision 1.193 2015/08/04 07:17:42 brouard
239: Summary: 0.98q4
240:
1.193 brouard 241: Revision 1.192 2015/07/16 16:49:02 brouard
242: Summary: Fixing some outputs
243:
1.192 brouard 244: Revision 1.191 2015/07/14 10:00:33 brouard
245: Summary: Some fixes
246:
1.191 brouard 247: Revision 1.190 2015/05/05 08:51:13 brouard
248: Summary: Adding digits in output parameters (7 digits instead of 6)
249:
250: Fix 1+age+.
251:
1.190 brouard 252: Revision 1.189 2015/04/30 14:45:16 brouard
253: Summary: 0.98q2
254:
1.189 brouard 255: Revision 1.188 2015/04/30 08:27:53 brouard
256: *** empty log message ***
257:
1.188 brouard 258: Revision 1.187 2015/04/29 09:11:15 brouard
259: *** empty log message ***
260:
1.187 brouard 261: Revision 1.186 2015/04/23 12:01:52 brouard
262: Summary: V1*age is working now, version 0.98q1
263:
264: Some codes had been disabled in order to simplify and Vn*age was
265: working in the optimization phase, ie, giving correct MLE parameters,
266: but, as usual, outputs were not correct and program core dumped.
267:
1.186 brouard 268: Revision 1.185 2015/03/11 13:26:42 brouard
269: Summary: Inclusion of compile and links command line for Intel Compiler
270:
1.185 brouard 271: Revision 1.184 2015/03/11 11:52:39 brouard
272: Summary: Back from Windows 8. Intel Compiler
273:
1.184 brouard 274: Revision 1.183 2015/03/10 20:34:32 brouard
275: Summary: 0.98q0, trying with directest, mnbrak fixed
276:
277: We use directest instead of original Powell test; probably no
278: incidence on the results, but better justifications;
279: We fixed Numerical Recipes mnbrak routine which was wrong and gave
280: wrong results.
281:
1.183 brouard 282: Revision 1.182 2015/02/12 08:19:57 brouard
283: Summary: Trying to keep directest which seems simpler and more general
284: Author: Nicolas Brouard
285:
1.182 brouard 286: Revision 1.181 2015/02/11 23:22:24 brouard
287: Summary: Comments on Powell added
288:
289: Author:
290:
1.181 brouard 291: Revision 1.180 2015/02/11 17:33:45 brouard
292: Summary: Finishing move from main to function (hpijx and prevalence_limit)
293:
1.180 brouard 294: Revision 1.179 2015/01/04 09:57:06 brouard
295: Summary: back to OS/X
296:
1.179 brouard 297: Revision 1.178 2015/01/04 09:35:48 brouard
298: *** empty log message ***
299:
1.178 brouard 300: Revision 1.177 2015/01/03 18:40:56 brouard
301: Summary: Still testing ilc32 on OSX
302:
1.177 brouard 303: Revision 1.176 2015/01/03 16:45:04 brouard
304: *** empty log message ***
305:
1.176 brouard 306: Revision 1.175 2015/01/03 16:33:42 brouard
307: *** empty log message ***
308:
1.175 brouard 309: Revision 1.174 2015/01/03 16:15:49 brouard
310: Summary: Still in cross-compilation
311:
1.174 brouard 312: Revision 1.173 2015/01/03 12:06:26 brouard
313: Summary: trying to detect cross-compilation
314:
1.173 brouard 315: Revision 1.172 2014/12/27 12:07:47 brouard
316: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
317:
1.172 brouard 318: Revision 1.171 2014/12/23 13:26:59 brouard
319: Summary: Back from Visual C
320:
321: Still problem with utsname.h on Windows
322:
1.171 brouard 323: Revision 1.170 2014/12/23 11:17:12 brouard
324: Summary: Cleaning some \%% back to %%
325:
326: The escape was mandatory for a specific compiler (which one?), but too many warnings.
327:
1.170 brouard 328: Revision 1.169 2014/12/22 23:08:31 brouard
329: Summary: 0.98p
330:
331: Outputs some informations on compiler used, OS etc. Testing on different platforms.
332:
1.169 brouard 333: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 334: Summary: update
1.169 brouard 335:
1.168 brouard 336: Revision 1.167 2014/12/22 13:50:56 brouard
337: Summary: Testing uname and compiler version and if compiled 32 or 64
338:
339: Testing on Linux 64
340:
1.167 brouard 341: Revision 1.166 2014/12/22 11:40:47 brouard
342: *** empty log message ***
343:
1.166 brouard 344: Revision 1.165 2014/12/16 11:20:36 brouard
345: Summary: After compiling on Visual C
346:
347: * imach.c (Module): Merging 1.61 to 1.162
348:
1.165 brouard 349: Revision 1.164 2014/12/16 10:52:11 brouard
350: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
351:
352: * imach.c (Module): Merging 1.61 to 1.162
353:
1.164 brouard 354: Revision 1.163 2014/12/16 10:30:11 brouard
355: * imach.c (Module): Merging 1.61 to 1.162
356:
1.163 brouard 357: Revision 1.162 2014/09/25 11:43:39 brouard
358: Summary: temporary backup 0.99!
359:
1.162 brouard 360: Revision 1.1 2014/09/16 11:06:58 brouard
361: Summary: With some code (wrong) for nlopt
362:
363: Author:
364:
365: Revision 1.161 2014/09/15 20:41:41 brouard
366: Summary: Problem with macro SQR on Intel compiler
367:
1.161 brouard 368: Revision 1.160 2014/09/02 09:24:05 brouard
369: *** empty log message ***
370:
1.160 brouard 371: Revision 1.159 2014/09/01 10:34:10 brouard
372: Summary: WIN32
373: Author: Brouard
374:
1.159 brouard 375: Revision 1.158 2014/08/27 17:11:51 brouard
376: *** empty log message ***
377:
1.158 brouard 378: Revision 1.157 2014/08/27 16:26:55 brouard
379: Summary: Preparing windows Visual studio version
380: Author: Brouard
381:
382: In order to compile on Visual studio, time.h is now correct and time_t
383: and tm struct should be used. difftime should be used but sometimes I
384: just make the differences in raw time format (time(&now).
385: Trying to suppress #ifdef LINUX
386: Add xdg-open for __linux in order to open default browser.
387:
1.157 brouard 388: Revision 1.156 2014/08/25 20:10:10 brouard
389: *** empty log message ***
390:
1.156 brouard 391: Revision 1.155 2014/08/25 18:32:34 brouard
392: Summary: New compile, minor changes
393: Author: Brouard
394:
1.155 brouard 395: Revision 1.154 2014/06/20 17:32:08 brouard
396: Summary: Outputs now all graphs of convergence to period prevalence
397:
1.154 brouard 398: Revision 1.153 2014/06/20 16:45:46 brouard
399: Summary: If 3 live state, convergence to period prevalence on same graph
400: Author: Brouard
401:
1.153 brouard 402: Revision 1.152 2014/06/18 17:54:09 brouard
403: Summary: open browser, use gnuplot on same dir than imach if not found in the path
404:
1.152 brouard 405: Revision 1.151 2014/06/18 16:43:30 brouard
406: *** empty log message ***
407:
1.151 brouard 408: Revision 1.150 2014/06/18 16:42:35 brouard
409: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
410: Author: brouard
411:
1.150 brouard 412: Revision 1.149 2014/06/18 15:51:14 brouard
413: Summary: Some fixes in parameter files errors
414: Author: Nicolas Brouard
415:
1.149 brouard 416: Revision 1.148 2014/06/17 17:38:48 brouard
417: Summary: Nothing new
418: Author: Brouard
419:
420: Just a new packaging for OS/X version 0.98nS
421:
1.148 brouard 422: Revision 1.147 2014/06/16 10:33:11 brouard
423: *** empty log message ***
424:
1.147 brouard 425: Revision 1.146 2014/06/16 10:20:28 brouard
426: Summary: Merge
427: Author: Brouard
428:
429: Merge, before building revised version.
430:
1.146 brouard 431: Revision 1.145 2014/06/10 21:23:15 brouard
432: Summary: Debugging with valgrind
433: Author: Nicolas Brouard
434:
435: Lot of changes in order to output the results with some covariates
436: After the Edimburgh REVES conference 2014, it seems mandatory to
437: improve the code.
438: No more memory valgrind error but a lot has to be done in order to
439: continue the work of splitting the code into subroutines.
440: Also, decodemodel has been improved. Tricode is still not
441: optimal. nbcode should be improved. Documentation has been added in
442: the source code.
443:
1.144 brouard 444: Revision 1.143 2014/01/26 09:45:38 brouard
445: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
446:
447: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
448: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
449:
1.143 brouard 450: Revision 1.142 2014/01/26 03:57:36 brouard
451: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
452:
453: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
454:
1.142 brouard 455: Revision 1.141 2014/01/26 02:42:01 brouard
456: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
457:
1.141 brouard 458: Revision 1.140 2011/09/02 10:37:54 brouard
459: Summary: times.h is ok with mingw32 now.
460:
1.140 brouard 461: Revision 1.139 2010/06/14 07:50:17 brouard
462: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
463: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
464:
1.139 brouard 465: Revision 1.138 2010/04/30 18:19:40 brouard
466: *** empty log message ***
467:
1.138 brouard 468: Revision 1.137 2010/04/29 18:11:38 brouard
469: (Module): Checking covariates for more complex models
470: than V1+V2. A lot of change to be done. Unstable.
471:
1.137 brouard 472: Revision 1.136 2010/04/26 20:30:53 brouard
473: (Module): merging some libgsl code. Fixing computation
474: of likelione (using inter/intrapolation if mle = 0) in order to
475: get same likelihood as if mle=1.
476: Some cleaning of code and comments added.
477:
1.136 brouard 478: Revision 1.135 2009/10/29 15:33:14 brouard
479: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
480:
1.135 brouard 481: Revision 1.134 2009/10/29 13:18:53 brouard
482: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
483:
1.134 brouard 484: Revision 1.133 2009/07/06 10:21:25 brouard
485: just nforces
486:
1.133 brouard 487: Revision 1.132 2009/07/06 08:22:05 brouard
488: Many tings
489:
1.132 brouard 490: Revision 1.131 2009/06/20 16:22:47 brouard
491: Some dimensions resccaled
492:
1.131 brouard 493: Revision 1.130 2009/05/26 06:44:34 brouard
494: (Module): Max Covariate is now set to 20 instead of 8. A
495: lot of cleaning with variables initialized to 0. Trying to make
496: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
497:
1.130 brouard 498: Revision 1.129 2007/08/31 13:49:27 lievre
499: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
500:
1.129 lievre 501: Revision 1.128 2006/06/30 13:02:05 brouard
502: (Module): Clarifications on computing e.j
503:
1.128 brouard 504: Revision 1.127 2006/04/28 18:11:50 brouard
505: (Module): Yes the sum of survivors was wrong since
506: imach-114 because nhstepm was no more computed in the age
507: loop. Now we define nhstepma in the age loop.
508: (Module): In order to speed up (in case of numerous covariates) we
509: compute health expectancies (without variances) in a first step
510: and then all the health expectancies with variances or standard
511: deviation (needs data from the Hessian matrices) which slows the
512: computation.
513: In the future we should be able to stop the program is only health
514: expectancies and graph are needed without standard deviations.
515:
1.127 brouard 516: Revision 1.126 2006/04/28 17:23:28 brouard
517: (Module): Yes the sum of survivors was wrong since
518: imach-114 because nhstepm was no more computed in the age
519: loop. Now we define nhstepma in the age loop.
520: Version 0.98h
521:
1.126 brouard 522: Revision 1.125 2006/04/04 15:20:31 lievre
523: Errors in calculation of health expectancies. Age was not initialized.
524: Forecasting file added.
525:
526: Revision 1.124 2006/03/22 17:13:53 lievre
527: Parameters are printed with %lf instead of %f (more numbers after the comma).
528: The log-likelihood is printed in the log file
529:
530: Revision 1.123 2006/03/20 10:52:43 brouard
531: * imach.c (Module): <title> changed, corresponds to .htm file
532: name. <head> headers where missing.
533:
534: * imach.c (Module): Weights can have a decimal point as for
535: English (a comma might work with a correct LC_NUMERIC environment,
536: otherwise the weight is truncated).
537: Modification of warning when the covariates values are not 0 or
538: 1.
539: Version 0.98g
540:
541: Revision 1.122 2006/03/20 09:45:41 brouard
542: (Module): Weights can have a decimal point as for
543: English (a comma might work with a correct LC_NUMERIC environment,
544: otherwise the weight is truncated).
545: Modification of warning when the covariates values are not 0 or
546: 1.
547: Version 0.98g
548:
549: Revision 1.121 2006/03/16 17:45:01 lievre
550: * imach.c (Module): Comments concerning covariates added
551:
552: * imach.c (Module): refinements in the computation of lli if
553: status=-2 in order to have more reliable computation if stepm is
554: not 1 month. Version 0.98f
555:
556: Revision 1.120 2006/03/16 15:10:38 lievre
557: (Module): refinements in the computation of lli if
558: status=-2 in order to have more reliable computation if stepm is
559: not 1 month. Version 0.98f
560:
561: Revision 1.119 2006/03/15 17:42:26 brouard
562: (Module): Bug if status = -2, the loglikelihood was
563: computed as likelihood omitting the logarithm. Version O.98e
564:
565: Revision 1.118 2006/03/14 18:20:07 brouard
566: (Module): varevsij Comments added explaining the second
567: table of variances if popbased=1 .
568: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
569: (Module): Function pstamp added
570: (Module): Version 0.98d
571:
572: Revision 1.117 2006/03/14 17:16:22 brouard
573: (Module): varevsij Comments added explaining the second
574: table of variances if popbased=1 .
575: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
576: (Module): Function pstamp added
577: (Module): Version 0.98d
578:
579: Revision 1.116 2006/03/06 10:29:27 brouard
580: (Module): Variance-covariance wrong links and
581: varian-covariance of ej. is needed (Saito).
582:
583: Revision 1.115 2006/02/27 12:17:45 brouard
584: (Module): One freematrix added in mlikeli! 0.98c
585:
586: Revision 1.114 2006/02/26 12:57:58 brouard
587: (Module): Some improvements in processing parameter
588: filename with strsep.
589:
590: Revision 1.113 2006/02/24 14:20:24 brouard
591: (Module): Memory leaks checks with valgrind and:
592: datafile was not closed, some imatrix were not freed and on matrix
593: allocation too.
594:
595: Revision 1.112 2006/01/30 09:55:26 brouard
596: (Module): Back to gnuplot.exe instead of wgnuplot.exe
597:
598: Revision 1.111 2006/01/25 20:38:18 brouard
599: (Module): Lots of cleaning and bugs added (Gompertz)
600: (Module): Comments can be added in data file. Missing date values
601: can be a simple dot '.'.
602:
603: Revision 1.110 2006/01/25 00:51:50 brouard
604: (Module): Lots of cleaning and bugs added (Gompertz)
605:
606: Revision 1.109 2006/01/24 19:37:15 brouard
607: (Module): Comments (lines starting with a #) are allowed in data.
608:
609: Revision 1.108 2006/01/19 18:05:42 lievre
610: Gnuplot problem appeared...
611: To be fixed
612:
613: Revision 1.107 2006/01/19 16:20:37 brouard
614: Test existence of gnuplot in imach path
615:
616: Revision 1.106 2006/01/19 13:24:36 brouard
617: Some cleaning and links added in html output
618:
619: Revision 1.105 2006/01/05 20:23:19 lievre
620: *** empty log message ***
621:
622: Revision 1.104 2005/09/30 16:11:43 lievre
623: (Module): sump fixed, loop imx fixed, and simplifications.
624: (Module): If the status is missing at the last wave but we know
625: that the person is alive, then we can code his/her status as -2
626: (instead of missing=-1 in earlier versions) and his/her
627: contributions to the likelihood is 1 - Prob of dying from last
628: health status (= 1-p13= p11+p12 in the easiest case of somebody in
629: the healthy state at last known wave). Version is 0.98
630:
631: Revision 1.103 2005/09/30 15:54:49 lievre
632: (Module): sump fixed, loop imx fixed, and simplifications.
633:
634: Revision 1.102 2004/09/15 17:31:30 brouard
635: Add the possibility to read data file including tab characters.
636:
637: Revision 1.101 2004/09/15 10:38:38 brouard
638: Fix on curr_time
639:
640: Revision 1.100 2004/07/12 18:29:06 brouard
641: Add version for Mac OS X. Just define UNIX in Makefile
642:
643: Revision 1.99 2004/06/05 08:57:40 brouard
644: *** empty log message ***
645:
646: Revision 1.98 2004/05/16 15:05:56 brouard
647: New version 0.97 . First attempt to estimate force of mortality
648: directly from the data i.e. without the need of knowing the health
649: state at each age, but using a Gompertz model: log u =a + b*age .
650: This is the basic analysis of mortality and should be done before any
651: other analysis, in order to test if the mortality estimated from the
652: cross-longitudinal survey is different from the mortality estimated
653: from other sources like vital statistic data.
654:
655: The same imach parameter file can be used but the option for mle should be -3.
656:
1.133 brouard 657: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 658: former routines in order to include the new code within the former code.
659:
660: The output is very simple: only an estimate of the intercept and of
661: the slope with 95% confident intervals.
662:
663: Current limitations:
664: A) Even if you enter covariates, i.e. with the
665: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
666: B) There is no computation of Life Expectancy nor Life Table.
667:
668: Revision 1.97 2004/02/20 13:25:42 lievre
669: Version 0.96d. Population forecasting command line is (temporarily)
670: suppressed.
671:
672: Revision 1.96 2003/07/15 15:38:55 brouard
673: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
674: rewritten within the same printf. Workaround: many printfs.
675:
676: Revision 1.95 2003/07/08 07:54:34 brouard
677: * imach.c (Repository):
678: (Repository): Using imachwizard code to output a more meaningful covariance
679: matrix (cov(a12,c31) instead of numbers.
680:
681: Revision 1.94 2003/06/27 13:00:02 brouard
682: Just cleaning
683:
684: Revision 1.93 2003/06/25 16:33:55 brouard
685: (Module): On windows (cygwin) function asctime_r doesn't
686: exist so I changed back to asctime which exists.
687: (Module): Version 0.96b
688:
689: Revision 1.92 2003/06/25 16:30:45 brouard
690: (Module): On windows (cygwin) function asctime_r doesn't
691: exist so I changed back to asctime which exists.
692:
693: Revision 1.91 2003/06/25 15:30:29 brouard
694: * imach.c (Repository): Duplicated warning errors corrected.
695: (Repository): Elapsed time after each iteration is now output. It
696: helps to forecast when convergence will be reached. Elapsed time
697: is stamped in powell. We created a new html file for the graphs
698: concerning matrix of covariance. It has extension -cov.htm.
699:
700: Revision 1.90 2003/06/24 12:34:15 brouard
701: (Module): Some bugs corrected for windows. Also, when
702: mle=-1 a template is output in file "or"mypar.txt with the design
703: of the covariance matrix to be input.
704:
705: Revision 1.89 2003/06/24 12:30:52 brouard
706: (Module): Some bugs corrected for windows. Also, when
707: mle=-1 a template is output in file "or"mypar.txt with the design
708: of the covariance matrix to be input.
709:
710: Revision 1.88 2003/06/23 17:54:56 brouard
711: * 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.
712:
713: Revision 1.87 2003/06/18 12:26:01 brouard
714: Version 0.96
715:
716: Revision 1.86 2003/06/17 20:04:08 brouard
717: (Module): Change position of html and gnuplot routines and added
718: routine fileappend.
719:
720: Revision 1.85 2003/06/17 13:12:43 brouard
721: * imach.c (Repository): Check when date of death was earlier that
722: current date of interview. It may happen when the death was just
723: prior to the death. In this case, dh was negative and likelihood
724: was wrong (infinity). We still send an "Error" but patch by
725: assuming that the date of death was just one stepm after the
726: interview.
727: (Repository): Because some people have very long ID (first column)
728: we changed int to long in num[] and we added a new lvector for
729: memory allocation. But we also truncated to 8 characters (left
730: truncation)
731: (Repository): No more line truncation errors.
732:
733: Revision 1.84 2003/06/13 21:44:43 brouard
734: * imach.c (Repository): Replace "freqsummary" at a correct
735: place. It differs from routine "prevalence" which may be called
736: many times. Probs is memory consuming and must be used with
737: parcimony.
738: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
739:
740: Revision 1.83 2003/06/10 13:39:11 lievre
741: *** empty log message ***
742:
743: Revision 1.82 2003/06/05 15:57:20 brouard
744: Add log in imach.c and fullversion number is now printed.
745:
746: */
747: /*
748: Interpolated Markov Chain
749:
750: Short summary of the programme:
751:
1.227 brouard 752: This program computes Healthy Life Expectancies or State-specific
753: (if states aren't health statuses) Expectancies from
754: cross-longitudinal data. Cross-longitudinal data consist in:
755:
756: -1- a first survey ("cross") where individuals from different ages
757: are interviewed on their health status or degree of disability (in
758: the case of a health survey which is our main interest)
759:
760: -2- at least a second wave of interviews ("longitudinal") which
761: measure each change (if any) in individual health status. Health
762: expectancies are computed from the time spent in each health state
763: according to a model. More health states you consider, more time is
764: necessary to reach the Maximum Likelihood of the parameters involved
765: in the model. The simplest model is the multinomial logistic model
766: where pij is the probability to be observed in state j at the second
767: wave conditional to be observed in state i at the first
768: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
769: etc , where 'age' is age and 'sex' is a covariate. If you want to
770: have a more complex model than "constant and age", you should modify
771: the program where the markup *Covariates have to be included here
772: again* invites you to do it. More covariates you add, slower the
1.126 brouard 773: convergence.
774:
775: The advantage of this computer programme, compared to a simple
776: multinomial logistic model, is clear when the delay between waves is not
777: identical for each individual. Also, if a individual missed an
778: intermediate interview, the information is lost, but taken into
779: account using an interpolation or extrapolation.
780:
781: hPijx is the probability to be observed in state i at age x+h
782: conditional to the observed state i at age x. The delay 'h' can be
783: split into an exact number (nh*stepm) of unobserved intermediate
784: states. This elementary transition (by month, quarter,
785: semester or year) is modelled as a multinomial logistic. The hPx
786: matrix is simply the matrix product of nh*stepm elementary matrices
787: and the contribution of each individual to the likelihood is simply
788: hPijx.
789:
790: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 791: of the life expectancies. It also computes the period (stable) prevalence.
792:
793: Back prevalence and projections:
1.227 brouard 794:
795: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
796: double agemaxpar, double ftolpl, int *ncvyearp, double
797: dateprev1,double dateprev2, int firstpass, int lastpass, int
798: mobilavproj)
799:
800: Computes the back prevalence limit for any combination of
801: covariate values k at any age between ageminpar and agemaxpar and
802: returns it in **bprlim. In the loops,
803:
804: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
805: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
806:
807: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 808: Computes for any combination of covariates k and any age between bage and fage
809: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
810: oldm=oldms;savm=savms;
1.227 brouard 811:
812: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k);
1.218 brouard 813: Computes the transition matrix starting at age 'age' over
814: 'nhstepm*hstepm*stepm' months (i.e. until
815: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 816: nhstepm*hstepm matrices.
817:
818: Returns p3mat[i][j][h] after calling
819: p3mat[i][j][h]=matprod2(newm,
820: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
821: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
822: oldm);
1.226 brouard 823:
824: Important routines
825:
826: - func (or funcone), computes logit (pij) distinguishing
827: o fixed variables (single or product dummies or quantitative);
828: o varying variables by:
829: (1) wave (single, product dummies, quantitative),
830: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
831: % fixed dummy (treated) or quantitative (not done because time-consuming);
832: % varying dummy (not done) or quantitative (not done);
833: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
834: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
835: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
836: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
837: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 838:
1.226 brouard 839:
840:
1.133 brouard 841: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
842: Institut national d'études démographiques, Paris.
1.126 brouard 843: This software have been partly granted by Euro-REVES, a concerted action
844: from the European Union.
845: It is copyrighted identically to a GNU software product, ie programme and
846: software can be distributed freely for non commercial use. Latest version
847: can be accessed at http://euroreves.ined.fr/imach .
848:
849: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
850: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
851:
852: **********************************************************************/
853: /*
854: main
855: read parameterfile
856: read datafile
857: concatwav
858: freqsummary
859: if (mle >= 1)
860: mlikeli
861: print results files
862: if mle==1
863: computes hessian
864: read end of parameter file: agemin, agemax, bage, fage, estepm
865: begin-prev-date,...
866: open gnuplot file
867: open html file
1.145 brouard 868: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
869: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
870: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
871: freexexit2 possible for memory heap.
872:
873: h Pij x | pij_nom ficrestpij
874: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
875: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
876: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
877:
878: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
879: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
880: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
881: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
882: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
883:
1.126 brouard 884: forecasting if prevfcast==1 prevforecast call prevalence()
885: health expectancies
886: Variance-covariance of DFLE
887: prevalence()
888: movingaverage()
889: varevsij()
890: if popbased==1 varevsij(,popbased)
891: total life expectancies
892: Variance of period (stable) prevalence
893: end
894: */
895:
1.187 brouard 896: /* #define DEBUG */
897: /* #define DEBUGBRENT */
1.203 brouard 898: /* #define DEBUGLINMIN */
899: /* #define DEBUGHESS */
900: #define DEBUGHESSIJ
1.224 brouard 901: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 902: #define POWELL /* Instead of NLOPT */
1.224 brouard 903: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 904: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
905: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 906:
907: #include <math.h>
908: #include <stdio.h>
909: #include <stdlib.h>
910: #include <string.h>
1.226 brouard 911: #include <ctype.h>
1.159 brouard 912:
913: #ifdef _WIN32
914: #include <io.h>
1.172 brouard 915: #include <windows.h>
916: #include <tchar.h>
1.159 brouard 917: #else
1.126 brouard 918: #include <unistd.h>
1.159 brouard 919: #endif
1.126 brouard 920:
921: #include <limits.h>
922: #include <sys/types.h>
1.171 brouard 923:
924: #if defined(__GNUC__)
925: #include <sys/utsname.h> /* Doesn't work on Windows */
926: #endif
927:
1.126 brouard 928: #include <sys/stat.h>
929: #include <errno.h>
1.159 brouard 930: /* extern int errno; */
1.126 brouard 931:
1.157 brouard 932: /* #ifdef LINUX */
933: /* #include <time.h> */
934: /* #include "timeval.h" */
935: /* #else */
936: /* #include <sys/time.h> */
937: /* #endif */
938:
1.126 brouard 939: #include <time.h>
940:
1.136 brouard 941: #ifdef GSL
942: #include <gsl/gsl_errno.h>
943: #include <gsl/gsl_multimin.h>
944: #endif
945:
1.167 brouard 946:
1.162 brouard 947: #ifdef NLOPT
948: #include <nlopt.h>
949: typedef struct {
950: double (* function)(double [] );
951: } myfunc_data ;
952: #endif
953:
1.126 brouard 954: /* #include <libintl.h> */
955: /* #define _(String) gettext (String) */
956:
1.251 brouard 957: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 958:
959: #define GNUPLOTPROGRAM "gnuplot"
960: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
961: #define FILENAMELENGTH 132
962:
963: #define GLOCK_ERROR_NOPATH -1 /* empty path */
964: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
965:
1.144 brouard 966: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
967: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 968:
969: #define NINTERVMAX 8
1.144 brouard 970: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
971: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
972: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 973: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 974: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
975: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.126 brouard 976: #define MAXN 20000
1.144 brouard 977: #define YEARM 12. /**< Number of months per year */
1.218 brouard 978: /* #define AGESUP 130 */
979: #define AGESUP 150
980: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 981: #define AGEBASE 40
1.194 brouard 982: #define AGEOVERFLOW 1.e20
1.164 brouard 983: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 984: #ifdef _WIN32
985: #define DIRSEPARATOR '\\'
986: #define CHARSEPARATOR "\\"
987: #define ODIRSEPARATOR '/'
988: #else
1.126 brouard 989: #define DIRSEPARATOR '/'
990: #define CHARSEPARATOR "/"
991: #define ODIRSEPARATOR '\\'
992: #endif
993:
1.264 ! brouard 994: /* $Id: imach.c,v 1.263 2017/04/24 15:23:15 brouard Exp $ */
1.126 brouard 995: /* $State: Exp $ */
1.196 brouard 996: #include "version.h"
997: char version[]=__IMACH_VERSION__;
1.224 brouard 998: char copyright[]="February 2016,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2018";
1.264 ! brouard 999: char fullversion[]="$Revision: 1.263 $ $Date: 2017/04/24 15:23:15 $";
1.126 brouard 1000: char strstart[80];
1001: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1002: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1003: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1004: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1005: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1006: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1007: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1008: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1009: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1010: int cptcovprodnoage=0; /**< Number of covariate products without age */
1011: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1012: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1013: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1014: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1015: int nsd=0; /**< Total number of single dummy variables (output) */
1016: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1017: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1018: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1019: int ntveff=0; /**< ntveff number of effective time varying variables */
1020: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1021: int cptcov=0; /* Working variable */
1.218 brouard 1022: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 1023: int npar=NPARMAX;
1024: int nlstate=2; /* Number of live states */
1025: int ndeath=1; /* Number of dead states */
1.130 brouard 1026: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1027: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1028: int popbased=0;
1029:
1030: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1031: int maxwav=0; /* Maxim number of waves */
1032: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1033: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1034: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1035: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1036: int mle=1, weightopt=0;
1.126 brouard 1037: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1038: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1039: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1040: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1041: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1042: int selected(int kvar); /* Is covariate kvar selected for printing results */
1043:
1.130 brouard 1044: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1045: double **matprod2(); /* test */
1.126 brouard 1046: double **oldm, **newm, **savm; /* Working pointers to matrices */
1047: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1048: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1049:
1.136 brouard 1050: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1051: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1052: FILE *ficlog, *ficrespow;
1.130 brouard 1053: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1054: double fretone; /* Only one call to likelihood */
1.130 brouard 1055: long ipmx=0; /* Number of contributions */
1.126 brouard 1056: double sw; /* Sum of weights */
1057: char filerespow[FILENAMELENGTH];
1058: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1059: FILE *ficresilk;
1060: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1061: FILE *ficresprobmorprev;
1062: FILE *fichtm, *fichtmcov; /* Html File */
1063: FILE *ficreseij;
1064: char filerese[FILENAMELENGTH];
1065: FILE *ficresstdeij;
1066: char fileresstde[FILENAMELENGTH];
1067: FILE *ficrescveij;
1068: char filerescve[FILENAMELENGTH];
1069: FILE *ficresvij;
1070: char fileresv[FILENAMELENGTH];
1071: FILE *ficresvpl;
1072: char fileresvpl[FILENAMELENGTH];
1073: char title[MAXLINE];
1.234 brouard 1074: char model[MAXLINE]; /**< The model line */
1.217 brouard 1075: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1076: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1077: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1078: char command[FILENAMELENGTH];
1079: int outcmd=0;
1080:
1.217 brouard 1081: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1082: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1083: char filelog[FILENAMELENGTH]; /* Log file */
1084: char filerest[FILENAMELENGTH];
1085: char fileregp[FILENAMELENGTH];
1086: char popfile[FILENAMELENGTH];
1087:
1088: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1089:
1.157 brouard 1090: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1091: /* struct timezone tzp; */
1092: /* extern int gettimeofday(); */
1093: struct tm tml, *gmtime(), *localtime();
1094:
1095: extern time_t time();
1096:
1097: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1098: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1099: struct tm tm;
1100:
1.126 brouard 1101: char strcurr[80], strfor[80];
1102:
1103: char *endptr;
1104: long lval;
1105: double dval;
1106:
1107: #define NR_END 1
1108: #define FREE_ARG char*
1109: #define FTOL 1.0e-10
1110:
1111: #define NRANSI
1.240 brouard 1112: #define ITMAX 200
1113: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1114:
1115: #define TOL 2.0e-4
1116:
1117: #define CGOLD 0.3819660
1118: #define ZEPS 1.0e-10
1119: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1120:
1121: #define GOLD 1.618034
1122: #define GLIMIT 100.0
1123: #define TINY 1.0e-20
1124:
1125: static double maxarg1,maxarg2;
1126: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1127: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1128:
1129: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1130: #define rint(a) floor(a+0.5)
1.166 brouard 1131: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1132: #define mytinydouble 1.0e-16
1.166 brouard 1133: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1134: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1135: /* static double dsqrarg; */
1136: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1137: static double sqrarg;
1138: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1139: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1140: int agegomp= AGEGOMP;
1141:
1142: int imx;
1143: int stepm=1;
1144: /* Stepm, step in month: minimum step interpolation*/
1145:
1146: int estepm;
1147: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1148:
1149: int m,nb;
1150: long *num;
1.197 brouard 1151: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1152: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1153: covariate for which somebody answered excluding
1154: undefined. Usually 2: 0 and 1. */
1155: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1156: covariate for which somebody answered including
1157: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1158: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1159: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1160: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1161: double *ageexmed,*agecens;
1162: double dateintmean=0;
1163:
1164: double *weight;
1165: int **s; /* Status */
1.141 brouard 1166: double *agedc;
1.145 brouard 1167: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1168: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1169: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.225 brouard 1170: double **coqvar; /* Fixed quantitative covariate iqv */
1171: double ***cotvar; /* Time varying covariate itv */
1172: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1173: double idx;
1174: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1175: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1176: /*k 1 2 3 4 5 6 7 8 9 */
1177: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1178: /* Tndvar[k] 1 2 3 4 5 */
1179: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1180: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1181: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1182: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1183: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1184: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1185: /* Tprod[i]=k 4 7 */
1186: /* Tage[i]=k 5 8 */
1187: /* */
1188: /* Type */
1189: /* V 1 2 3 4 5 */
1190: /* F F V V V */
1191: /* D Q D D Q */
1192: /* */
1193: int *TvarsD;
1194: int *TvarsDind;
1195: int *TvarsQ;
1196: int *TvarsQind;
1197:
1.235 brouard 1198: #define MAXRESULTLINES 10
1199: int nresult=0;
1.258 brouard 1200: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1201: int TKresult[MAXRESULTLINES];
1.237 brouard 1202: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1203: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1204: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1205: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1206: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1207: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1208:
1.234 brouard 1209: /* 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 1210: 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 */
1211: 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 */
1212: 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 */
1213: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1214: 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 */
1215: 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 1216: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1217: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1218: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1219: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1220: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1221: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1222: 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 */
1223: 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 */
1224:
1.230 brouard 1225: int *Tvarsel; /**< Selected covariates for output */
1226: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1227: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1228: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1229: 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 1230: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1231: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1232: int *Tage;
1.227 brouard 1233: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1234: 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 1235: 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*/
1236: 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 1237: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1238: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1239: int **Tvard;
1240: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1241: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1242: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1243: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1244: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1245: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1246: double *lsurv, *lpop, *tpop;
1247:
1.231 brouard 1248: #define FD 1; /* Fixed dummy covariate */
1249: #define FQ 2; /* Fixed quantitative covariate */
1250: #define FP 3; /* Fixed product covariate */
1251: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1252: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1253: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1254: #define VD 10; /* Varying dummy covariate */
1255: #define VQ 11; /* Varying quantitative covariate */
1256: #define VP 12; /* Varying product covariate */
1257: #define VPDD 13; /* Varying product dummy*dummy covariate */
1258: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1259: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1260: #define APFD 16; /* Age product * fixed dummy covariate */
1261: #define APFQ 17; /* Age product * fixed quantitative covariate */
1262: #define APVD 18; /* Age product * varying dummy covariate */
1263: #define APVQ 19; /* Age product * varying quantitative covariate */
1264:
1265: #define FTYPE 1; /* Fixed covariate */
1266: #define VTYPE 2; /* Varying covariate (loop in wave) */
1267: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1268:
1269: struct kmodel{
1270: int maintype; /* main type */
1271: int subtype; /* subtype */
1272: };
1273: struct kmodel modell[NCOVMAX];
1274:
1.143 brouard 1275: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1276: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1277:
1278: /**************** split *************************/
1279: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1280: {
1281: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1282: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1283: */
1284: char *ss; /* pointer */
1.186 brouard 1285: int l1=0, l2=0; /* length counters */
1.126 brouard 1286:
1287: l1 = strlen(path ); /* length of path */
1288: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1289: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1290: if ( ss == NULL ) { /* no directory, so determine current directory */
1291: strcpy( name, path ); /* we got the fullname name because no directory */
1292: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1293: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1294: /* get current working directory */
1295: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1296: #ifdef WIN32
1297: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1298: #else
1299: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1300: #endif
1.126 brouard 1301: return( GLOCK_ERROR_GETCWD );
1302: }
1303: /* got dirc from getcwd*/
1304: printf(" DIRC = %s \n",dirc);
1.205 brouard 1305: } else { /* strip directory from path */
1.126 brouard 1306: ss++; /* after this, the filename */
1307: l2 = strlen( ss ); /* length of filename */
1308: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1309: strcpy( name, ss ); /* save file name */
1310: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1311: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1312: printf(" DIRC2 = %s \n",dirc);
1313: }
1314: /* We add a separator at the end of dirc if not exists */
1315: l1 = strlen( dirc ); /* length of directory */
1316: if( dirc[l1-1] != DIRSEPARATOR ){
1317: dirc[l1] = DIRSEPARATOR;
1318: dirc[l1+1] = 0;
1319: printf(" DIRC3 = %s \n",dirc);
1320: }
1321: ss = strrchr( name, '.' ); /* find last / */
1322: if (ss >0){
1323: ss++;
1324: strcpy(ext,ss); /* save extension */
1325: l1= strlen( name);
1326: l2= strlen(ss)+1;
1327: strncpy( finame, name, l1-l2);
1328: finame[l1-l2]= 0;
1329: }
1330:
1331: return( 0 ); /* we're done */
1332: }
1333:
1334:
1335: /******************************************/
1336:
1337: void replace_back_to_slash(char *s, char*t)
1338: {
1339: int i;
1340: int lg=0;
1341: i=0;
1342: lg=strlen(t);
1343: for(i=0; i<= lg; i++) {
1344: (s[i] = t[i]);
1345: if (t[i]== '\\') s[i]='/';
1346: }
1347: }
1348:
1.132 brouard 1349: char *trimbb(char *out, char *in)
1.137 brouard 1350: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1351: char *s;
1352: s=out;
1353: while (*in != '\0'){
1.137 brouard 1354: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1355: in++;
1356: }
1357: *out++ = *in++;
1358: }
1359: *out='\0';
1360: return s;
1361: }
1362:
1.187 brouard 1363: /* char *substrchaine(char *out, char *in, char *chain) */
1364: /* { */
1365: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1366: /* char *s, *t; */
1367: /* t=in;s=out; */
1368: /* while ((*in != *chain) && (*in != '\0')){ */
1369: /* *out++ = *in++; */
1370: /* } */
1371:
1372: /* /\* *in matches *chain *\/ */
1373: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1374: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1375: /* } */
1376: /* in--; chain--; */
1377: /* while ( (*in != '\0')){ */
1378: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1379: /* *out++ = *in++; */
1380: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1381: /* } */
1382: /* *out='\0'; */
1383: /* out=s; */
1384: /* return out; */
1385: /* } */
1386: char *substrchaine(char *out, char *in, char *chain)
1387: {
1388: /* Substract chain 'chain' from 'in', return and output 'out' */
1389: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1390:
1391: char *strloc;
1392:
1393: strcpy (out, in);
1394: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1395: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1396: if(strloc != NULL){
1397: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1398: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1399: /* strcpy (strloc, strloc +strlen(chain));*/
1400: }
1401: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1402: return out;
1403: }
1404:
1405:
1.145 brouard 1406: char *cutl(char *blocc, char *alocc, char *in, char occ)
1407: {
1.187 brouard 1408: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1409: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1410: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1411: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1412: */
1.160 brouard 1413: char *s, *t;
1.145 brouard 1414: t=in;s=in;
1415: while ((*in != occ) && (*in != '\0')){
1416: *alocc++ = *in++;
1417: }
1418: if( *in == occ){
1419: *(alocc)='\0';
1420: s=++in;
1421: }
1422:
1423: if (s == t) {/* occ not found */
1424: *(alocc-(in-s))='\0';
1425: in=s;
1426: }
1427: while ( *in != '\0'){
1428: *blocc++ = *in++;
1429: }
1430:
1431: *blocc='\0';
1432: return t;
1433: }
1.137 brouard 1434: char *cutv(char *blocc, char *alocc, char *in, char occ)
1435: {
1.187 brouard 1436: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1437: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1438: gives blocc="abcdef2ghi" and alocc="j".
1439: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1440: */
1441: char *s, *t;
1442: t=in;s=in;
1443: while (*in != '\0'){
1444: while( *in == occ){
1445: *blocc++ = *in++;
1446: s=in;
1447: }
1448: *blocc++ = *in++;
1449: }
1450: if (s == t) /* occ not found */
1451: *(blocc-(in-s))='\0';
1452: else
1453: *(blocc-(in-s)-1)='\0';
1454: in=s;
1455: while ( *in != '\0'){
1456: *alocc++ = *in++;
1457: }
1458:
1459: *alocc='\0';
1460: return s;
1461: }
1462:
1.126 brouard 1463: int nbocc(char *s, char occ)
1464: {
1465: int i,j=0;
1466: int lg=20;
1467: i=0;
1468: lg=strlen(s);
1469: for(i=0; i<= lg; i++) {
1.234 brouard 1470: if (s[i] == occ ) j++;
1.126 brouard 1471: }
1472: return j;
1473: }
1474:
1.137 brouard 1475: /* void cutv(char *u,char *v, char*t, char occ) */
1476: /* { */
1477: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1478: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1479: /* gives u="abcdef2ghi" and v="j" *\/ */
1480: /* int i,lg,j,p=0; */
1481: /* i=0; */
1482: /* lg=strlen(t); */
1483: /* for(j=0; j<=lg-1; j++) { */
1484: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1485: /* } */
1.126 brouard 1486:
1.137 brouard 1487: /* for(j=0; j<p; j++) { */
1488: /* (u[j] = t[j]); */
1489: /* } */
1490: /* u[p]='\0'; */
1.126 brouard 1491:
1.137 brouard 1492: /* for(j=0; j<= lg; j++) { */
1493: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1494: /* } */
1495: /* } */
1.126 brouard 1496:
1.160 brouard 1497: #ifdef _WIN32
1498: char * strsep(char **pp, const char *delim)
1499: {
1500: char *p, *q;
1501:
1502: if ((p = *pp) == NULL)
1503: return 0;
1504: if ((q = strpbrk (p, delim)) != NULL)
1505: {
1506: *pp = q + 1;
1507: *q = '\0';
1508: }
1509: else
1510: *pp = 0;
1511: return p;
1512: }
1513: #endif
1514:
1.126 brouard 1515: /********************** nrerror ********************/
1516:
1517: void nrerror(char error_text[])
1518: {
1519: fprintf(stderr,"ERREUR ...\n");
1520: fprintf(stderr,"%s\n",error_text);
1521: exit(EXIT_FAILURE);
1522: }
1523: /*********************** vector *******************/
1524: double *vector(int nl, int nh)
1525: {
1526: double *v;
1527: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1528: if (!v) nrerror("allocation failure in vector");
1529: return v-nl+NR_END;
1530: }
1531:
1532: /************************ free vector ******************/
1533: void free_vector(double*v, int nl, int nh)
1534: {
1535: free((FREE_ARG)(v+nl-NR_END));
1536: }
1537:
1538: /************************ivector *******************************/
1539: int *ivector(long nl,long nh)
1540: {
1541: int *v;
1542: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1543: if (!v) nrerror("allocation failure in ivector");
1544: return v-nl+NR_END;
1545: }
1546:
1547: /******************free ivector **************************/
1548: void free_ivector(int *v, long nl, long nh)
1549: {
1550: free((FREE_ARG)(v+nl-NR_END));
1551: }
1552:
1553: /************************lvector *******************************/
1554: long *lvector(long nl,long nh)
1555: {
1556: long *v;
1557: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1558: if (!v) nrerror("allocation failure in ivector");
1559: return v-nl+NR_END;
1560: }
1561:
1562: /******************free lvector **************************/
1563: void free_lvector(long *v, long nl, long nh)
1564: {
1565: free((FREE_ARG)(v+nl-NR_END));
1566: }
1567:
1568: /******************* imatrix *******************************/
1569: int **imatrix(long nrl, long nrh, long ncl, long nch)
1570: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1571: {
1572: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1573: int **m;
1574:
1575: /* allocate pointers to rows */
1576: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1577: if (!m) nrerror("allocation failure 1 in matrix()");
1578: m += NR_END;
1579: m -= nrl;
1580:
1581:
1582: /* allocate rows and set pointers to them */
1583: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1584: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1585: m[nrl] += NR_END;
1586: m[nrl] -= ncl;
1587:
1588: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1589:
1590: /* return pointer to array of pointers to rows */
1591: return m;
1592: }
1593:
1594: /****************** free_imatrix *************************/
1595: void free_imatrix(m,nrl,nrh,ncl,nch)
1596: int **m;
1597: long nch,ncl,nrh,nrl;
1598: /* free an int matrix allocated by imatrix() */
1599: {
1600: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1601: free((FREE_ARG) (m+nrl-NR_END));
1602: }
1603:
1604: /******************* matrix *******************************/
1605: double **matrix(long nrl, long nrh, long ncl, long nch)
1606: {
1607: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1608: double **m;
1609:
1610: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1611: if (!m) nrerror("allocation failure 1 in matrix()");
1612: m += NR_END;
1613: m -= nrl;
1614:
1615: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1616: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1617: m[nrl] += NR_END;
1618: m[nrl] -= ncl;
1619:
1620: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1621: return m;
1.145 brouard 1622: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1623: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1624: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1625: */
1626: }
1627:
1628: /*************************free matrix ************************/
1629: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1630: {
1631: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1632: free((FREE_ARG)(m+nrl-NR_END));
1633: }
1634:
1635: /******************* ma3x *******************************/
1636: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1637: {
1638: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1639: double ***m;
1640:
1641: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1642: if (!m) nrerror("allocation failure 1 in matrix()");
1643: m += NR_END;
1644: m -= nrl;
1645:
1646: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1647: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1648: m[nrl] += NR_END;
1649: m[nrl] -= ncl;
1650:
1651: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1652:
1653: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1654: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1655: m[nrl][ncl] += NR_END;
1656: m[nrl][ncl] -= nll;
1657: for (j=ncl+1; j<=nch; j++)
1658: m[nrl][j]=m[nrl][j-1]+nlay;
1659:
1660: for (i=nrl+1; i<=nrh; i++) {
1661: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1662: for (j=ncl+1; j<=nch; j++)
1663: m[i][j]=m[i][j-1]+nlay;
1664: }
1665: return m;
1666: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1667: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1668: */
1669: }
1670:
1671: /*************************free ma3x ************************/
1672: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1673: {
1674: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1675: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1676: free((FREE_ARG)(m+nrl-NR_END));
1677: }
1678:
1679: /*************** function subdirf ***********/
1680: char *subdirf(char fileres[])
1681: {
1682: /* Caution optionfilefiname is hidden */
1683: strcpy(tmpout,optionfilefiname);
1684: strcat(tmpout,"/"); /* Add to the right */
1685: strcat(tmpout,fileres);
1686: return tmpout;
1687: }
1688:
1689: /*************** function subdirf2 ***********/
1690: char *subdirf2(char fileres[], char *preop)
1691: {
1692:
1693: /* Caution optionfilefiname is hidden */
1694: strcpy(tmpout,optionfilefiname);
1695: strcat(tmpout,"/");
1696: strcat(tmpout,preop);
1697: strcat(tmpout,fileres);
1698: return tmpout;
1699: }
1700:
1701: /*************** function subdirf3 ***********/
1702: char *subdirf3(char fileres[], char *preop, char *preop2)
1703: {
1704:
1705: /* Caution optionfilefiname is hidden */
1706: strcpy(tmpout,optionfilefiname);
1707: strcat(tmpout,"/");
1708: strcat(tmpout,preop);
1709: strcat(tmpout,preop2);
1710: strcat(tmpout,fileres);
1711: return tmpout;
1712: }
1.213 brouard 1713:
1714: /*************** function subdirfext ***********/
1715: char *subdirfext(char fileres[], char *preop, char *postop)
1716: {
1717:
1718: strcpy(tmpout,preop);
1719: strcat(tmpout,fileres);
1720: strcat(tmpout,postop);
1721: return tmpout;
1722: }
1.126 brouard 1723:
1.213 brouard 1724: /*************** function subdirfext3 ***********/
1725: char *subdirfext3(char fileres[], char *preop, char *postop)
1726: {
1727:
1728: /* Caution optionfilefiname is hidden */
1729: strcpy(tmpout,optionfilefiname);
1730: strcat(tmpout,"/");
1731: strcat(tmpout,preop);
1732: strcat(tmpout,fileres);
1733: strcat(tmpout,postop);
1734: return tmpout;
1735: }
1736:
1.162 brouard 1737: char *asc_diff_time(long time_sec, char ascdiff[])
1738: {
1739: long sec_left, days, hours, minutes;
1740: days = (time_sec) / (60*60*24);
1741: sec_left = (time_sec) % (60*60*24);
1742: hours = (sec_left) / (60*60) ;
1743: sec_left = (sec_left) %(60*60);
1744: minutes = (sec_left) /60;
1745: sec_left = (sec_left) % (60);
1746: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1747: return ascdiff;
1748: }
1749:
1.126 brouard 1750: /***************** f1dim *************************/
1751: extern int ncom;
1752: extern double *pcom,*xicom;
1753: extern double (*nrfunc)(double []);
1754:
1755: double f1dim(double x)
1756: {
1757: int j;
1758: double f;
1759: double *xt;
1760:
1761: xt=vector(1,ncom);
1762: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1763: f=(*nrfunc)(xt);
1764: free_vector(xt,1,ncom);
1765: return f;
1766: }
1767:
1768: /*****************brent *************************/
1769: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1770: {
1771: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1772: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1773: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1774: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1775: * returned function value.
1776: */
1.126 brouard 1777: int iter;
1778: double a,b,d,etemp;
1.159 brouard 1779: double fu=0,fv,fw,fx;
1.164 brouard 1780: double ftemp=0.;
1.126 brouard 1781: double p,q,r,tol1,tol2,u,v,w,x,xm;
1782: double e=0.0;
1783:
1784: a=(ax < cx ? ax : cx);
1785: b=(ax > cx ? ax : cx);
1786: x=w=v=bx;
1787: fw=fv=fx=(*f)(x);
1788: for (iter=1;iter<=ITMAX;iter++) {
1789: xm=0.5*(a+b);
1790: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1791: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1792: printf(".");fflush(stdout);
1793: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1794: #ifdef DEBUGBRENT
1.126 brouard 1795: 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);
1796: 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);
1797: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1798: #endif
1799: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1800: *xmin=x;
1801: return fx;
1802: }
1803: ftemp=fu;
1804: if (fabs(e) > tol1) {
1805: r=(x-w)*(fx-fv);
1806: q=(x-v)*(fx-fw);
1807: p=(x-v)*q-(x-w)*r;
1808: q=2.0*(q-r);
1809: if (q > 0.0) p = -p;
1810: q=fabs(q);
1811: etemp=e;
1812: e=d;
1813: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1814: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1815: else {
1.224 brouard 1816: d=p/q;
1817: u=x+d;
1818: if (u-a < tol2 || b-u < tol2)
1819: d=SIGN(tol1,xm-x);
1.126 brouard 1820: }
1821: } else {
1822: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1823: }
1824: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1825: fu=(*f)(u);
1826: if (fu <= fx) {
1827: if (u >= x) a=x; else b=x;
1828: SHFT(v,w,x,u)
1.183 brouard 1829: SHFT(fv,fw,fx,fu)
1830: } else {
1831: if (u < x) a=u; else b=u;
1832: if (fu <= fw || w == x) {
1.224 brouard 1833: v=w;
1834: w=u;
1835: fv=fw;
1836: fw=fu;
1.183 brouard 1837: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1838: v=u;
1839: fv=fu;
1.183 brouard 1840: }
1841: }
1.126 brouard 1842: }
1843: nrerror("Too many iterations in brent");
1844: *xmin=x;
1845: return fx;
1846: }
1847:
1848: /****************** mnbrak ***********************/
1849:
1850: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1851: double (*func)(double))
1.183 brouard 1852: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1853: the downhill direction (defined by the function as evaluated at the initial points) and returns
1854: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1855: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1856: */
1.126 brouard 1857: double ulim,u,r,q, dum;
1858: double fu;
1.187 brouard 1859:
1860: double scale=10.;
1861: int iterscale=0;
1862:
1863: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1864: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1865:
1866:
1867: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1868: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1869: /* *bx = *ax - (*ax - *bx)/scale; */
1870: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1871: /* } */
1872:
1.126 brouard 1873: if (*fb > *fa) {
1874: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1875: SHFT(dum,*fb,*fa,dum)
1876: }
1.126 brouard 1877: *cx=(*bx)+GOLD*(*bx-*ax);
1878: *fc=(*func)(*cx);
1.183 brouard 1879: #ifdef DEBUG
1.224 brouard 1880: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1881: 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 1882: #endif
1.224 brouard 1883: 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 1884: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1885: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1886: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1887: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1888: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1889: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1890: fu=(*func)(u);
1.163 brouard 1891: #ifdef DEBUG
1892: /* f(x)=A(x-u)**2+f(u) */
1893: double A, fparabu;
1894: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1895: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 1896: 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);
1897: 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 1898: /* And thus,it can be that fu > *fc even if fparabu < *fc */
1899: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
1900: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
1901: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 1902: #endif
1.184 brouard 1903: #ifdef MNBRAKORIGINAL
1.183 brouard 1904: #else
1.191 brouard 1905: /* if (fu > *fc) { */
1906: /* #ifdef DEBUG */
1907: /* printf("mnbrak4 fu > fc \n"); */
1908: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
1909: /* #endif */
1910: /* /\* 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 *\\/ *\/ */
1911: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
1912: /* dum=u; /\* Shifting c and u *\/ */
1913: /* u = *cx; */
1914: /* *cx = dum; */
1915: /* dum = fu; */
1916: /* fu = *fc; */
1917: /* *fc =dum; */
1918: /* } else { /\* end *\/ */
1919: /* #ifdef DEBUG */
1920: /* printf("mnbrak3 fu < fc \n"); */
1921: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
1922: /* #endif */
1923: /* dum=u; /\* Shifting c and u *\/ */
1924: /* u = *cx; */
1925: /* *cx = dum; */
1926: /* dum = fu; */
1927: /* fu = *fc; */
1928: /* *fc =dum; */
1929: /* } */
1.224 brouard 1930: #ifdef DEBUGMNBRAK
1931: double A, fparabu;
1932: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1933: fparabu= *fa - A*(*ax-u)*(*ax-u);
1934: 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);
1935: 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 1936: #endif
1.191 brouard 1937: dum=u; /* Shifting c and u */
1938: u = *cx;
1939: *cx = dum;
1940: dum = fu;
1941: fu = *fc;
1942: *fc =dum;
1.183 brouard 1943: #endif
1.162 brouard 1944: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 1945: #ifdef DEBUG
1.224 brouard 1946: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1947: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 1948: #endif
1.126 brouard 1949: fu=(*func)(u);
1950: if (fu < *fc) {
1.183 brouard 1951: #ifdef DEBUG
1.224 brouard 1952: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
1953: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
1954: #endif
1955: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
1956: SHFT(*fb,*fc,fu,(*func)(u))
1957: #ifdef DEBUG
1958: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 1959: #endif
1960: }
1.162 brouard 1961: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 1962: #ifdef DEBUG
1.224 brouard 1963: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1964: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 1965: #endif
1.126 brouard 1966: u=ulim;
1967: fu=(*func)(u);
1.183 brouard 1968: } else { /* u could be left to b (if r > q parabola has a maximum) */
1969: #ifdef DEBUG
1.224 brouard 1970: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
1971: 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 1972: #endif
1.126 brouard 1973: u=(*cx)+GOLD*(*cx-*bx);
1974: fu=(*func)(u);
1.224 brouard 1975: #ifdef DEBUG
1976: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
1977: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
1978: #endif
1.183 brouard 1979: } /* end tests */
1.126 brouard 1980: SHFT(*ax,*bx,*cx,u)
1.183 brouard 1981: SHFT(*fa,*fb,*fc,fu)
1982: #ifdef DEBUG
1.224 brouard 1983: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
1984: 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 1985: #endif
1986: } /* 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 1987: }
1988:
1989: /*************** linmin ************************/
1.162 brouard 1990: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
1991: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
1992: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
1993: the value of func at the returned location p . This is actually all accomplished by calling the
1994: routines mnbrak and brent .*/
1.126 brouard 1995: int ncom;
1996: double *pcom,*xicom;
1997: double (*nrfunc)(double []);
1998:
1.224 brouard 1999: #ifdef LINMINORIGINAL
1.126 brouard 2000: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2001: #else
2002: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2003: #endif
1.126 brouard 2004: {
2005: double brent(double ax, double bx, double cx,
2006: double (*f)(double), double tol, double *xmin);
2007: double f1dim(double x);
2008: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2009: double *fc, double (*func)(double));
2010: int j;
2011: double xx,xmin,bx,ax;
2012: double fx,fb,fa;
1.187 brouard 2013:
1.203 brouard 2014: #ifdef LINMINORIGINAL
2015: #else
2016: double scale=10., axs, xxs; /* Scale added for infinity */
2017: #endif
2018:
1.126 brouard 2019: ncom=n;
2020: pcom=vector(1,n);
2021: xicom=vector(1,n);
2022: nrfunc=func;
2023: for (j=1;j<=n;j++) {
2024: pcom[j]=p[j];
1.202 brouard 2025: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2026: }
1.187 brouard 2027:
1.203 brouard 2028: #ifdef LINMINORIGINAL
2029: xx=1.;
2030: #else
2031: axs=0.0;
2032: xxs=1.;
2033: do{
2034: xx= xxs;
2035: #endif
1.187 brouard 2036: ax=0.;
2037: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2038: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2039: /* 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)) */
2040: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2041: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2042: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2043: /* 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 2044: #ifdef LINMINORIGINAL
2045: #else
2046: if (fx != fx){
1.224 brouard 2047: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2048: printf("|");
2049: fprintf(ficlog,"|");
1.203 brouard 2050: #ifdef DEBUGLINMIN
1.224 brouard 2051: 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 2052: #endif
2053: }
1.224 brouard 2054: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2055: #endif
2056:
1.191 brouard 2057: #ifdef DEBUGLINMIN
2058: 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 2059: 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 2060: #endif
1.224 brouard 2061: #ifdef LINMINORIGINAL
2062: #else
2063: if(fb == fx){ /* Flat function in the direction */
2064: xmin=xx;
2065: *flat=1;
2066: }else{
2067: *flat=0;
2068: #endif
2069: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2070: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2071: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2072: /* fmin = f(p[j] + xmin * xi[j]) */
2073: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2074: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2075: #ifdef DEBUG
1.224 brouard 2076: 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);
2077: 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);
2078: #endif
2079: #ifdef LINMINORIGINAL
2080: #else
2081: }
1.126 brouard 2082: #endif
1.191 brouard 2083: #ifdef DEBUGLINMIN
2084: printf("linmin end ");
1.202 brouard 2085: fprintf(ficlog,"linmin end ");
1.191 brouard 2086: #endif
1.126 brouard 2087: for (j=1;j<=n;j++) {
1.203 brouard 2088: #ifdef LINMINORIGINAL
2089: xi[j] *= xmin;
2090: #else
2091: #ifdef DEBUGLINMIN
2092: if(xxs <1.0)
2093: printf(" before xi[%d]=%12.8f", j,xi[j]);
2094: #endif
2095: 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) */
2096: #ifdef DEBUGLINMIN
2097: if(xxs <1.0)
2098: 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 );
2099: #endif
2100: #endif
1.187 brouard 2101: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2102: }
1.191 brouard 2103: #ifdef DEBUGLINMIN
1.203 brouard 2104: printf("\n");
1.191 brouard 2105: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2106: 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 2107: for (j=1;j<=n;j++) {
1.202 brouard 2108: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2109: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2110: if(j % ncovmodel == 0){
1.191 brouard 2111: printf("\n");
1.202 brouard 2112: fprintf(ficlog,"\n");
2113: }
1.191 brouard 2114: }
1.203 brouard 2115: #else
1.191 brouard 2116: #endif
1.126 brouard 2117: free_vector(xicom,1,n);
2118: free_vector(pcom,1,n);
2119: }
2120:
2121:
2122: /*************** powell ************************/
1.162 brouard 2123: /*
2124: Minimization of a function func of n variables. Input consists of an initial starting point
2125: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2126: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2127: such that failure to decrease by more than this amount on one iteration signals doneness. On
2128: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2129: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2130: */
1.224 brouard 2131: #ifdef LINMINORIGINAL
2132: #else
2133: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2134: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2135: #endif
1.126 brouard 2136: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2137: double (*func)(double []))
2138: {
1.224 brouard 2139: #ifdef LINMINORIGINAL
2140: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2141: double (*func)(double []));
1.224 brouard 2142: #else
1.241 brouard 2143: void linmin(double p[], double xi[], int n, double *fret,
2144: double (*func)(double []),int *flat);
1.224 brouard 2145: #endif
1.239 brouard 2146: int i,ibig,j,jk,k;
1.126 brouard 2147: double del,t,*pt,*ptt,*xit;
1.181 brouard 2148: double directest;
1.126 brouard 2149: double fp,fptt;
2150: double *xits;
2151: int niterf, itmp;
1.224 brouard 2152: #ifdef LINMINORIGINAL
2153: #else
2154:
2155: flatdir=ivector(1,n);
2156: for (j=1;j<=n;j++) flatdir[j]=0;
2157: #endif
1.126 brouard 2158:
2159: pt=vector(1,n);
2160: ptt=vector(1,n);
2161: xit=vector(1,n);
2162: xits=vector(1,n);
2163: *fret=(*func)(p);
2164: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2165: rcurr_time = time(NULL);
1.126 brouard 2166: for (*iter=1;;++(*iter)) {
1.187 brouard 2167: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2168: ibig=0;
2169: del=0.0;
1.157 brouard 2170: rlast_time=rcurr_time;
2171: /* (void) gettimeofday(&curr_time,&tzp); */
2172: rcurr_time = time(NULL);
2173: curr_time = *localtime(&rcurr_time);
2174: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2175: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2176: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2177: for (i=1;i<=n;i++) {
1.126 brouard 2178: fprintf(ficrespow," %.12lf", p[i]);
2179: }
1.239 brouard 2180: fprintf(ficrespow,"\n");fflush(ficrespow);
2181: printf("\n#model= 1 + age ");
2182: fprintf(ficlog,"\n#model= 1 + age ");
2183: if(nagesqr==1){
1.241 brouard 2184: printf(" + age*age ");
2185: fprintf(ficlog," + age*age ");
1.239 brouard 2186: }
2187: for(j=1;j <=ncovmodel-2;j++){
2188: if(Typevar[j]==0) {
2189: printf(" + V%d ",Tvar[j]);
2190: fprintf(ficlog," + V%d ",Tvar[j]);
2191: }else if(Typevar[j]==1) {
2192: printf(" + V%d*age ",Tvar[j]);
2193: fprintf(ficlog," + V%d*age ",Tvar[j]);
2194: }else if(Typevar[j]==2) {
2195: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2196: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2197: }
2198: }
1.126 brouard 2199: printf("\n");
1.239 brouard 2200: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2201: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2202: fprintf(ficlog,"\n");
1.239 brouard 2203: for(i=1,jk=1; i <=nlstate; i++){
2204: for(k=1; k <=(nlstate+ndeath); k++){
2205: if (k != i) {
2206: printf("%d%d ",i,k);
2207: fprintf(ficlog,"%d%d ",i,k);
2208: for(j=1; j <=ncovmodel; j++){
2209: printf("%12.7f ",p[jk]);
2210: fprintf(ficlog,"%12.7f ",p[jk]);
2211: jk++;
2212: }
2213: printf("\n");
2214: fprintf(ficlog,"\n");
2215: }
2216: }
2217: }
1.241 brouard 2218: if(*iter <=3 && *iter >1){
1.157 brouard 2219: tml = *localtime(&rcurr_time);
2220: strcpy(strcurr,asctime(&tml));
2221: rforecast_time=rcurr_time;
1.126 brouard 2222: itmp = strlen(strcurr);
2223: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2224: strcurr[itmp-1]='\0';
1.162 brouard 2225: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2226: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2227: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2228: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2229: forecast_time = *localtime(&rforecast_time);
2230: strcpy(strfor,asctime(&forecast_time));
2231: itmp = strlen(strfor);
2232: if(strfor[itmp-1]=='\n')
2233: strfor[itmp-1]='\0';
2234: 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);
2235: 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 2236: }
2237: }
1.187 brouard 2238: for (i=1;i<=n;i++) { /* For each direction i */
2239: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2240: fptt=(*fret);
2241: #ifdef DEBUG
1.203 brouard 2242: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2243: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2244: #endif
1.203 brouard 2245: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2246: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2247: #ifdef LINMINORIGINAL
1.188 brouard 2248: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2249: #else
2250: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2251: flatdir[i]=flat; /* Function is vanishing in that direction i */
2252: #endif
2253: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2254: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2255: /* because that direction will be replaced unless the gain del is small */
2256: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2257: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2258: /* with the new direction. */
2259: del=fabs(fptt-(*fret));
2260: ibig=i;
1.126 brouard 2261: }
2262: #ifdef DEBUG
2263: printf("%d %.12e",i,(*fret));
2264: fprintf(ficlog,"%d %.12e",i,(*fret));
2265: for (j=1;j<=n;j++) {
1.224 brouard 2266: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2267: printf(" x(%d)=%.12e",j,xit[j]);
2268: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2269: }
2270: for(j=1;j<=n;j++) {
1.225 brouard 2271: printf(" p(%d)=%.12e",j,p[j]);
2272: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2273: }
2274: printf("\n");
2275: fprintf(ficlog,"\n");
2276: #endif
1.187 brouard 2277: } /* end loop on each direction i */
2278: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2279: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2280: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2281: for(j=1;j<=n;j++) {
1.225 brouard 2282: if(flatdir[j] >0){
2283: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2284: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2285: }
2286: /* printf("\n"); */
2287: /* fprintf(ficlog,"\n"); */
2288: }
1.243 brouard 2289: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2290: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2291: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2292: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2293: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2294: /* decreased of more than 3.84 */
2295: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2296: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2297: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2298:
1.188 brouard 2299: /* Starting the program with initial values given by a former maximization will simply change */
2300: /* the scales of the directions and the directions, because the are reset to canonical directions */
2301: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2302: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2303: #ifdef DEBUG
2304: int k[2],l;
2305: k[0]=1;
2306: k[1]=-1;
2307: printf("Max: %.12e",(*func)(p));
2308: fprintf(ficlog,"Max: %.12e",(*func)(p));
2309: for (j=1;j<=n;j++) {
2310: printf(" %.12e",p[j]);
2311: fprintf(ficlog," %.12e",p[j]);
2312: }
2313: printf("\n");
2314: fprintf(ficlog,"\n");
2315: for(l=0;l<=1;l++) {
2316: for (j=1;j<=n;j++) {
2317: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2318: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2319: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2320: }
2321: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2322: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2323: }
2324: #endif
2325:
1.224 brouard 2326: #ifdef LINMINORIGINAL
2327: #else
2328: free_ivector(flatdir,1,n);
2329: #endif
1.126 brouard 2330: free_vector(xit,1,n);
2331: free_vector(xits,1,n);
2332: free_vector(ptt,1,n);
2333: free_vector(pt,1,n);
2334: return;
1.192 brouard 2335: } /* enough precision */
1.240 brouard 2336: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2337: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2338: ptt[j]=2.0*p[j]-pt[j];
2339: xit[j]=p[j]-pt[j];
2340: pt[j]=p[j];
2341: }
1.181 brouard 2342: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2343: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2344: if (*iter <=4) {
1.225 brouard 2345: #else
2346: #endif
1.224 brouard 2347: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2348: #else
1.161 brouard 2349: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2350: #endif
1.162 brouard 2351: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2352: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2353: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2354: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2355: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2356: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2357: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2358: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2359: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2360: /* Even if f3 <f1, directest can be negative and t >0 */
2361: /* mu² and del² are equal when f3=f1 */
2362: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2363: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2364: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2365: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2366: #ifdef NRCORIGINAL
2367: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2368: #else
2369: 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 2370: t= t- del*SQR(fp-fptt);
1.183 brouard 2371: #endif
1.202 brouard 2372: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2373: #ifdef DEBUG
1.181 brouard 2374: 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);
2375: 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 2376: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2377: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2378: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2379: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2380: 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);
2381: 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);
2382: #endif
1.183 brouard 2383: #ifdef POWELLORIGINAL
2384: if (t < 0.0) { /* Then we use it for new direction */
2385: #else
1.182 brouard 2386: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2387: 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 2388: 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 2389: 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 2390: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2391: }
1.181 brouard 2392: if (directest < 0.0) { /* Then we use it for new direction */
2393: #endif
1.191 brouard 2394: #ifdef DEBUGLINMIN
1.234 brouard 2395: printf("Before linmin in direction P%d-P0\n",n);
2396: for (j=1;j<=n;j++) {
2397: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2398: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2399: if(j % ncovmodel == 0){
2400: printf("\n");
2401: fprintf(ficlog,"\n");
2402: }
2403: }
1.224 brouard 2404: #endif
2405: #ifdef LINMINORIGINAL
1.234 brouard 2406: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2407: #else
1.234 brouard 2408: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2409: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2410: #endif
1.234 brouard 2411:
1.191 brouard 2412: #ifdef DEBUGLINMIN
1.234 brouard 2413: for (j=1;j<=n;j++) {
2414: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2415: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2416: if(j % ncovmodel == 0){
2417: printf("\n");
2418: fprintf(ficlog,"\n");
2419: }
2420: }
1.224 brouard 2421: #endif
1.234 brouard 2422: for (j=1;j<=n;j++) {
2423: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2424: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2425: }
1.224 brouard 2426: #ifdef LINMINORIGINAL
2427: #else
1.234 brouard 2428: for (j=1, flatd=0;j<=n;j++) {
2429: if(flatdir[j]>0)
2430: flatd++;
2431: }
2432: if(flatd >0){
1.255 brouard 2433: printf("%d flat directions: ",flatd);
2434: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2435: for (j=1;j<=n;j++) {
2436: if(flatdir[j]>0){
2437: printf("%d ",j);
2438: fprintf(ficlog,"%d ",j);
2439: }
2440: }
2441: printf("\n");
2442: fprintf(ficlog,"\n");
2443: }
1.191 brouard 2444: #endif
1.234 brouard 2445: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2446: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2447:
1.126 brouard 2448: #ifdef DEBUG
1.234 brouard 2449: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2450: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2451: for(j=1;j<=n;j++){
2452: printf(" %lf",xit[j]);
2453: fprintf(ficlog," %lf",xit[j]);
2454: }
2455: printf("\n");
2456: fprintf(ficlog,"\n");
1.126 brouard 2457: #endif
1.192 brouard 2458: } /* end of t or directest negative */
1.224 brouard 2459: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2460: #else
1.234 brouard 2461: } /* end if (fptt < fp) */
1.192 brouard 2462: #endif
1.225 brouard 2463: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2464: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2465: #else
1.224 brouard 2466: #endif
1.234 brouard 2467: } /* loop iteration */
1.126 brouard 2468: }
1.234 brouard 2469:
1.126 brouard 2470: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2471:
1.235 brouard 2472: 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 2473: {
1.235 brouard 2474: /* Computes the prevalence limit in each live state at age x and for covariate combination ij
2475: (and selected quantitative values in nres)
2476: by left multiplying the unit
1.234 brouard 2477: matrix by transitions matrix until convergence is reached with precision ftolpl */
1.206 brouard 2478: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2479: /* Wx is row vector: population in state 1, population in state 2, population dead */
2480: /* or prevalence in state 1, prevalence in state 2, 0 */
2481: /* newm is the matrix after multiplications, its rows are identical at a factor */
2482: /* Initial matrix pimij */
2483: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2484: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2485: /* 0, 0 , 1} */
2486: /*
2487: * and after some iteration: */
2488: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2489: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2490: /* 0, 0 , 1} */
2491: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2492: /* {0.51571254859325999, 0.4842874514067399, */
2493: /* 0.51326036147820708, 0.48673963852179264} */
2494: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2495:
1.126 brouard 2496: int i, ii,j,k;
1.209 brouard 2497: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2498: /* double **matprod2(); */ /* test */
1.218 brouard 2499: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2500: double **newm;
1.209 brouard 2501: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2502: int ncvloop=0;
1.169 brouard 2503:
1.209 brouard 2504: min=vector(1,nlstate);
2505: max=vector(1,nlstate);
2506: meandiff=vector(1,nlstate);
2507:
1.218 brouard 2508: /* Starting with matrix unity */
1.126 brouard 2509: for (ii=1;ii<=nlstate+ndeath;ii++)
2510: for (j=1;j<=nlstate+ndeath;j++){
2511: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2512: }
1.169 brouard 2513:
2514: cov[1]=1.;
2515:
2516: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2517: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2518: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2519: ncvloop++;
1.126 brouard 2520: newm=savm;
2521: /* Covariates have to be included here again */
1.138 brouard 2522: cov[2]=agefin;
1.187 brouard 2523: if(nagesqr==1)
2524: cov[3]= agefin*agefin;;
1.234 brouard 2525: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2526: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2527: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2528: /* 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 2529: }
2530: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2531: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2532: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2533: /* 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 2534: }
1.237 brouard 2535: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2536: if(Dummy[Tvar[Tage[k]]]){
2537: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2538: } else{
1.235 brouard 2539: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2540: }
1.235 brouard 2541: /* 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 2542: }
1.237 brouard 2543: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2544: /* 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 2545: if(Dummy[Tvard[k][1]==0]){
2546: if(Dummy[Tvard[k][2]==0]){
2547: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2548: }else{
2549: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2550: }
2551: }else{
2552: if(Dummy[Tvard[k][2]==0]){
2553: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2554: }else{
2555: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2556: }
2557: }
1.234 brouard 2558: }
1.138 brouard 2559: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2560: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2561: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2562: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2563: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2564: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2565: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2566:
1.126 brouard 2567: savm=oldm;
2568: oldm=newm;
1.209 brouard 2569:
2570: for(j=1; j<=nlstate; j++){
2571: max[j]=0.;
2572: min[j]=1.;
2573: }
2574: for(i=1;i<=nlstate;i++){
2575: sumnew=0;
2576: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2577: for(j=1; j<=nlstate; j++){
2578: prlim[i][j]= newm[i][j]/(1-sumnew);
2579: max[j]=FMAX(max[j],prlim[i][j]);
2580: min[j]=FMIN(min[j],prlim[i][j]);
2581: }
2582: }
2583:
1.126 brouard 2584: maxmax=0.;
1.209 brouard 2585: for(j=1; j<=nlstate; j++){
2586: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2587: maxmax=FMAX(maxmax,meandiff[j]);
2588: /* 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 2589: } /* j loop */
1.203 brouard 2590: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2591: /* 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 2592: if(maxmax < ftolpl){
1.209 brouard 2593: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2594: free_vector(min,1,nlstate);
2595: free_vector(max,1,nlstate);
2596: free_vector(meandiff,1,nlstate);
1.126 brouard 2597: return prlim;
2598: }
1.169 brouard 2599: } /* age loop */
1.208 brouard 2600: /* After some age loop it doesn't converge */
1.209 brouard 2601: printf("Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.0f years. Try to lower 'ftolpl'. \n\
1.208 brouard 2602: Earliest age to start was %d-%d=%d, ncvloop=%d, ncvyear=%d\n", (int)age, maxmax, ftolpl, delaymax, (int)age, (int)delaymax, (int)agefin, ncvloop, *ncvyear);
1.209 brouard 2603: /* 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); */
2604: free_vector(min,1,nlstate);
2605: free_vector(max,1,nlstate);
2606: free_vector(meandiff,1,nlstate);
1.208 brouard 2607:
1.169 brouard 2608: return prlim; /* should not reach here */
1.126 brouard 2609: }
2610:
1.217 brouard 2611:
2612: /**** Back Prevalence limit (stable or period prevalence) ****************/
2613:
1.218 brouard 2614: /* 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) */
2615: /* 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 2616: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2617: {
1.264 ! brouard 2618: /* 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 2619: matrix by transitions matrix until convergence is reached with precision ftolpl */
2620: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2621: /* Wx is row vector: population in state 1, population in state 2, population dead */
2622: /* or prevalence in state 1, prevalence in state 2, 0 */
2623: /* newm is the matrix after multiplications, its rows are identical at a factor */
2624: /* Initial matrix pimij */
2625: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2626: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2627: /* 0, 0 , 1} */
2628: /*
2629: * and after some iteration: */
2630: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2631: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2632: /* 0, 0 , 1} */
2633: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2634: /* {0.51571254859325999, 0.4842874514067399, */
2635: /* 0.51326036147820708, 0.48673963852179264} */
2636: /* If we start from prlim again, prlim tends to a constant matrix */
2637:
2638: int i, ii,j,k;
1.247 brouard 2639: int first=0;
1.217 brouard 2640: double *min, *max, *meandiff, maxmax,sumnew=0.;
2641: /* double **matprod2(); */ /* test */
2642: double **out, cov[NCOVMAX+1], **bmij();
2643: double **newm;
1.218 brouard 2644: double **dnewm, **doldm, **dsavm; /* for use */
2645: double **oldm, **savm; /* for use */
2646:
1.217 brouard 2647: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2648: int ncvloop=0;
2649:
2650: min=vector(1,nlstate);
2651: max=vector(1,nlstate);
2652: meandiff=vector(1,nlstate);
2653:
1.218 brouard 2654: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2655: oldm=oldms; savm=savms;
2656:
2657: /* Starting with matrix unity */
2658: for (ii=1;ii<=nlstate+ndeath;ii++)
2659: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2660: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2661: }
2662:
2663: cov[1]=1.;
2664:
2665: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2666: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2667: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2668: for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2669: ncvloop++;
1.218 brouard 2670: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2671: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2672: /* Covariates have to be included here again */
2673: cov[2]=agefin;
2674: if(nagesqr==1)
2675: cov[3]= agefin*agefin;;
1.242 brouard 2676: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2677: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2678: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 ! brouard 2679: /* 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 2680: }
2681: /* for (k=1; k<=cptcovn;k++) { */
2682: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2683: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2684: /* /\* 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])]); *\/ */
2685: /* } */
2686: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2687: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2688: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2689: /* 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]); */
2690: }
2691: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2692: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2693: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2694: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2695: for (k=1; k<=cptcovage;k++){ /* For product with age */
2696: if(Dummy[Tvar[Tage[k]]]){
2697: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2698: } else{
2699: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2700: }
2701: /* 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]); */
2702: }
2703: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2704: /* 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]); */
2705: if(Dummy[Tvard[k][1]==0]){
2706: if(Dummy[Tvard[k][2]==0]){
2707: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2708: }else{
2709: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2710: }
2711: }else{
2712: if(Dummy[Tvard[k][2]==0]){
2713: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2714: }else{
2715: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2716: }
2717: }
1.217 brouard 2718: }
2719:
2720: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2721: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2722: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2723: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2724: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2725: /* ij should be linked to the correct index of cov */
2726: /* age and covariate values ij are in 'cov', but we need to pass
2727: * ij for the observed prevalence at age and status and covariate
2728: * number: prevacurrent[(int)agefin][ii][ij]
2729: */
2730: /* 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 *\/ */
2731: /* 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 *\/ */
2732: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij)); /* Bug Valgrind */
1.217 brouard 2733: savm=oldm;
2734: oldm=newm;
2735: for(j=1; j<=nlstate; j++){
2736: max[j]=0.;
2737: min[j]=1.;
2738: }
2739: for(j=1; j<=nlstate; j++){
2740: for(i=1;i<=nlstate;i++){
1.234 brouard 2741: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2742: bprlim[i][j]= newm[i][j];
2743: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2744: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2745: }
2746: }
1.218 brouard 2747:
1.217 brouard 2748: maxmax=0.;
2749: for(i=1; i<=nlstate; i++){
2750: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2751: maxmax=FMAX(maxmax,meandiff[i]);
2752: /* 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); */
2753: } /* j loop */
2754: *ncvyear= -( (int)age- (int)agefin);
1.218 brouard 2755: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear);*/
1.217 brouard 2756: if(maxmax < ftolpl){
1.220 brouard 2757: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2758: free_vector(min,1,nlstate);
2759: free_vector(max,1,nlstate);
2760: free_vector(meandiff,1,nlstate);
2761: return bprlim;
2762: }
2763: } /* age loop */
2764: /* After some age loop it doesn't converge */
1.247 brouard 2765: if(first){
2766: first=1;
2767: 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\
2768: 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);
2769: }
2770: 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 2771: 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);
2772: /* 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); */
2773: free_vector(min,1,nlstate);
2774: free_vector(max,1,nlstate);
2775: free_vector(meandiff,1,nlstate);
2776:
2777: return bprlim; /* should not reach here */
2778: }
2779:
1.126 brouard 2780: /*************** transition probabilities ***************/
2781:
2782: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2783: {
1.138 brouard 2784: /* According to parameters values stored in x and the covariate's values stored in cov,
2785: computes the probability to be observed in state j being in state i by appying the
2786: model to the ncovmodel covariates (including constant and age).
2787: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2788: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2789: ncth covariate in the global vector x is given by the formula:
2790: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2791: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2792: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2793: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
2794: Outputs ps[i][j] the probability to be observed in j being in j according to
2795: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
2796: */
2797: double s1, lnpijopii;
1.126 brouard 2798: /*double t34;*/
1.164 brouard 2799: int i,j, nc, ii, jj;
1.126 brouard 2800:
1.223 brouard 2801: for(i=1; i<= nlstate; i++){
2802: for(j=1; j<i;j++){
2803: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2804: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2805: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2806: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2807: }
2808: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2809: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2810: }
2811: for(j=i+1; j<=nlstate+ndeath;j++){
2812: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2813: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2814: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2815: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2816: }
2817: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2818: }
2819: }
1.218 brouard 2820:
1.223 brouard 2821: for(i=1; i<= nlstate; i++){
2822: s1=0;
2823: for(j=1; j<i; j++){
2824: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2825: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2826: }
2827: for(j=i+1; j<=nlstate+ndeath; j++){
2828: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2829: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2830: }
2831: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2832: ps[i][i]=1./(s1+1.);
2833: /* Computing other pijs */
2834: for(j=1; j<i; j++)
2835: ps[i][j]= exp(ps[i][j])*ps[i][i];
2836: for(j=i+1; j<=nlstate+ndeath; j++)
2837: ps[i][j]= exp(ps[i][j])*ps[i][i];
2838: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2839: } /* end i */
1.218 brouard 2840:
1.223 brouard 2841: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2842: for(jj=1; jj<= nlstate+ndeath; jj++){
2843: ps[ii][jj]=0;
2844: ps[ii][ii]=1;
2845: }
2846: }
1.218 brouard 2847:
2848:
1.223 brouard 2849: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2850: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2851: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2852: /* } */
2853: /* printf("\n "); */
2854: /* } */
2855: /* printf("\n ");printf("%lf ",cov[2]);*/
2856: /*
2857: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2858: goto end;*/
1.223 brouard 2859: return ps;
1.126 brouard 2860: }
2861:
1.218 brouard 2862: /*************** backward transition probabilities ***************/
2863:
2864: /* 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 ) */
2865: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2866: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
2867: {
1.222 brouard 2868: /* Computes the backward probability at age agefin and covariate ij
2869: * and returns in **ps as well as **bmij.
2870: */
1.218 brouard 2871: int i, ii, j,k;
1.222 brouard 2872:
2873: double **out, **pmij();
2874: double sumnew=0.;
1.218 brouard 2875: double agefin;
1.222 brouard 2876:
2877: double **dnewm, **dsavm, **doldm;
2878: double **bbmij;
2879:
1.218 brouard 2880: doldm=ddoldms; /* global pointers */
1.222 brouard 2881: dnewm=ddnewms;
2882: dsavm=ddsavms;
2883:
2884: agefin=cov[2];
2885: /* bmij *//* age is cov[2], ij is included in cov, but we need for
2886: the observed prevalence (with this covariate ij) */
2887: dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate);
2888: /* We do have the matrix Px in savm and we need pij */
2889: for (j=1;j<=nlstate+ndeath;j++){
2890: sumnew=0.; /* w1 p11 + w2 p21 only on live states */
2891: for (ii=1;ii<=nlstate;ii++){
2892: sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij];
2893: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
2894: for (ii=1;ii<=nlstate+ndeath;ii++){
2895: if(sumnew >= 1.e-10){
2896: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
2897: /* doldm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
2898: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
2899: /* doldm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
2900: /* }else */
2901: doldm[ii][j]=(ii==j ? 1./sumnew : 0.0);
2902: }else{
1.242 brouard 2903: ;
2904: /* printf("ii=%d, i=%d, doldm=%lf dsavm=%lf, probs=%lf, sumnew=%lf,agefin=%d\n",ii,j,doldm[ii][j],dsavm[ii][j],prevacurrent[(int)agefin][ii][ij],sumnew, (int)agefin); */
1.222 brouard 2905: }
2906: } /*End ii */
2907: } /* End j, At the end doldm is diag[1/(w_1p1i+w_2 p2i)] */
2908: /* left Product of this diag matrix by dsavm=Px (newm=dsavm*doldm) */
2909: bbmij=matprod2(dnewm, dsavm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, doldm); /* Bug Valgrind */
2910: /* dsavm=doldm; /\* dsavm is now diag [1/(w_1p1i+w_2 p2i)] but can be overwritten*\/ */
2911: /* doldm=dnewm; /\* doldm is now Px * diag [1/(w_1p1i+w_2 p2i)] *\/ */
2912: /* dnewm=dsavm; /\* doldm is now Px * diag [1/(w_1p1i+w_2 p2i)] *\/ */
2913: /* left Product of this matrix by diag matrix of prevalences (savm) */
2914: for (j=1;j<=nlstate+ndeath;j++){
2915: for (ii=1;ii<=nlstate+ndeath;ii++){
2916: dsavm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij] : 0.0);
2917: }
2918: } /* End j, At the end oldm is diag[1/(w_1p1i+w_2 p2i)] */
2919: ps=matprod2(doldm, dsavm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dnewm); /* Bug Valgrind */
2920: /* newm or out is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
2921: /* end bmij */
2922: return ps;
1.218 brouard 2923: }
1.217 brouard 2924: /*************** transition probabilities ***************/
2925:
1.218 brouard 2926: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 2927: {
2928: /* According to parameters values stored in x and the covariate's values stored in cov,
2929: computes the probability to be observed in state j being in state i by appying the
2930: model to the ncovmodel covariates (including constant and age).
2931: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2932: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2933: ncth covariate in the global vector x is given by the formula:
2934: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2935: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2936: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2937: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
2938: Outputs ps[i][j] the probability to be observed in j being in j according to
2939: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
2940: */
2941: double s1, lnpijopii;
2942: /*double t34;*/
2943: int i,j, nc, ii, jj;
2944:
1.234 brouard 2945: for(i=1; i<= nlstate; i++){
2946: for(j=1; j<i;j++){
2947: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2948: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2949: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2950: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2951: }
2952: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2953: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2954: }
2955: for(j=i+1; j<=nlstate+ndeath;j++){
2956: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2957: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2958: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2959: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2960: }
2961: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2962: }
2963: }
2964:
2965: for(i=1; i<= nlstate; i++){
2966: s1=0;
2967: for(j=1; j<i; j++){
2968: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2969: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2970: }
2971: for(j=i+1; j<=nlstate+ndeath; j++){
2972: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2973: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2974: }
2975: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2976: ps[i][i]=1./(s1+1.);
2977: /* Computing other pijs */
2978: for(j=1; j<i; j++)
2979: ps[i][j]= exp(ps[i][j])*ps[i][i];
2980: for(j=i+1; j<=nlstate+ndeath; j++)
2981: ps[i][j]= exp(ps[i][j])*ps[i][i];
2982: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2983: } /* end i */
2984:
2985: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2986: for(jj=1; jj<= nlstate+ndeath; jj++){
2987: ps[ii][jj]=0;
2988: ps[ii][ii]=1;
2989: }
2990: }
2991: /* Added for backcast */ /* Transposed matrix too */
2992: for(jj=1; jj<= nlstate+ndeath; jj++){
2993: s1=0.;
2994: for(ii=1; ii<= nlstate+ndeath; ii++){
2995: s1+=ps[ii][jj];
2996: }
2997: for(ii=1; ii<= nlstate; ii++){
2998: ps[ii][jj]=ps[ii][jj]/s1;
2999: }
3000: }
3001: /* Transposition */
3002: for(jj=1; jj<= nlstate+ndeath; jj++){
3003: for(ii=jj; ii<= nlstate+ndeath; ii++){
3004: s1=ps[ii][jj];
3005: ps[ii][jj]=ps[jj][ii];
3006: ps[jj][ii]=s1;
3007: }
3008: }
3009: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3010: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3011: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3012: /* } */
3013: /* printf("\n "); */
3014: /* } */
3015: /* printf("\n ");printf("%lf ",cov[2]);*/
3016: /*
3017: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3018: goto end;*/
3019: return ps;
1.217 brouard 3020: }
3021:
3022:
1.126 brouard 3023: /**************** Product of 2 matrices ******************/
3024:
1.145 brouard 3025: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3026: {
3027: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3028: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3029: /* in, b, out are matrice of pointers which should have been initialized
3030: before: only the contents of out is modified. The function returns
3031: a pointer to pointers identical to out */
1.145 brouard 3032: int i, j, k;
1.126 brouard 3033: for(i=nrl; i<= nrh; i++)
1.145 brouard 3034: for(k=ncolol; k<=ncoloh; k++){
3035: out[i][k]=0.;
3036: for(j=ncl; j<=nch; j++)
3037: out[i][k] +=in[i][j]*b[j][k];
3038: }
1.126 brouard 3039: return out;
3040: }
3041:
3042:
3043: /************* Higher Matrix Product ***************/
3044:
1.235 brouard 3045: 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 3046: {
1.218 brouard 3047: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3048: 'nhstepm*hstepm*stepm' months (i.e. until
3049: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3050: nhstepm*hstepm matrices.
3051: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3052: (typically every 2 years instead of every month which is too big
3053: for the memory).
3054: Model is determined by parameters x and covariates have to be
3055: included manually here.
3056:
3057: */
3058:
3059: int i, j, d, h, k;
1.131 brouard 3060: double **out, cov[NCOVMAX+1];
1.126 brouard 3061: double **newm;
1.187 brouard 3062: double agexact;
1.214 brouard 3063: double agebegin, ageend;
1.126 brouard 3064:
3065: /* Hstepm could be zero and should return the unit matrix */
3066: for (i=1;i<=nlstate+ndeath;i++)
3067: for (j=1;j<=nlstate+ndeath;j++){
3068: oldm[i][j]=(i==j ? 1.0 : 0.0);
3069: po[i][j][0]=(i==j ? 1.0 : 0.0);
3070: }
3071: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3072: for(h=1; h <=nhstepm; h++){
3073: for(d=1; d <=hstepm; d++){
3074: newm=savm;
3075: /* Covariates have to be included here again */
3076: cov[1]=1.;
1.214 brouard 3077: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3078: cov[2]=agexact;
3079: if(nagesqr==1)
1.227 brouard 3080: cov[3]= agexact*agexact;
1.235 brouard 3081: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3082: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3083: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3084: /* 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)); */
3085: }
3086: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3087: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3088: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3089: /* 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]); */
3090: }
3091: for (k=1; k<=cptcovage;k++){
3092: if(Dummy[Tvar[Tage[k]]]){
3093: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3094: } else{
3095: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3096: }
3097: /* 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]); */
3098: }
3099: for (k=1; k<=cptcovprod;k++){ /* */
3100: /* 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]); */
3101: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3102: }
3103: /* for (k=1; k<=cptcovn;k++) */
3104: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3105: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3106: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3107: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3108: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3109:
3110:
1.126 brouard 3111: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3112: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3113: /* right multiplication of oldm by the current matrix */
1.126 brouard 3114: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3115: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3116: /* if((int)age == 70){ */
3117: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3118: /* for(i=1; i<=nlstate+ndeath; i++) { */
3119: /* printf("%d pmmij ",i); */
3120: /* for(j=1;j<=nlstate+ndeath;j++) { */
3121: /* printf("%f ",pmmij[i][j]); */
3122: /* } */
3123: /* printf(" oldm "); */
3124: /* for(j=1;j<=nlstate+ndeath;j++) { */
3125: /* printf("%f ",oldm[i][j]); */
3126: /* } */
3127: /* printf("\n"); */
3128: /* } */
3129: /* } */
1.126 brouard 3130: savm=oldm;
3131: oldm=newm;
3132: }
3133: for(i=1; i<=nlstate+ndeath; i++)
3134: for(j=1;j<=nlstate+ndeath;j++) {
1.218 brouard 3135: po[i][j][h]=newm[i][j];
3136: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3137: }
1.128 brouard 3138: /*printf("h=%d ",h);*/
1.126 brouard 3139: } /* end h */
1.218 brouard 3140: /* printf("\n H=%d \n",h); */
1.126 brouard 3141: return po;
3142: }
3143:
1.217 brouard 3144: /************* Higher Back Matrix Product ***************/
1.218 brouard 3145: /* 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 ) */
1.222 brouard 3146: double ***hbxij(double ***po, int nhstepm, double age, int hstepm, double *x, double ***prevacurrent, int nlstate, int stepm, int ij )
1.217 brouard 3147: {
1.218 brouard 3148: /* Computes the transition matrix starting at age 'age' over
1.217 brouard 3149: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3150: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3151: nhstepm*hstepm matrices.
3152: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3153: (typically every 2 years instead of every month which is too big
1.217 brouard 3154: for the memory).
1.218 brouard 3155: Model is determined by parameters x and covariates have to be
3156: included manually here.
1.217 brouard 3157:
1.222 brouard 3158: */
1.217 brouard 3159:
3160: int i, j, d, h, k;
3161: double **out, cov[NCOVMAX+1];
3162: double **newm;
3163: double agexact;
3164: double agebegin, ageend;
1.222 brouard 3165: double **oldm, **savm;
1.217 brouard 3166:
1.222 brouard 3167: oldm=oldms;savm=savms;
1.217 brouard 3168: /* Hstepm could be zero and should return the unit matrix */
3169: for (i=1;i<=nlstate+ndeath;i++)
3170: for (j=1;j<=nlstate+ndeath;j++){
3171: oldm[i][j]=(i==j ? 1.0 : 0.0);
3172: po[i][j][0]=(i==j ? 1.0 : 0.0);
3173: }
3174: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3175: for(h=1; h <=nhstepm; h++){
3176: for(d=1; d <=hstepm; d++){
3177: newm=savm;
3178: /* Covariates have to be included here again */
3179: cov[1]=1.;
3180: agexact=age-((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
3181: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3182: cov[2]=agexact;
3183: if(nagesqr==1)
1.222 brouard 3184: cov[3]= agexact*agexact;
1.218 brouard 3185: for (k=1; k<=cptcovn;k++)
1.222 brouard 3186: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)];
3187: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.217 brouard 3188: for (k=1; k<=cptcovage;k++) /* Should start at cptcovn+1 */
1.222 brouard 3189: /* cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
3190: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3191: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
1.217 brouard 3192: for (k=1; k<=cptcovprod;k++) /* Useless because included in cptcovn */
1.222 brouard 3193: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
3194: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
1.218 brouard 3195:
3196:
1.217 brouard 3197: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3198: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3199: /* Careful transposed matrix */
1.222 brouard 3200: /* age is in cov[2] */
1.218 brouard 3201: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3202: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3203: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3204: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3205: /* if((int)age == 70){ */
3206: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3207: /* for(i=1; i<=nlstate+ndeath; i++) { */
3208: /* printf("%d pmmij ",i); */
3209: /* for(j=1;j<=nlstate+ndeath;j++) { */
3210: /* printf("%f ",pmmij[i][j]); */
3211: /* } */
3212: /* printf(" oldm "); */
3213: /* for(j=1;j<=nlstate+ndeath;j++) { */
3214: /* printf("%f ",oldm[i][j]); */
3215: /* } */
3216: /* printf("\n"); */
3217: /* } */
3218: /* } */
3219: savm=oldm;
3220: oldm=newm;
3221: }
3222: for(i=1; i<=nlstate+ndeath; i++)
3223: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3224: po[i][j][h]=newm[i][j];
3225: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.217 brouard 3226: }
3227: /*printf("h=%d ",h);*/
3228: } /* end h */
1.222 brouard 3229: /* printf("\n H=%d \n",h); */
1.217 brouard 3230: return po;
3231: }
3232:
3233:
1.162 brouard 3234: #ifdef NLOPT
3235: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3236: double fret;
3237: double *xt;
3238: int j;
3239: myfunc_data *d2 = (myfunc_data *) pd;
3240: /* xt = (p1-1); */
3241: xt=vector(1,n);
3242: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3243:
3244: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3245: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3246: printf("Function = %.12lf ",fret);
3247: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3248: printf("\n");
3249: free_vector(xt,1,n);
3250: return fret;
3251: }
3252: #endif
1.126 brouard 3253:
3254: /*************** log-likelihood *************/
3255: double func( double *x)
3256: {
1.226 brouard 3257: int i, ii, j, k, mi, d, kk;
3258: int ioffset=0;
3259: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3260: double **out;
3261: double lli; /* Individual log likelihood */
3262: int s1, s2;
1.228 brouard 3263: 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 3264: double bbh, survp;
3265: long ipmx;
3266: double agexact;
3267: /*extern weight */
3268: /* We are differentiating ll according to initial status */
3269: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3270: /*for(i=1;i<imx;i++)
3271: printf(" %d\n",s[4][i]);
3272: */
1.162 brouard 3273:
1.226 brouard 3274: ++countcallfunc;
1.162 brouard 3275:
1.226 brouard 3276: cov[1]=1.;
1.126 brouard 3277:
1.226 brouard 3278: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3279: ioffset=0;
1.226 brouard 3280: if(mle==1){
3281: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3282: /* Computes the values of the ncovmodel covariates of the model
3283: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3284: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3285: to be observed in j being in i according to the model.
3286: */
1.243 brouard 3287: ioffset=2+nagesqr ;
1.233 brouard 3288: /* Fixed */
1.234 brouard 3289: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3290: 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)*/
3291: }
1.226 brouard 3292: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3293: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3294: has been calculated etc */
3295: /* For an individual i, wav[i] gives the number of effective waves */
3296: /* We compute the contribution to Likelihood of each effective transition
3297: mw[mi][i] is real wave of the mi th effectve wave */
3298: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3299: s2=s[mw[mi+1][i]][i];
3300: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3301: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3302: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3303: */
3304: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3305: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3306: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3307: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3308: }
3309: for (ii=1;ii<=nlstate+ndeath;ii++)
3310: for (j=1;j<=nlstate+ndeath;j++){
3311: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3312: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3313: }
3314: for(d=0; d<dh[mi][i]; d++){
3315: newm=savm;
3316: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3317: cov[2]=agexact;
3318: if(nagesqr==1)
3319: cov[3]= agexact*agexact; /* Should be changed here */
3320: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3321: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3322: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3323: else
3324: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3325: }
3326: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3327: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3328: savm=oldm;
3329: oldm=newm;
3330: } /* end mult */
3331:
3332: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3333: /* But now since version 0.9 we anticipate for bias at large stepm.
3334: * If stepm is larger than one month (smallest stepm) and if the exact delay
3335: * (in months) between two waves is not a multiple of stepm, we rounded to
3336: * the nearest (and in case of equal distance, to the lowest) interval but now
3337: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3338: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3339: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3340: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3341: * -stepm/2 to stepm/2 .
3342: * For stepm=1 the results are the same as for previous versions of Imach.
3343: * For stepm > 1 the results are less biased than in previous versions.
3344: */
1.234 brouard 3345: s1=s[mw[mi][i]][i];
3346: s2=s[mw[mi+1][i]][i];
3347: bbh=(double)bh[mi][i]/(double)stepm;
3348: /* bias bh is positive if real duration
3349: * is higher than the multiple of stepm and negative otherwise.
3350: */
3351: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3352: if( s2 > nlstate){
3353: /* i.e. if s2 is a death state and if the date of death is known
3354: then the contribution to the likelihood is the probability to
3355: die between last step unit time and current step unit time,
3356: which is also equal to probability to die before dh
3357: minus probability to die before dh-stepm .
3358: In version up to 0.92 likelihood was computed
3359: as if date of death was unknown. Death was treated as any other
3360: health state: the date of the interview describes the actual state
3361: and not the date of a change in health state. The former idea was
3362: to consider that at each interview the state was recorded
3363: (healthy, disable or death) and IMaCh was corrected; but when we
3364: introduced the exact date of death then we should have modified
3365: the contribution of an exact death to the likelihood. This new
3366: contribution is smaller and very dependent of the step unit
3367: stepm. It is no more the probability to die between last interview
3368: and month of death but the probability to survive from last
3369: interview up to one month before death multiplied by the
3370: probability to die within a month. Thanks to Chris
3371: Jackson for correcting this bug. Former versions increased
3372: mortality artificially. The bad side is that we add another loop
3373: which slows down the processing. The difference can be up to 10%
3374: lower mortality.
3375: */
3376: /* If, at the beginning of the maximization mostly, the
3377: cumulative probability or probability to be dead is
3378: constant (ie = 1) over time d, the difference is equal to
3379: 0. out[s1][3] = savm[s1][3]: probability, being at state
3380: s1 at precedent wave, to be dead a month before current
3381: wave is equal to probability, being at state s1 at
3382: precedent wave, to be dead at mont of the current
3383: wave. Then the observed probability (that this person died)
3384: is null according to current estimated parameter. In fact,
3385: it should be very low but not zero otherwise the log go to
3386: infinity.
3387: */
1.183 brouard 3388: /* #ifdef INFINITYORIGINAL */
3389: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3390: /* #else */
3391: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3392: /* lli=log(mytinydouble); */
3393: /* else */
3394: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3395: /* #endif */
1.226 brouard 3396: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3397:
1.226 brouard 3398: } else if ( s2==-1 ) { /* alive */
3399: for (j=1,survp=0. ; j<=nlstate; j++)
3400: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3401: /*survp += out[s1][j]; */
3402: lli= log(survp);
3403: }
3404: else if (s2==-4) {
3405: for (j=3,survp=0. ; j<=nlstate; j++)
3406: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3407: lli= log(survp);
3408: }
3409: else if (s2==-5) {
3410: for (j=1,survp=0. ; j<=2; j++)
3411: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3412: lli= log(survp);
3413: }
3414: else{
3415: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3416: /* 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 */
3417: }
3418: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3419: /*if(lli ==000.0)*/
3420: /*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); */
3421: ipmx +=1;
3422: sw += weight[i];
3423: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3424: /* if (lli < log(mytinydouble)){ */
3425: /* 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); */
3426: /* 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]); */
3427: /* } */
3428: } /* end of wave */
3429: } /* end of individual */
3430: } else if(mle==2){
3431: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3432: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3433: for(mi=1; mi<= wav[i]-1; mi++){
3434: for (ii=1;ii<=nlstate+ndeath;ii++)
3435: for (j=1;j<=nlstate+ndeath;j++){
3436: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3437: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3438: }
3439: for(d=0; d<=dh[mi][i]; d++){
3440: newm=savm;
3441: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3442: cov[2]=agexact;
3443: if(nagesqr==1)
3444: cov[3]= agexact*agexact;
3445: for (kk=1; kk<=cptcovage;kk++) {
3446: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3447: }
3448: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3449: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3450: savm=oldm;
3451: oldm=newm;
3452: } /* end mult */
3453:
3454: s1=s[mw[mi][i]][i];
3455: s2=s[mw[mi+1][i]][i];
3456: bbh=(double)bh[mi][i]/(double)stepm;
3457: 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 */
3458: ipmx +=1;
3459: sw += weight[i];
3460: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3461: } /* end of wave */
3462: } /* end of individual */
3463: } else if(mle==3){ /* exponential inter-extrapolation */
3464: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3465: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3466: for(mi=1; mi<= wav[i]-1; mi++){
3467: for (ii=1;ii<=nlstate+ndeath;ii++)
3468: for (j=1;j<=nlstate+ndeath;j++){
3469: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3470: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3471: }
3472: for(d=0; d<dh[mi][i]; d++){
3473: newm=savm;
3474: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3475: cov[2]=agexact;
3476: if(nagesqr==1)
3477: cov[3]= agexact*agexact;
3478: for (kk=1; kk<=cptcovage;kk++) {
3479: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3480: }
3481: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3482: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3483: savm=oldm;
3484: oldm=newm;
3485: } /* end mult */
3486:
3487: s1=s[mw[mi][i]][i];
3488: s2=s[mw[mi+1][i]][i];
3489: bbh=(double)bh[mi][i]/(double)stepm;
3490: 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 */
3491: ipmx +=1;
3492: sw += weight[i];
3493: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3494: } /* end of wave */
3495: } /* end of individual */
3496: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3497: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3498: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3499: for(mi=1; mi<= wav[i]-1; mi++){
3500: for (ii=1;ii<=nlstate+ndeath;ii++)
3501: for (j=1;j<=nlstate+ndeath;j++){
3502: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3503: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3504: }
3505: for(d=0; d<dh[mi][i]; d++){
3506: newm=savm;
3507: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3508: cov[2]=agexact;
3509: if(nagesqr==1)
3510: cov[3]= agexact*agexact;
3511: for (kk=1; kk<=cptcovage;kk++) {
3512: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3513: }
1.126 brouard 3514:
1.226 brouard 3515: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3516: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3517: savm=oldm;
3518: oldm=newm;
3519: } /* end mult */
3520:
3521: s1=s[mw[mi][i]][i];
3522: s2=s[mw[mi+1][i]][i];
3523: if( s2 > nlstate){
3524: lli=log(out[s1][s2] - savm[s1][s2]);
3525: } else if ( s2==-1 ) { /* alive */
3526: for (j=1,survp=0. ; j<=nlstate; j++)
3527: survp += out[s1][j];
3528: lli= log(survp);
3529: }else{
3530: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3531: }
3532: ipmx +=1;
3533: sw += weight[i];
3534: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3535: /* 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 3536: } /* end of wave */
3537: } /* end of individual */
3538: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3539: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3540: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3541: for(mi=1; mi<= wav[i]-1; mi++){
3542: for (ii=1;ii<=nlstate+ndeath;ii++)
3543: for (j=1;j<=nlstate+ndeath;j++){
3544: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3545: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3546: }
3547: for(d=0; d<dh[mi][i]; d++){
3548: newm=savm;
3549: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3550: cov[2]=agexact;
3551: if(nagesqr==1)
3552: cov[3]= agexact*agexact;
3553: for (kk=1; kk<=cptcovage;kk++) {
3554: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3555: }
1.126 brouard 3556:
1.226 brouard 3557: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3558: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3559: savm=oldm;
3560: oldm=newm;
3561: } /* end mult */
3562:
3563: s1=s[mw[mi][i]][i];
3564: s2=s[mw[mi+1][i]][i];
3565: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3566: ipmx +=1;
3567: sw += weight[i];
3568: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3569: /*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]);*/
3570: } /* end of wave */
3571: } /* end of individual */
3572: } /* End of if */
3573: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3574: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3575: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3576: return -l;
1.126 brouard 3577: }
3578:
3579: /*************** log-likelihood *************/
3580: double funcone( double *x)
3581: {
1.228 brouard 3582: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3583: int i, ii, j, k, mi, d, kk;
1.228 brouard 3584: int ioffset=0;
1.131 brouard 3585: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3586: double **out;
3587: double lli; /* Individual log likelihood */
3588: double llt;
3589: int s1, s2;
1.228 brouard 3590: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3591:
1.126 brouard 3592: double bbh, survp;
1.187 brouard 3593: double agexact;
1.214 brouard 3594: double agebegin, ageend;
1.126 brouard 3595: /*extern weight */
3596: /* We are differentiating ll according to initial status */
3597: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3598: /*for(i=1;i<imx;i++)
3599: printf(" %d\n",s[4][i]);
3600: */
3601: cov[1]=1.;
3602:
3603: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3604: ioffset=0;
3605: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3606: /* ioffset=2+nagesqr+cptcovage; */
3607: ioffset=2+nagesqr;
1.232 brouard 3608: /* Fixed */
1.224 brouard 3609: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3610: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3611: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3612: 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)*/
3613: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3614: /* cov[2+6]=covar[Tvar[6]][i]; */
3615: /* cov[2+6]=covar[2][i]; V2 */
3616: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3617: /* cov[2+7]=covar[Tvar[7]][i]; */
3618: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3619: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3620: /* cov[2+9]=covar[Tvar[9]][i]; */
3621: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3622: }
1.232 brouard 3623: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3624: /* 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?)*\/ */
3625: /* } */
1.231 brouard 3626: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3627: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3628: /* } */
1.225 brouard 3629:
1.233 brouard 3630:
3631: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3632: /* Wave varying (but not age varying) */
3633: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3634: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3635: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3636: }
1.232 brouard 3637: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3638: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3639: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3640: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3641: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3642: /* 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 3643: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3644: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3645: /* /\* 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]); *\/ */
3646: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3647: /* } */
1.126 brouard 3648: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3649: for (j=1;j<=nlstate+ndeath;j++){
3650: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3651: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3652: }
1.214 brouard 3653:
3654: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3655: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3656: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3657: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3658: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3659: and mw[mi+1][i]. dh depends on stepm.*/
3660: newm=savm;
1.247 brouard 3661: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3662: cov[2]=agexact;
3663: if(nagesqr==1)
3664: cov[3]= agexact*agexact;
3665: for (kk=1; kk<=cptcovage;kk++) {
3666: if(!FixedV[Tvar[Tage[kk]]])
3667: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3668: else
3669: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3670: }
3671: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3672: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3673: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3674: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3675: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3676: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3677: savm=oldm;
3678: oldm=newm;
1.126 brouard 3679: } /* end mult */
3680:
3681: s1=s[mw[mi][i]][i];
3682: s2=s[mw[mi+1][i]][i];
1.217 brouard 3683: /* if(s2==-1){ */
3684: /* printf(" s1=%d, s2=%d i=%d \n", s1, s2, i); */
3685: /* /\* exit(1); *\/ */
3686: /* } */
1.126 brouard 3687: bbh=(double)bh[mi][i]/(double)stepm;
3688: /* bias is positive if real duration
3689: * is higher than the multiple of stepm and negative otherwise.
3690: */
3691: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3692: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3693: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3694: for (j=1,survp=0. ; j<=nlstate; j++)
3695: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3696: lli= log(survp);
1.126 brouard 3697: }else if (mle==1){
1.242 brouard 3698: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3699: } else if(mle==2){
1.242 brouard 3700: 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 3701: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3702: 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 3703: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3704: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3705: } else{ /* mle=0 back to 1 */
1.242 brouard 3706: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3707: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3708: } /* End of if */
3709: ipmx +=1;
3710: sw += weight[i];
3711: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3712: /*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 3713: if(globpr){
1.246 brouard 3714: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3715: %11.6f %11.6f %11.6f ", \
1.242 brouard 3716: num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw,
3717: 2*weight[i]*lli,out[s1][s2],savm[s1][s2]);
3718: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3719: llt +=ll[k]*gipmx/gsw;
3720: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3721: }
3722: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3723: }
1.232 brouard 3724: } /* end of wave */
3725: } /* end of individual */
3726: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3727: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3728: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3729: if(globpr==0){ /* First time we count the contributions and weights */
3730: gipmx=ipmx;
3731: gsw=sw;
3732: }
3733: return -l;
1.126 brouard 3734: }
3735:
3736:
3737: /*************** function likelione ***********/
3738: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*funcone)(double []))
3739: {
3740: /* This routine should help understanding what is done with
3741: the selection of individuals/waves and
3742: to check the exact contribution to the likelihood.
3743: Plotting could be done.
3744: */
3745: int k;
3746:
3747: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3748: strcpy(fileresilk,"ILK_");
1.202 brouard 3749: strcat(fileresilk,fileresu);
1.126 brouard 3750: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3751: printf("Problem with resultfile: %s\n", fileresilk);
3752: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3753: }
1.214 brouard 3754: 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");
3755: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3756: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3757: for(k=1; k<=nlstate; k++)
3758: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3759: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3760: }
3761:
3762: *fretone=(*funcone)(p);
3763: if(*globpri !=0){
3764: fclose(ficresilk);
1.205 brouard 3765: if (mle ==0)
3766: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3767: else if(mle >=1)
3768: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3769: 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));
1.207 brouard 3770:
1.208 brouard 3771:
3772: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3773: 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 3774: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3775: }
1.207 brouard 3776: 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 3777: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3778: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3779: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3780: fflush(fichtm);
1.205 brouard 3781: }
1.126 brouard 3782: return;
3783: }
3784:
3785:
3786: /*********** Maximum Likelihood Estimation ***************/
3787:
3788: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3789: {
1.165 brouard 3790: int i,j, iter=0;
1.126 brouard 3791: double **xi;
3792: double fret;
3793: double fretone; /* Only one call to likelihood */
3794: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3795:
3796: #ifdef NLOPT
3797: int creturn;
3798: nlopt_opt opt;
3799: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3800: double *lb;
3801: double minf; /* the minimum objective value, upon return */
3802: double * p1; /* Shifted parameters from 0 instead of 1 */
3803: myfunc_data dinst, *d = &dinst;
3804: #endif
3805:
3806:
1.126 brouard 3807: xi=matrix(1,npar,1,npar);
3808: for (i=1;i<=npar;i++)
3809: for (j=1;j<=npar;j++)
3810: xi[i][j]=(i==j ? 1.0 : 0.0);
3811: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3812: strcpy(filerespow,"POW_");
1.126 brouard 3813: strcat(filerespow,fileres);
3814: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3815: printf("Problem with resultfile: %s\n", filerespow);
3816: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3817: }
3818: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3819: for (i=1;i<=nlstate;i++)
3820: for(j=1;j<=nlstate+ndeath;j++)
3821: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3822: fprintf(ficrespow,"\n");
1.162 brouard 3823: #ifdef POWELL
1.126 brouard 3824: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3825: #endif
1.126 brouard 3826:
1.162 brouard 3827: #ifdef NLOPT
3828: #ifdef NEWUOA
3829: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
3830: #else
3831: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
3832: #endif
3833: lb=vector(0,npar-1);
3834: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
3835: nlopt_set_lower_bounds(opt, lb);
3836: nlopt_set_initial_step1(opt, 0.1);
3837:
3838: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
3839: d->function = func;
3840: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
3841: nlopt_set_min_objective(opt, myfunc, d);
3842: nlopt_set_xtol_rel(opt, ftol);
3843: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
3844: printf("nlopt failed! %d\n",creturn);
3845: }
3846: else {
3847: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
3848: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
3849: iter=1; /* not equal */
3850: }
3851: nlopt_destroy(opt);
3852: #endif
1.126 brouard 3853: free_matrix(xi,1,npar,1,npar);
3854: fclose(ficrespow);
1.203 brouard 3855: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
3856: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 3857: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 3858:
3859: }
3860:
3861: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 3862: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 3863: {
3864: double **a,**y,*x,pd;
1.203 brouard 3865: /* double **hess; */
1.164 brouard 3866: int i, j;
1.126 brouard 3867: int *indx;
3868:
3869: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 3870: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 3871: void lubksb(double **a, int npar, int *indx, double b[]) ;
3872: void ludcmp(double **a, int npar, int *indx, double *d) ;
3873: double gompertz(double p[]);
1.203 brouard 3874: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 3875:
3876: printf("\nCalculation of the hessian matrix. Wait...\n");
3877: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
3878: for (i=1;i<=npar;i++){
1.203 brouard 3879: printf("%d-",i);fflush(stdout);
3880: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 3881:
3882: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
3883:
3884: /* printf(" %f ",p[i]);
3885: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
3886: }
3887:
3888: for (i=1;i<=npar;i++) {
3889: for (j=1;j<=npar;j++) {
3890: if (j>i) {
1.203 brouard 3891: printf(".%d-%d",i,j);fflush(stdout);
3892: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
3893: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 3894:
3895: hess[j][i]=hess[i][j];
3896: /*printf(" %lf ",hess[i][j]);*/
3897: }
3898: }
3899: }
3900: printf("\n");
3901: fprintf(ficlog,"\n");
3902:
3903: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
3904: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
3905:
3906: a=matrix(1,npar,1,npar);
3907: y=matrix(1,npar,1,npar);
3908: x=vector(1,npar);
3909: indx=ivector(1,npar);
3910: for (i=1;i<=npar;i++)
3911: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
3912: ludcmp(a,npar,indx,&pd);
3913:
3914: for (j=1;j<=npar;j++) {
3915: for (i=1;i<=npar;i++) x[i]=0;
3916: x[j]=1;
3917: lubksb(a,npar,indx,x);
3918: for (i=1;i<=npar;i++){
3919: matcov[i][j]=x[i];
3920: }
3921: }
3922:
3923: printf("\n#Hessian matrix#\n");
3924: fprintf(ficlog,"\n#Hessian matrix#\n");
3925: for (i=1;i<=npar;i++) {
3926: for (j=1;j<=npar;j++) {
1.203 brouard 3927: printf("%.6e ",hess[i][j]);
3928: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 3929: }
3930: printf("\n");
3931: fprintf(ficlog,"\n");
3932: }
3933:
1.203 brouard 3934: /* printf("\n#Covariance matrix#\n"); */
3935: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
3936: /* for (i=1;i<=npar;i++) { */
3937: /* for (j=1;j<=npar;j++) { */
3938: /* printf("%.6e ",matcov[i][j]); */
3939: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
3940: /* } */
3941: /* printf("\n"); */
3942: /* fprintf(ficlog,"\n"); */
3943: /* } */
3944:
1.126 brouard 3945: /* Recompute Inverse */
1.203 brouard 3946: /* for (i=1;i<=npar;i++) */
3947: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
3948: /* ludcmp(a,npar,indx,&pd); */
3949:
3950: /* printf("\n#Hessian matrix recomputed#\n"); */
3951:
3952: /* for (j=1;j<=npar;j++) { */
3953: /* for (i=1;i<=npar;i++) x[i]=0; */
3954: /* x[j]=1; */
3955: /* lubksb(a,npar,indx,x); */
3956: /* for (i=1;i<=npar;i++){ */
3957: /* y[i][j]=x[i]; */
3958: /* printf("%.3e ",y[i][j]); */
3959: /* fprintf(ficlog,"%.3e ",y[i][j]); */
3960: /* } */
3961: /* printf("\n"); */
3962: /* fprintf(ficlog,"\n"); */
3963: /* } */
3964:
3965: /* Verifying the inverse matrix */
3966: #ifdef DEBUGHESS
3967: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 3968:
1.203 brouard 3969: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
3970: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 3971:
3972: for (j=1;j<=npar;j++) {
3973: for (i=1;i<=npar;i++){
1.203 brouard 3974: printf("%.2f ",y[i][j]);
3975: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 3976: }
3977: printf("\n");
3978: fprintf(ficlog,"\n");
3979: }
1.203 brouard 3980: #endif
1.126 brouard 3981:
3982: free_matrix(a,1,npar,1,npar);
3983: free_matrix(y,1,npar,1,npar);
3984: free_vector(x,1,npar);
3985: free_ivector(indx,1,npar);
1.203 brouard 3986: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 3987:
3988:
3989: }
3990:
3991: /*************** hessian matrix ****************/
3992: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 3993: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 3994: int i;
3995: int l=1, lmax=20;
1.203 brouard 3996: double k1,k2, res, fx;
1.132 brouard 3997: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 3998: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
3999: int k=0,kmax=10;
4000: double l1;
4001:
4002: fx=func(x);
4003: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4004: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4005: l1=pow(10,l);
4006: delts=delt;
4007: for(k=1 ; k <kmax; k=k+1){
4008: delt = delta*(l1*k);
4009: p2[theta]=x[theta] +delt;
1.145 brouard 4010: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4011: p2[theta]=x[theta]-delt;
4012: k2=func(p2)-fx;
4013: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4014: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4015:
1.203 brouard 4016: #ifdef DEBUGHESSII
1.126 brouard 4017: 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);
4018: 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);
4019: #endif
4020: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4021: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4022: k=kmax;
4023: }
4024: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4025: k=kmax; l=lmax*10;
1.126 brouard 4026: }
4027: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4028: delts=delt;
4029: }
1.203 brouard 4030: } /* End loop k */
1.126 brouard 4031: }
4032: delti[theta]=delts;
4033: return res;
4034:
4035: }
4036:
1.203 brouard 4037: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4038: {
4039: int i;
1.164 brouard 4040: int l=1, lmax=20;
1.126 brouard 4041: double k1,k2,k3,k4,res,fx;
1.132 brouard 4042: double p2[MAXPARM+1];
1.203 brouard 4043: int k, kmax=1;
4044: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4045:
4046: int firstime=0;
1.203 brouard 4047:
1.126 brouard 4048: fx=func(x);
1.203 brouard 4049: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4050: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4051: p2[thetai]=x[thetai]+delti[thetai]*k;
4052: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4053: k1=func(p2)-fx;
4054:
1.203 brouard 4055: p2[thetai]=x[thetai]+delti[thetai]*k;
4056: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4057: k2=func(p2)-fx;
4058:
1.203 brouard 4059: p2[thetai]=x[thetai]-delti[thetai]*k;
4060: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4061: k3=func(p2)-fx;
4062:
1.203 brouard 4063: p2[thetai]=x[thetai]-delti[thetai]*k;
4064: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4065: k4=func(p2)-fx;
1.203 brouard 4066: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4067: if(k1*k2*k3*k4 <0.){
1.208 brouard 4068: firstime=1;
1.203 brouard 4069: kmax=kmax+10;
1.208 brouard 4070: }
4071: if(kmax >=10 || firstime ==1){
1.246 brouard 4072: 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);
4073: 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 4074: 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);
4075: 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);
4076: }
4077: #ifdef DEBUGHESSIJ
4078: v1=hess[thetai][thetai];
4079: v2=hess[thetaj][thetaj];
4080: cv12=res;
4081: /* Computing eigen value of Hessian matrix */
4082: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4083: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4084: if ((lc2 <0) || (lc1 <0) ){
4085: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4086: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4087: 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);
4088: 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);
4089: }
1.126 brouard 4090: #endif
4091: }
4092: return res;
4093: }
4094:
1.203 brouard 4095: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4096: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4097: /* { */
4098: /* int i; */
4099: /* int l=1, lmax=20; */
4100: /* double k1,k2,k3,k4,res,fx; */
4101: /* double p2[MAXPARM+1]; */
4102: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4103: /* int k=0,kmax=10; */
4104: /* double l1; */
4105:
4106: /* fx=func(x); */
4107: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4108: /* l1=pow(10,l); */
4109: /* delts=delt; */
4110: /* for(k=1 ; k <kmax; k=k+1){ */
4111: /* delt = delti*(l1*k); */
4112: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4113: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4114: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4115: /* k1=func(p2)-fx; */
4116:
4117: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4118: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4119: /* k2=func(p2)-fx; */
4120:
4121: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4122: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4123: /* k3=func(p2)-fx; */
4124:
4125: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4126: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4127: /* k4=func(p2)-fx; */
4128: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4129: /* #ifdef DEBUGHESSIJ */
4130: /* 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); */
4131: /* 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); */
4132: /* #endif */
4133: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4134: /* k=kmax; */
4135: /* } */
4136: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4137: /* k=kmax; l=lmax*10; */
4138: /* } */
4139: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4140: /* delts=delt; */
4141: /* } */
4142: /* } /\* End loop k *\/ */
4143: /* } */
4144: /* delti[theta]=delts; */
4145: /* return res; */
4146: /* } */
4147:
4148:
1.126 brouard 4149: /************** Inverse of matrix **************/
4150: void ludcmp(double **a, int n, int *indx, double *d)
4151: {
4152: int i,imax,j,k;
4153: double big,dum,sum,temp;
4154: double *vv;
4155:
4156: vv=vector(1,n);
4157: *d=1.0;
4158: for (i=1;i<=n;i++) {
4159: big=0.0;
4160: for (j=1;j<=n;j++)
4161: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4162: if (big == 0.0){
4163: printf(" Singular Hessian matrix at row %d:\n",i);
4164: for (j=1;j<=n;j++) {
4165: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4166: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4167: }
4168: fflush(ficlog);
4169: fclose(ficlog);
4170: nrerror("Singular matrix in routine ludcmp");
4171: }
1.126 brouard 4172: vv[i]=1.0/big;
4173: }
4174: for (j=1;j<=n;j++) {
4175: for (i=1;i<j;i++) {
4176: sum=a[i][j];
4177: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4178: a[i][j]=sum;
4179: }
4180: big=0.0;
4181: for (i=j;i<=n;i++) {
4182: sum=a[i][j];
4183: for (k=1;k<j;k++)
4184: sum -= a[i][k]*a[k][j];
4185: a[i][j]=sum;
4186: if ( (dum=vv[i]*fabs(sum)) >= big) {
4187: big=dum;
4188: imax=i;
4189: }
4190: }
4191: if (j != imax) {
4192: for (k=1;k<=n;k++) {
4193: dum=a[imax][k];
4194: a[imax][k]=a[j][k];
4195: a[j][k]=dum;
4196: }
4197: *d = -(*d);
4198: vv[imax]=vv[j];
4199: }
4200: indx[j]=imax;
4201: if (a[j][j] == 0.0) a[j][j]=TINY;
4202: if (j != n) {
4203: dum=1.0/(a[j][j]);
4204: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4205: }
4206: }
4207: free_vector(vv,1,n); /* Doesn't work */
4208: ;
4209: }
4210:
4211: void lubksb(double **a, int n, int *indx, double b[])
4212: {
4213: int i,ii=0,ip,j;
4214: double sum;
4215:
4216: for (i=1;i<=n;i++) {
4217: ip=indx[i];
4218: sum=b[ip];
4219: b[ip]=b[i];
4220: if (ii)
4221: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4222: else if (sum) ii=i;
4223: b[i]=sum;
4224: }
4225: for (i=n;i>=1;i--) {
4226: sum=b[i];
4227: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4228: b[i]=sum/a[i][i];
4229: }
4230: }
4231:
4232: void pstamp(FILE *fichier)
4233: {
1.196 brouard 4234: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4235: }
4236:
1.253 brouard 4237: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
4238:
4239: /* y=a+bx regression */
4240: double sumx = 0.0; /* sum of x */
4241: double sumx2 = 0.0; /* sum of x**2 */
4242: double sumxy = 0.0; /* sum of x * y */
4243: double sumy = 0.0; /* sum of y */
4244: double sumy2 = 0.0; /* sum of y**2 */
4245: double sume2; /* sum of square or residuals */
4246: double yhat;
4247:
4248: double denom=0;
4249: int i;
4250: int ne=*no;
4251:
4252: for ( i=ifi, ne=0;i<=ila;i++) {
4253: if(!isfinite(x[i]) || !isfinite(y[i])){
4254: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
4255: continue;
4256: }
4257: ne=ne+1;
4258: sumx += x[i];
4259: sumx2 += x[i]*x[i];
4260: sumxy += x[i] * y[i];
4261: sumy += y[i];
4262: sumy2 += y[i]*y[i];
4263: denom = (ne * sumx2 - sumx*sumx);
4264: /* 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); */
4265: }
4266:
4267: denom = (ne * sumx2 - sumx*sumx);
4268: if (denom == 0) {
4269: // vertical, slope m is infinity
4270: *b = INFINITY;
4271: *a = 0;
4272: if (r) *r = 0;
4273: return 1;
4274: }
4275:
4276: *b = (ne * sumxy - sumx * sumy) / denom;
4277: *a = (sumy * sumx2 - sumx * sumxy) / denom;
4278: if (r!=NULL) {
4279: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
4280: sqrt((sumx2 - sumx*sumx/ne) *
4281: (sumy2 - sumy*sumy/ne));
4282: }
4283: *no=ne;
4284: for ( i=ifi, ne=0;i<=ila;i++) {
4285: if(!isfinite(x[i]) || !isfinite(y[i])){
4286: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
4287: continue;
4288: }
4289: ne=ne+1;
4290: yhat = y[i] - *a -*b* x[i];
4291: sume2 += yhat * yhat ;
4292:
4293: denom = (ne * sumx2 - sumx*sumx);
4294: /* 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); */
4295: }
4296: *sb = sqrt(sume2/(ne-2)/(sumx2 - sumx * sumx /ne));
4297: *sa= *sb * sqrt(sumx2/ne);
4298:
4299: return 0;
4300: }
4301:
1.126 brouard 4302: /************ Frequencies ********************/
1.251 brouard 4303: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4304: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4305: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4306: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4307:
1.253 brouard 4308: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0;
1.226 brouard 4309: int iind=0, iage=0;
4310: int mi; /* Effective wave */
4311: int first;
4312: double ***freq; /* Frequencies */
1.253 brouard 4313: double *x, *y, a,b,r, sa, sb; /* for regression, y=b+m*x and r is the correlation coefficient */
4314: int no;
1.226 brouard 4315: double *meanq;
4316: double **meanqt;
4317: double *pp, **prop, *posprop, *pospropt;
4318: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4319: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4320: double agebegin, ageend;
4321:
4322: pp=vector(1,nlstate);
1.251 brouard 4323: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4324: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4325: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4326: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4327: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
4328: meanqt=matrix(1,lastpass,1,nqtveff);
4329: strcpy(fileresp,"P_");
4330: strcat(fileresp,fileresu);
4331: /*strcat(fileresphtm,fileresu);*/
4332: if((ficresp=fopen(fileresp,"w"))==NULL) {
4333: printf("Problem with prevalence resultfile: %s\n", fileresp);
4334: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4335: exit(0);
4336: }
1.240 brouard 4337:
1.226 brouard 4338: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4339: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4340: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4341: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4342: fflush(ficlog);
4343: exit(70);
4344: }
4345: else{
4346: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4347: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4348: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4349: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4350: }
1.237 brouard 4351: 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 4352:
1.226 brouard 4353: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4354: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4355: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4356: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4357: fflush(ficlog);
4358: exit(70);
1.240 brouard 4359: } else{
1.226 brouard 4360: 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 4361: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4362: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4363: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4364: }
1.240 brouard 4365: 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);
4366:
1.253 brouard 4367: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4368: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4369: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4370: j1=0;
1.126 brouard 4371:
1.227 brouard 4372: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4373: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4374: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4375:
4376:
1.226 brouard 4377: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4378: reference=low_education V1=0,V2=0
4379: med_educ V1=1 V2=0,
4380: high_educ V1=0 V2=1
4381: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4382: */
1.249 brouard 4383: dateintsum=0;
4384: k2cpt=0;
4385:
1.253 brouard 4386: if(cptcoveff == 0 )
4387: nl=1; /* Constant model only */
4388: else
4389: nl=2;
4390: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4391: if(nj==1)
4392: j=0; /* First pass for the constant */
4393: else
4394: j=cptcoveff; /* Other passes for the covariate values */
1.251 brouard 4395: first=1;
4396: for (j1 = 1; j1 <= (int) pow(2,j); j1++){ /* Loop on covariates combination in order of model, excluding quantitatives, V4=0, V3=0 for example, fixed or varying covariates */
4397: posproptt=0.;
4398: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4399: scanf("%d", i);*/
4400: for (i=-5; i<=nlstate+ndeath; i++)
4401: for (jk=-5; jk<=nlstate+ndeath; jk++)
4402: for(m=iagemin; m <= iagemax+3; m++)
4403: freq[i][jk][m]=0;
4404:
4405: for (i=1; i<=nlstate; i++) {
1.240 brouard 4406: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4407: prop[i][m]=0;
4408: posprop[i]=0;
4409: pospropt[i]=0;
4410: }
4411: /* for (z1=1; z1<= nqfveff; z1++) { */
4412: /* meanq[z1]+=0.; */
4413: /* for(m=1;m<=lastpass;m++){ */
4414: /* meanqt[m][z1]=0.; */
4415: /* } */
4416: /* } */
4417:
4418: /* dateintsum=0; */
4419: /* k2cpt=0; */
4420:
4421: /* For that combination of covariate j1, we count and print the frequencies in one pass */
4422: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4423: bool=1;
4424: if(j !=0){
4425: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4426: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4427: /* for (z1=1; z1<= nqfveff; z1++) { */
4428: /* meanq[z1]+=coqvar[Tvar[z1]][iind]; /\* Computes mean of quantitative with selected filter *\/ */
4429: /* } */
4430: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4431: /* if(Tvaraff[z1] ==-20){ */
4432: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4433: /* }else if(Tvaraff[z1] ==-10){ */
4434: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4435: /* }else */
4436: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
4437: /* Tests if this individual iind responded to combination j1 (V4=1 V3=0) */
4438: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4439: /* 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",
4440: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4441: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4442: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4443: } /* Onlyf fixed */
4444: } /* end z1 */
4445: } /* cptcovn > 0 */
4446: } /* end any */
4447: }/* end j==0 */
4448: if (bool==1){ /* We selected an individual iind satisfying combination j1 or all fixed */
4449: /* for(m=firstpass; m<=lastpass; m++){ */
4450: for(mi=1; mi<wav[iind];mi++){ /* For that wave */
4451: m=mw[mi][iind];
4452: if(j!=0){
4453: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4454: for (z1=1; z1<=cptcoveff; z1++) {
4455: if( Fixed[Tmodelind[z1]]==1){
4456: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4457: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4458: value is -1, we don't select. It differs from the
4459: constant and age model which counts them. */
4460: bool=0; /* not selected */
4461: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4462: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4463: bool=0;
4464: }
4465: }
4466: }
4467: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4468: } /* end j==0 */
4469: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
4470: if(bool==1){
4471: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4472: and mw[mi+1][iind]. dh depends on stepm. */
4473: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4474: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4475: if(m >=firstpass && m <=lastpass){
4476: k2=anint[m][iind]+(mint[m][iind]/12.);
4477: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4478: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4479: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4480: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4481: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4482: if (m<lastpass) {
4483: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4484: /* 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]); */
4485: if(s[m][iind]==-1)
4486: 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.));
4487: freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4488: /* if((int)agev[m][iind] == 55) */
4489: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4490: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4491: 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 4492: }
1.251 brouard 4493: } /* end if between passes */
4494: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4495: dateintsum=dateintsum+k2; /* on all covariates ?*/
4496: k2cpt++;
4497: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4498: }
1.251 brouard 4499: }else{
4500: bool=1;
4501: }/* end bool 2 */
4502: } /* end m */
4503: } /* end bool */
4504: } /* end iind = 1 to imx */
4505: /* prop[s][age] is feeded for any initial and valid live state as well as
4506: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4507:
4508:
4509: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
4510: pstamp(ficresp);
4511: if (cptcoveff>0 && j!=0){
4512: printf( "\n#********** Variable ");
4513: fprintf(ficresp, "\n#********** Variable ");
4514: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4515: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4516: fprintf(ficlog, "\n#********** Variable ");
4517: for (z1=1; z1<=cptcoveff; z1++){
4518: if(!FixedV[Tvaraff[z1]]){
4519: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4520: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4521: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4522: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4523: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4524: }else{
1.251 brouard 4525: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4526: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4527: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4528: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4529: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4530: }
4531: }
4532: printf( "**********\n#");
4533: fprintf(ficresp, "**********\n#");
4534: fprintf(ficresphtm, "**********</h3>\n");
4535: fprintf(ficresphtmfr, "**********</h3>\n");
4536: fprintf(ficlog, "**********\n");
4537: }
4538: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
4539: for(i=1; i<=nlstate;i++) {
4540: fprintf(ficresp, " Age Prev(%d) N(%d) N ",i,i);
4541: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4542: }
4543: fprintf(ficresp, "\n");
4544: fprintf(ficresphtm, "\n");
4545:
4546: /* Header of frequency table by age */
4547: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4548: fprintf(ficresphtmfr,"<th>Age</th> ");
4549: for(jk=-1; jk <=nlstate+ndeath; jk++){
4550: for(m=-1; m <=nlstate+ndeath; m++){
4551: if(jk!=0 && m!=0)
4552: fprintf(ficresphtmfr,"<th>%d%d</th> ",jk,m);
1.240 brouard 4553: }
1.226 brouard 4554: }
1.251 brouard 4555: fprintf(ficresphtmfr, "\n");
4556:
4557: /* For each age */
4558: for(iage=iagemin; iage <= iagemax+3; iage++){
4559: fprintf(ficresphtm,"<tr>");
4560: if(iage==iagemax+1){
4561: fprintf(ficlog,"1");
4562: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4563: }else if(iage==iagemax+2){
4564: fprintf(ficlog,"0");
4565: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4566: }else if(iage==iagemax+3){
4567: fprintf(ficlog,"Total");
4568: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4569: }else{
1.240 brouard 4570: if(first==1){
1.251 brouard 4571: first=0;
4572: printf("See log file for details...\n");
4573: }
4574: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4575: fprintf(ficlog,"Age %d", iage);
4576: }
4577: for(jk=1; jk <=nlstate ; jk++){
4578: for(m=-1, pp[jk]=0; m <=nlstate+ndeath ; m++)
4579: pp[jk] += freq[jk][m][iage];
4580: }
4581: for(jk=1; jk <=nlstate ; jk++){
4582: for(m=-1, pos=0; m <=0 ; m++)
4583: pos += freq[jk][m][iage];
4584: if(pp[jk]>=1.e-10){
4585: if(first==1){
4586: printf(" %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]);
4587: }
4588: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]);
4589: }else{
4590: if(first==1)
4591: printf(" %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk);
4592: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk);
1.240 brouard 4593: }
4594: }
4595:
1.251 brouard 4596: for(jk=1; jk <=nlstate ; jk++){
4597: /* posprop[jk]=0; */
4598: for(m=0, pp[jk]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4599: pp[jk] += freq[jk][m][iage];
4600: } /* pp[jk] is the total number of transitions starting from state jk and any ending status until this age */
4601:
4602: for(jk=1,pos=0, pospropta=0.; jk <=nlstate ; jk++){
4603: pos += pp[jk]; /* pos is the total number of transitions until this age */
4604: posprop[jk] += prop[jk][iage]; /* prop is the number of transitions from a live state
4605: from jk at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4606: pospropta += prop[jk][iage]; /* prop is the number of transitions from a live state
1.240 brouard 4607: from jk at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4608: }
1.251 brouard 4609: for(jk=1; jk <=nlstate ; jk++){
1.240 brouard 4610: if(pos>=1.e-5){
1.251 brouard 4611: if(first==1)
4612: printf(" %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos);
4613: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos);
4614: }else{
4615: if(first==1)
4616: printf(" %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk);
4617: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk);
4618: }
4619: if( iage <= iagemax){
4620: if(pos>=1.e-5){
4621: fprintf(ficresp," %d %.5f %.0f %.0f",iage,prop[jk][iage]/pospropta, prop[jk][iage],pospropta);
1.264 ! brouard 4622: /* fprintf(ficresp, "%d %d %d %.5f %.0f %.0f",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)],iage,prop[jk][iage]/pospropta, prop[jk][iage],pospropta); */
! 4623:
1.251 brouard 4624: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[jk][iage]/pospropta, prop[jk][iage],pospropta);
4625: /*probs[iage][jk][j1]= pp[jk]/pos;*/
4626: /*printf("\niage=%d jk=%d j1=%d %.5f %.0f %.0f %f",iage,jk,j1,pp[jk]/pos, pp[jk],pos,probs[iage][jk][j1]);*/
4627: }
4628: else{
4629: fprintf(ficresp," %d NaNq %.0f %.0f",iage,prop[jk][iage],pospropta);
4630: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[jk][iage],pospropta);
4631: }
1.240 brouard 4632: }
1.251 brouard 4633: pospropt[jk] +=posprop[jk];
4634: } /* end loop jk */
4635: /* pospropt=0.; */
4636: for(jk=-1; jk <=nlstate+ndeath; jk++){
4637: for(m=-1; m <=nlstate+ndeath; m++){
4638: if(freq[jk][m][iage] !=0 ) { /* minimizing output */
4639: if(first==1){
4640: printf(" %d%d=%.0f",jk,m,freq[jk][m][iage]);
4641: }
1.253 brouard 4642: /* printf(" %d%d=%.0f",jk,m,freq[jk][m][iage]); */
1.251 brouard 4643: fprintf(ficlog," %d%d=%.0f",jk,m,freq[jk][m][iage]);
4644: }
4645: if(jk!=0 && m!=0)
4646: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[jk][m][iage]);
1.240 brouard 4647: }
1.251 brouard 4648: } /* end loop jk */
4649: posproptt=0.;
4650: for(jk=1; jk <=nlstate; jk++){
4651: posproptt += pospropt[jk];
4652: }
4653: fprintf(ficresphtmfr,"</tr>\n ");
4654: if(iage <= iagemax){
4655: fprintf(ficresp,"\n");
4656: fprintf(ficresphtm,"</tr>\n");
1.240 brouard 4657: }
1.251 brouard 4658: if(first==1)
4659: printf("Others in log...\n");
4660: fprintf(ficlog,"\n");
4661: } /* end loop age iage */
4662: fprintf(ficresphtm,"<tr><th>Tot</th>");
4663: for(jk=1; jk <=nlstate ; jk++){
4664: if(posproptt < 1.e-5){
4665: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[jk],posproptt);
4666: }else{
4667: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[jk]/posproptt,pospropt[jk],posproptt);
1.240 brouard 4668: }
1.226 brouard 4669: }
1.251 brouard 4670: fprintf(ficresphtm,"</tr>\n");
4671: fprintf(ficresphtm,"</table>\n");
4672: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4673: if(posproptt < 1.e-5){
1.251 brouard 4674: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4675: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4676: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4677: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4678: invalidvarcomb[j1]=1;
1.226 brouard 4679: }else{
1.251 brouard 4680: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4681: invalidvarcomb[j1]=0;
1.226 brouard 4682: }
1.251 brouard 4683: fprintf(ficresphtmfr,"</table>\n");
4684: fprintf(ficlog,"\n");
4685: if(j!=0){
4686: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
4687: for(i=1,jk=1; i <=nlstate; i++){
4688: for(k=1; k <=(nlstate+ndeath); k++){
4689: if (k != i) {
4690: for(jj=1; jj <=ncovmodel; jj++){ /* For counting jk */
1.253 brouard 4691: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4692: if(j1==1){ /* All dummy covariates to zero */
4693: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4694: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4695: printf("%d%d ",i,k);
4696: fprintf(ficlog,"%d%d ",i,k);
4697: printf("%12.7f ln(%.0f/%.0f)= %f, OR=%f sd=%f \n",p[jk],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]));
4698: fprintf(ficlog,"%12.7f ln(%.0f/%.0f)= %12.7f \n",p[jk],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
4699: pstart[jk]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4700: }
1.253 brouard 4701: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4702: for(iage=iagemin; iage <= iagemax+3; iage++){
4703: x[iage]= (double)iage;
4704: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
4705: /* printf("i=%d, k=%d, jk=%d, j1=%d, jj=%d, y[%d]=%f\n",i,k,jk,j1,jj, iage, y[iage]); */
4706: }
4707: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
4708: pstart[jk]=b;
4709: pstart[jk-1]=a;
1.252 brouard 4710: }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 */
4711: 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]);
4712: 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]);
1.251 brouard 4713: pstart[jk]= log((freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4]));
1.252 brouard 4714: printf("%d%d ",i,k);
4715: fprintf(ficlog,"%d%d ",i,k);
1.251 brouard 4716: printf("jk=%d,i=%d,k=%d,p[%d]=%12.7f ln((%.0f/%.0f)/(%.0f/%.0f))= %f, OR=%f sd=%f \n",jk,i,k,jk,p[jk],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]));
4717: }else{ /* Other cases, like quantitative fixed or varying covariates */
4718: ;
4719: }
4720: /* printf("%12.7f )", param[i][jj][k]); */
4721: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
4722: jk++;
4723: } /* end jj */
4724: } /* end k!= i */
4725: } /* end k */
4726: } /* end i, jk */
4727: } /* end j !=0 */
4728: } /* end selected combination of covariate j1 */
4729: if(j==0){ /* We can estimate starting values from the occurences in each case */
4730: printf("#Freqsummary: Starting values for the constants:\n");
4731: fprintf(ficlog,"\n");
4732: for(i=1,jk=1; i <=nlstate; i++){
4733: for(k=1; k <=(nlstate+ndeath); k++){
4734: if (k != i) {
4735: printf("%d%d ",i,k);
4736: fprintf(ficlog,"%d%d ",i,k);
4737: for(jj=1; jj <=ncovmodel; jj++){
1.253 brouard 4738: pstart[jk]=p[jk]; /* Setting pstart to p values by default */
4739: if(jj==1){ /* Age has to be done */
4740: pstart[jk]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4741: printf("%12.7f ln(%.0f/%.0f)= %12.7f ",p[jk],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
4742: fprintf(ficlog,"%12.7f ln(%.0f/%.0f)= %12.7f ",p[jk],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
4743: }
4744: /* printf("%12.7f )", param[i][jj][k]); */
4745: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
4746: jk++;
1.250 brouard 4747: }
1.251 brouard 4748: printf("\n");
4749: fprintf(ficlog,"\n");
1.250 brouard 4750: }
4751: }
4752: }
1.251 brouard 4753: printf("#Freqsummary\n");
4754: fprintf(ficlog,"\n");
4755: for(jk=-1; jk <=nlstate+ndeath; jk++){
4756: for(m=-1; m <=nlstate+ndeath; m++){
4757: /* param[i]|j][k]= freq[jk][m][iagemax+3] */
1.250 brouard 4758: printf(" %d%d=%.0f",jk,m,freq[jk][m][iagemax+3]);
4759: fprintf(ficlog," %d%d=%.0f",jk,m,freq[jk][m][iagemax+3]);
1.251 brouard 4760: /* if(freq[jk][m][iage] !=0 ) { /\* minimizing output *\/ */
4761: /* printf(" %d%d=%.0f",jk,m,freq[jk][m][iagemax+3]); */
4762: /* fprintf(ficlog," %d%d=%.0f",jk,m,freq[jk][m][iagemax+3]); */
4763: /* } */
4764: }
4765: } /* end loop jk */
4766:
4767: printf("\n");
4768: fprintf(ficlog,"\n");
4769: } /* end j=0 */
1.249 brouard 4770: } /* end j */
1.252 brouard 4771:
1.253 brouard 4772: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 4773: for(i=1, jk=1; i <=nlstate; i++){
4774: for(j=1; j <=nlstate+ndeath; j++){
4775: if(j!=i){
4776: /*ca[0]= k+'a'-1;ca[1]='\0';*/
4777: printf("%1d%1d",i,j);
4778: fprintf(ficparo,"%1d%1d",i,j);
4779: for(k=1; k<=ncovmodel;k++){
4780: /* printf(" %lf",param[i][j][k]); */
4781: /* fprintf(ficparo," %lf",param[i][j][k]); */
4782: p[jk]=pstart[jk];
4783: printf(" %f ",pstart[jk]);
4784: fprintf(ficparo," %f ",pstart[jk]);
4785: jk++;
4786: }
4787: printf("\n");
4788: fprintf(ficparo,"\n");
4789: }
4790: }
4791: }
4792: } /* end mle=-2 */
1.226 brouard 4793: dateintmean=dateintsum/k2cpt;
1.240 brouard 4794:
1.226 brouard 4795: fclose(ficresp);
4796: fclose(ficresphtm);
4797: fclose(ficresphtmfr);
4798: free_vector(meanq,1,nqfveff);
4799: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 4800: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
4801: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 4802: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4803: free_vector(pospropt,1,nlstate);
4804: free_vector(posprop,1,nlstate);
1.251 brouard 4805: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4806: free_vector(pp,1,nlstate);
4807: /* End of freqsummary */
4808: }
1.126 brouard 4809:
4810: /************ Prevalence ********************/
1.227 brouard 4811: 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)
4812: {
4813: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
4814: in each health status at the date of interview (if between dateprev1 and dateprev2).
4815: We still use firstpass and lastpass as another selection.
4816: */
1.126 brouard 4817:
1.227 brouard 4818: int i, m, jk, j1, bool, z1,j, iv;
4819: int mi; /* Effective wave */
4820: int iage;
4821: double agebegin, ageend;
4822:
4823: double **prop;
4824: double posprop;
4825: double y2; /* in fractional years */
4826: int iagemin, iagemax;
4827: int first; /** to stop verbosity which is redirected to log file */
4828:
4829: iagemin= (int) agemin;
4830: iagemax= (int) agemax;
4831: /*pp=vector(1,nlstate);*/
1.251 brouard 4832: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 4833: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
4834: j1=0;
1.222 brouard 4835:
1.227 brouard 4836: /*j=cptcoveff;*/
4837: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 4838:
1.227 brouard 4839: first=1;
4840: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
4841: for (i=1; i<=nlstate; i++)
1.251 brouard 4842: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 4843: prop[i][iage]=0.0;
4844: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
4845: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
4846: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
4847:
4848: for (i=1; i<=imx; i++) { /* Each individual */
4849: bool=1;
4850: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
4851: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
4852: m=mw[mi][i];
4853: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
4854: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
4855: for (z1=1; z1<=cptcoveff; z1++){
4856: if( Fixed[Tmodelind[z1]]==1){
4857: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4858: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
4859: bool=0;
4860: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
4861: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4862: bool=0;
4863: }
4864: }
4865: if(bool==1){ /* Otherwise we skip that wave/person */
4866: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
4867: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
4868: if(m >=firstpass && m <=lastpass){
4869: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
4870: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
4871: if(agev[m][i]==0) agev[m][i]=iagemax+1;
4872: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 4873: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 4874: 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);
4875: exit(1);
4876: }
4877: if (s[m][i]>0 && s[m][i]<=nlstate) {
4878: /*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]]);*/
4879: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
4880: prop[s[m][i]][iagemax+3] += weight[i];
4881: } /* end valid statuses */
4882: } /* end selection of dates */
4883: } /* end selection of waves */
4884: } /* end bool */
4885: } /* end wave */
4886: } /* end individual */
4887: for(i=iagemin; i <= iagemax+3; i++){
4888: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
4889: posprop += prop[jk][i];
4890: }
4891:
4892: for(jk=1; jk <=nlstate ; jk++){
4893: if( i <= iagemax){
4894: if(posprop>=1.e-5){
4895: probs[i][jk][j1]= prop[jk][i]/posprop;
4896: } else{
4897: if(first==1){
4898: first=0;
4899: printf("Warning Observed prevalence probs[%d][%d][%d]=%lf because of lack of cases\nSee others in log file...\n",jk,i,j1,probs[i][jk][j1]);
4900: }
4901: }
4902: }
4903: }/* end jk */
4904: }/* end i */
1.222 brouard 4905: /*} *//* end i1 */
1.227 brouard 4906: } /* end j1 */
1.222 brouard 4907:
1.227 brouard 4908: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
4909: /*free_vector(pp,1,nlstate);*/
1.251 brouard 4910: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 4911: } /* End of prevalence */
1.126 brouard 4912:
4913: /************* Waves Concatenation ***************/
4914:
4915: 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)
4916: {
4917: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
4918: Death is a valid wave (if date is known).
4919: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
4920: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4921: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 4922: */
1.126 brouard 4923:
1.224 brouard 4924: int i=0, mi=0, m=0, mli=0;
1.126 brouard 4925: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
4926: double sum=0., jmean=0.;*/
1.224 brouard 4927: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 4928: int j, k=0,jk, ju, jl;
4929: double sum=0.;
4930: first=0;
1.214 brouard 4931: firstwo=0;
1.217 brouard 4932: firsthree=0;
1.218 brouard 4933: firstfour=0;
1.164 brouard 4934: jmin=100000;
1.126 brouard 4935: jmax=-1;
4936: jmean=0.;
1.224 brouard 4937:
4938: /* Treating live states */
1.214 brouard 4939: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 4940: mi=0; /* First valid wave */
1.227 brouard 4941: mli=0; /* Last valid wave */
1.126 brouard 4942: m=firstpass;
1.214 brouard 4943: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 4944: 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 */
4945: mli=m-1;/* mw[++mi][i]=m-1; */
4946: }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 */
4947: mw[++mi][i]=m;
4948: mli=m;
1.224 brouard 4949: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
4950: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 4951: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 4952: }
1.227 brouard 4953: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 4954: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 4955: break;
1.224 brouard 4956: #else
1.227 brouard 4957: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
4958: if(firsthree == 0){
1.262 brouard 4959: 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 4960: firsthree=1;
4961: }
1.262 brouard 4962: 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 4963: mw[++mi][i]=m;
4964: mli=m;
4965: }
4966: if(s[m][i]==-2){ /* Vital status is really unknown */
4967: nbwarn++;
4968: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
4969: 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);
4970: 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);
4971: }
4972: break;
4973: }
4974: break;
1.224 brouard 4975: #endif
1.227 brouard 4976: }/* End m >= lastpass */
1.126 brouard 4977: }/* end while */
1.224 brouard 4978:
1.227 brouard 4979: /* 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 4980: /* After last pass */
1.224 brouard 4981: /* Treating death states */
1.214 brouard 4982: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 4983: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
4984: /* } */
1.126 brouard 4985: mi++; /* Death is another wave */
4986: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 4987: /* Only death is a correct wave */
1.126 brouard 4988: mw[mi][i]=m;
1.257 brouard 4989: } /* else not in a death state */
1.224 brouard 4990: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 4991: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 4992: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 4993: 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 */
4994: nbwarn++;
4995: if(firstfiv==0){
4996: 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 );
4997: firstfiv=1;
4998: }else{
4999: 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 );
5000: }
5001: }else{ /* Death occured afer last wave potential bias */
5002: nberr++;
5003: if(firstwo==0){
1.257 brouard 5004: 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 5005: firstwo=1;
5006: }
1.257 brouard 5007: 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 5008: }
1.257 brouard 5009: }else{ /* if date of interview is unknown */
1.227 brouard 5010: /* death is known but not confirmed by death status at any wave */
5011: if(firstfour==0){
5012: 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 );
5013: firstfour=1;
5014: }
5015: 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 5016: }
1.224 brouard 5017: } /* end if date of death is known */
5018: #endif
5019: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5020: /* wav[i]=mw[mi][i]; */
1.126 brouard 5021: if(mi==0){
5022: nbwarn++;
5023: if(first==0){
1.227 brouard 5024: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5025: first=1;
1.126 brouard 5026: }
5027: if(first==1){
1.227 brouard 5028: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5029: }
5030: } /* end mi==0 */
5031: } /* End individuals */
1.214 brouard 5032: /* wav and mw are no more changed */
1.223 brouard 5033:
1.214 brouard 5034:
1.126 brouard 5035: for(i=1; i<=imx; i++){
5036: for(mi=1; mi<wav[i];mi++){
5037: if (stepm <=0)
1.227 brouard 5038: dh[mi][i]=1;
1.126 brouard 5039: else{
1.260 brouard 5040: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5041: if (agedc[i] < 2*AGESUP) {
5042: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5043: if(j==0) j=1; /* Survives at least one month after exam */
5044: else if(j<0){
5045: nberr++;
5046: 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]);
5047: j=1; /* Temporary Dangerous patch */
5048: 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);
5049: 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]);
5050: 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);
5051: }
5052: k=k+1;
5053: if (j >= jmax){
5054: jmax=j;
5055: ijmax=i;
5056: }
5057: if (j <= jmin){
5058: jmin=j;
5059: ijmin=i;
5060: }
5061: sum=sum+j;
5062: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5063: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5064: }
5065: }
5066: else{
5067: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5068: /* 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 5069:
1.227 brouard 5070: k=k+1;
5071: if (j >= jmax) {
5072: jmax=j;
5073: ijmax=i;
5074: }
5075: else if (j <= jmin){
5076: jmin=j;
5077: ijmin=i;
5078: }
5079: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5080: /*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]);*/
5081: if(j<0){
5082: nberr++;
5083: 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]);
5084: 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]);
5085: }
5086: sum=sum+j;
5087: }
5088: jk= j/stepm;
5089: jl= j -jk*stepm;
5090: ju= j -(jk+1)*stepm;
5091: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5092: if(jl==0){
5093: dh[mi][i]=jk;
5094: bh[mi][i]=0;
5095: }else{ /* We want a negative bias in order to only have interpolation ie
5096: * to avoid the price of an extra matrix product in likelihood */
5097: dh[mi][i]=jk+1;
5098: bh[mi][i]=ju;
5099: }
5100: }else{
5101: if(jl <= -ju){
5102: dh[mi][i]=jk;
5103: bh[mi][i]=jl; /* bias is positive if real duration
5104: * is higher than the multiple of stepm and negative otherwise.
5105: */
5106: }
5107: else{
5108: dh[mi][i]=jk+1;
5109: bh[mi][i]=ju;
5110: }
5111: if(dh[mi][i]==0){
5112: dh[mi][i]=1; /* At least one step */
5113: bh[mi][i]=ju; /* At least one step */
5114: /* 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);*/
5115: }
5116: } /* end if mle */
1.126 brouard 5117: }
5118: } /* end wave */
5119: }
5120: jmean=sum/k;
5121: 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 5122: 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 5123: }
1.126 brouard 5124:
5125: /*********** Tricode ****************************/
1.220 brouard 5126: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5127: {
5128: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5129: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5130: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5131: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5132: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5133: */
1.130 brouard 5134:
1.242 brouard 5135: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5136: int modmaxcovj=0; /* Modality max of covariates j */
5137: int cptcode=0; /* Modality max of covariates j */
5138: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5139:
5140:
1.242 brouard 5141: /* cptcoveff=0; */
5142: /* *cptcov=0; */
1.126 brouard 5143:
1.242 brouard 5144: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.126 brouard 5145:
1.242 brouard 5146: /* Loop on covariates without age and products and no quantitative variable */
5147: /* for (j=1; j<=(cptcovs); j++) { /\* From model V1 + V2*age+ V3 + V3*V4 keeps V1 + V3 = 2 only *\/ */
5148: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5149: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5150: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5151: switch(Fixed[k]) {
5152: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5153: 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*/
5154: ij=(int)(covar[Tvar[k]][i]);
5155: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5156: * If product of Vn*Vm, still boolean *:
5157: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5158: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5159: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5160: modality of the nth covariate of individual i. */
5161: if (ij > modmaxcovj)
5162: modmaxcovj=ij;
5163: else if (ij < modmincovj)
5164: modmincovj=ij;
5165: if ((ij < -1) && (ij > NCOVMAX)){
5166: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5167: exit(1);
5168: }else
5169: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5170: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5171: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5172: /* getting the maximum value of the modality of the covariate
5173: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5174: female ies 1, then modmaxcovj=1.
5175: */
5176: } /* end for loop on individuals i */
5177: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5178: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5179: cptcode=modmaxcovj;
5180: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5181: /*for (i=0; i<=cptcode; i++) {*/
5182: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5183: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5184: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5185: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5186: if( j != -1){
5187: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5188: covariate for which somebody answered excluding
5189: undefined. Usually 2: 0 and 1. */
5190: }
5191: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5192: covariate for which somebody answered including
5193: undefined. Usually 3: -1, 0 and 1. */
5194: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5195: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5196: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5197:
1.242 brouard 5198: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5199: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5200: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5201: /* modmincovj=3; modmaxcovj = 7; */
5202: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5203: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5204: /* defining two dummy variables: variables V1_1 and V1_2.*/
5205: /* nbcode[Tvar[j]][ij]=k; */
5206: /* nbcode[Tvar[j]][1]=0; */
5207: /* nbcode[Tvar[j]][2]=1; */
5208: /* nbcode[Tvar[j]][3]=2; */
5209: /* To be continued (not working yet). */
5210: ij=0; /* ij is similar to i but can jump over null modalities */
5211: 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*/
5212: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5213: break;
5214: }
5215: ij++;
5216: 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*/
5217: cptcode = ij; /* New max modality for covar j */
5218: } /* end of loop on modality i=-1 to 1 or more */
5219: break;
5220: case 1: /* Testing on varying covariate, could be simple and
5221: * should look at waves or product of fixed *
5222: * varying. No time to test -1, assuming 0 and 1 only */
5223: ij=0;
5224: for(i=0; i<=1;i++){
5225: nbcode[Tvar[k]][++ij]=i;
5226: }
5227: break;
5228: default:
5229: break;
5230: } /* end switch */
5231: } /* end dummy test */
5232:
5233: /* for (k=0; k<= cptcode; k++) { /\* k=-1 ? k=0 to 1 *\//\* Could be 1 to 4 *\//\* cptcode=modmaxcovj *\/ */
5234: /* /\*recode from 0 *\/ */
5235: /* k is a modality. If we have model=V1+V1*sex */
5236: /* then: nbcode[1][1]=0 ; nbcode[1][2]=1; nbcode[2][1]=0 ; nbcode[2][2]=1; */
5237: /* But if some modality were not used, it is recoded from 0 to a newer modmaxcovj=cptcode *\/ */
5238: /* } */
5239: /* /\* cptcode = ij; *\/ /\* New max modality for covar j *\/ */
5240: /* if (ij > ncodemax[j]) { */
5241: /* printf( " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5242: /* fprintf(ficlog, " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5243: /* break; */
5244: /* } */
5245: /* } /\* end of loop on modality k *\/ */
5246: } /* end of loop on model-covariate j. nbcode[Tvarj][1]=0 and nbcode[Tvarj][2]=1 sets the value of covariate j*/
5247:
5248: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5249: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5250: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5251: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5252: 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 */
5253: 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 */
5254: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5255: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5256:
5257: ij=0;
5258: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5259: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5260: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5261: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5262: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5263: /* If product not in single variable we don't print results */
5264: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5265: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5266: 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*/
5267: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5268: 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 */
5269: if(Fixed[k]!=0)
5270: anyvaryingduminmodel=1;
5271: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5272: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5273: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5274: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5275: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5276: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5277: }
5278: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5279: /* ij--; */
5280: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5281: *cptcov=ij; /*Number of total real effective covariates: effective
5282: * because they can be excluded from the model and real
5283: * if in the model but excluded because missing values, but how to get k from ij?*/
5284: for(j=ij+1; j<= cptcovt; j++){
5285: Tvaraff[j]=0;
5286: Tmodelind[j]=0;
5287: }
5288: for(j=ntveff+1; j<= cptcovt; j++){
5289: TmodelInvind[j]=0;
5290: }
5291: /* To be sorted */
5292: ;
5293: }
1.126 brouard 5294:
1.145 brouard 5295:
1.126 brouard 5296: /*********** Health Expectancies ****************/
5297:
1.235 brouard 5298: 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 5299:
5300: {
5301: /* Health expectancies, no variances */
1.164 brouard 5302: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5303: int nhstepma, nstepma; /* Decreasing with age */
5304: double age, agelim, hf;
5305: double ***p3mat;
5306: double eip;
5307:
1.238 brouard 5308: /* pstamp(ficreseij); */
1.126 brouard 5309: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5310: fprintf(ficreseij,"# Age");
5311: for(i=1; i<=nlstate;i++){
5312: for(j=1; j<=nlstate;j++){
5313: fprintf(ficreseij," e%1d%1d ",i,j);
5314: }
5315: fprintf(ficreseij," e%1d. ",i);
5316: }
5317: fprintf(ficreseij,"\n");
5318:
5319:
5320: if(estepm < stepm){
5321: printf ("Problem %d lower than %d\n",estepm, stepm);
5322: }
5323: else hstepm=estepm;
5324: /* We compute the life expectancy from trapezoids spaced every estepm months
5325: * This is mainly to measure the difference between two models: for example
5326: * if stepm=24 months pijx are given only every 2 years and by summing them
5327: * we are calculating an estimate of the Life Expectancy assuming a linear
5328: * progression in between and thus overestimating or underestimating according
5329: * to the curvature of the survival function. If, for the same date, we
5330: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5331: * to compare the new estimate of Life expectancy with the same linear
5332: * hypothesis. A more precise result, taking into account a more precise
5333: * curvature will be obtained if estepm is as small as stepm. */
5334:
5335: /* For example we decided to compute the life expectancy with the smallest unit */
5336: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5337: nhstepm is the number of hstepm from age to agelim
5338: nstepm is the number of stepm from age to agelin.
5339: Look at hpijx to understand the reason of that which relies in memory size
5340: and note for a fixed period like estepm months */
5341: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5342: survival function given by stepm (the optimization length). Unfortunately it
5343: means that if the survival funtion is printed only each two years of age and if
5344: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5345: results. So we changed our mind and took the option of the best precision.
5346: */
5347: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5348:
5349: agelim=AGESUP;
5350: /* If stepm=6 months */
5351: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5352: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5353:
5354: /* nhstepm age range expressed in number of stepm */
5355: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5356: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5357: /* if (stepm >= YEARM) hstepm=1;*/
5358: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5359: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5360:
5361: for (age=bage; age<=fage; age ++){
5362: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5363: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5364: /* if (stepm >= YEARM) hstepm=1;*/
5365: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5366:
5367: /* If stepm=6 months */
5368: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5369: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5370:
1.235 brouard 5371: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5372:
5373: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5374:
5375: printf("%d|",(int)age);fflush(stdout);
5376: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5377:
5378: /* Computing expectancies */
5379: for(i=1; i<=nlstate;i++)
5380: for(j=1; j<=nlstate;j++)
5381: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5382: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5383:
5384: /* 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]);*/
5385:
5386: }
5387:
5388: fprintf(ficreseij,"%3.0f",age );
5389: for(i=1; i<=nlstate;i++){
5390: eip=0;
5391: for(j=1; j<=nlstate;j++){
5392: eip +=eij[i][j][(int)age];
5393: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5394: }
5395: fprintf(ficreseij,"%9.4f", eip );
5396: }
5397: fprintf(ficreseij,"\n");
5398:
5399: }
5400: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5401: printf("\n");
5402: fprintf(ficlog,"\n");
5403:
5404: }
5405:
1.235 brouard 5406: 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 5407:
5408: {
5409: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5410: to initial status i, ei. .
1.126 brouard 5411: */
5412: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5413: int nhstepma, nstepma; /* Decreasing with age */
5414: double age, agelim, hf;
5415: double ***p3matp, ***p3matm, ***varhe;
5416: double **dnewm,**doldm;
5417: double *xp, *xm;
5418: double **gp, **gm;
5419: double ***gradg, ***trgradg;
5420: int theta;
5421:
5422: double eip, vip;
5423:
5424: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5425: xp=vector(1,npar);
5426: xm=vector(1,npar);
5427: dnewm=matrix(1,nlstate*nlstate,1,npar);
5428: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5429:
5430: pstamp(ficresstdeij);
5431: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5432: fprintf(ficresstdeij,"# Age");
5433: for(i=1; i<=nlstate;i++){
5434: for(j=1; j<=nlstate;j++)
5435: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5436: fprintf(ficresstdeij," e%1d. ",i);
5437: }
5438: fprintf(ficresstdeij,"\n");
5439:
5440: pstamp(ficrescveij);
5441: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5442: fprintf(ficrescveij,"# Age");
5443: for(i=1; i<=nlstate;i++)
5444: for(j=1; j<=nlstate;j++){
5445: cptj= (j-1)*nlstate+i;
5446: for(i2=1; i2<=nlstate;i2++)
5447: for(j2=1; j2<=nlstate;j2++){
5448: cptj2= (j2-1)*nlstate+i2;
5449: if(cptj2 <= cptj)
5450: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5451: }
5452: }
5453: fprintf(ficrescveij,"\n");
5454:
5455: if(estepm < stepm){
5456: printf ("Problem %d lower than %d\n",estepm, stepm);
5457: }
5458: else hstepm=estepm;
5459: /* We compute the life expectancy from trapezoids spaced every estepm months
5460: * This is mainly to measure the difference between two models: for example
5461: * if stepm=24 months pijx are given only every 2 years and by summing them
5462: * we are calculating an estimate of the Life Expectancy assuming a linear
5463: * progression in between and thus overestimating or underestimating according
5464: * to the curvature of the survival function. If, for the same date, we
5465: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5466: * to compare the new estimate of Life expectancy with the same linear
5467: * hypothesis. A more precise result, taking into account a more precise
5468: * curvature will be obtained if estepm is as small as stepm. */
5469:
5470: /* For example we decided to compute the life expectancy with the smallest unit */
5471: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5472: nhstepm is the number of hstepm from age to agelim
5473: nstepm is the number of stepm from age to agelin.
5474: Look at hpijx to understand the reason of that which relies in memory size
5475: and note for a fixed period like estepm months */
5476: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5477: survival function given by stepm (the optimization length). Unfortunately it
5478: means that if the survival funtion is printed only each two years of age and if
5479: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5480: results. So we changed our mind and took the option of the best precision.
5481: */
5482: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5483:
5484: /* If stepm=6 months */
5485: /* nhstepm age range expressed in number of stepm */
5486: agelim=AGESUP;
5487: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5488: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5489: /* if (stepm >= YEARM) hstepm=1;*/
5490: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5491:
5492: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5493: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5494: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5495: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5496: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5497: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5498:
5499: for (age=bage; age<=fage; age ++){
5500: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5501: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5502: /* if (stepm >= YEARM) hstepm=1;*/
5503: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5504:
1.126 brouard 5505: /* If stepm=6 months */
5506: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5507: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5508:
5509: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5510:
1.126 brouard 5511: /* Computing Variances of health expectancies */
5512: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5513: decrease memory allocation */
5514: for(theta=1; theta <=npar; theta++){
5515: for(i=1; i<=npar; i++){
1.222 brouard 5516: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5517: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5518: }
1.235 brouard 5519: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5520: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5521:
1.126 brouard 5522: for(j=1; j<= nlstate; j++){
1.222 brouard 5523: for(i=1; i<=nlstate; i++){
5524: for(h=0; h<=nhstepm-1; h++){
5525: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5526: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5527: }
5528: }
1.126 brouard 5529: }
1.218 brouard 5530:
1.126 brouard 5531: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5532: for(h=0; h<=nhstepm-1; h++){
5533: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5534: }
1.126 brouard 5535: }/* End theta */
5536:
5537:
5538: for(h=0; h<=nhstepm-1; h++)
5539: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5540: for(theta=1; theta <=npar; theta++)
5541: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5542:
1.218 brouard 5543:
1.222 brouard 5544: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5545: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5546: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5547:
1.222 brouard 5548: printf("%d|",(int)age);fflush(stdout);
5549: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5550: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5551: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5552: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5553: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5554: for(ij=1;ij<=nlstate*nlstate;ij++)
5555: for(ji=1;ji<=nlstate*nlstate;ji++)
5556: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5557: }
5558: }
1.218 brouard 5559:
1.126 brouard 5560: /* Computing expectancies */
1.235 brouard 5561: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5562: for(i=1; i<=nlstate;i++)
5563: for(j=1; j<=nlstate;j++)
1.222 brouard 5564: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5565: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5566:
1.222 brouard 5567: /* 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 5568:
1.222 brouard 5569: }
1.218 brouard 5570:
1.126 brouard 5571: fprintf(ficresstdeij,"%3.0f",age );
5572: for(i=1; i<=nlstate;i++){
5573: eip=0.;
5574: vip=0.;
5575: for(j=1; j<=nlstate;j++){
1.222 brouard 5576: eip += eij[i][j][(int)age];
5577: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5578: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5579: 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 5580: }
5581: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5582: }
5583: fprintf(ficresstdeij,"\n");
1.218 brouard 5584:
1.126 brouard 5585: fprintf(ficrescveij,"%3.0f",age );
5586: for(i=1; i<=nlstate;i++)
5587: for(j=1; j<=nlstate;j++){
1.222 brouard 5588: cptj= (j-1)*nlstate+i;
5589: for(i2=1; i2<=nlstate;i2++)
5590: for(j2=1; j2<=nlstate;j2++){
5591: cptj2= (j2-1)*nlstate+i2;
5592: if(cptj2 <= cptj)
5593: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5594: }
1.126 brouard 5595: }
5596: fprintf(ficrescveij,"\n");
1.218 brouard 5597:
1.126 brouard 5598: }
5599: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5600: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5601: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5602: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5603: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5604: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5605: printf("\n");
5606: fprintf(ficlog,"\n");
1.218 brouard 5607:
1.126 brouard 5608: free_vector(xm,1,npar);
5609: free_vector(xp,1,npar);
5610: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5611: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5612: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5613: }
1.218 brouard 5614:
1.126 brouard 5615: /************ Variance ******************/
1.235 brouard 5616: 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 5617: {
5618: /* Variance of health expectancies */
5619: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/
5620: /* double **newm;*/
5621: /* int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)*/
5622:
5623: /* int movingaverage(); */
5624: double **dnewm,**doldm;
5625: double **dnewmp,**doldmp;
5626: int i, j, nhstepm, hstepm, h, nstepm ;
5627: int k;
5628: double *xp;
5629: double **gp, **gm; /* for var eij */
5630: double ***gradg, ***trgradg; /*for var eij */
5631: double **gradgp, **trgradgp; /* for var p point j */
5632: double *gpp, *gmp; /* for var p point j */
5633: double **varppt; /* for var p point j nlstate to nlstate+ndeath */
5634: double ***p3mat;
5635: double age,agelim, hf;
5636: /* double ***mobaverage; */
5637: int theta;
5638: char digit[4];
5639: char digitp[25];
5640:
5641: char fileresprobmorprev[FILENAMELENGTH];
5642:
5643: if(popbased==1){
5644: if(mobilav!=0)
5645: strcpy(digitp,"-POPULBASED-MOBILAV_");
5646: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5647: }
5648: else
5649: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5650:
1.218 brouard 5651: /* if (mobilav!=0) { */
5652: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5653: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5654: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5655: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5656: /* } */
5657: /* } */
5658:
5659: strcpy(fileresprobmorprev,"PRMORPREV-");
5660: sprintf(digit,"%-d",ij);
5661: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5662: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5663: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5664: strcat(fileresprobmorprev,fileresu);
5665: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5666: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5667: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5668: }
5669: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5670: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5671: pstamp(ficresprobmorprev);
5672: 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 5673: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5674: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5675: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5676: }
5677: for(j=1;j<=cptcoveff;j++)
5678: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5679: fprintf(ficresprobmorprev,"\n");
5680:
1.218 brouard 5681: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5682: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5683: fprintf(ficresprobmorprev," p.%-d SE",j);
5684: for(i=1; i<=nlstate;i++)
5685: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5686: }
5687: fprintf(ficresprobmorprev,"\n");
5688:
5689: fprintf(ficgp,"\n# Routine varevsij");
5690: fprintf(ficgp,"\nunset title \n");
5691: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5692: 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");
5693: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
5694: /* } */
5695: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5696: pstamp(ficresvij);
5697: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5698: if(popbased==1)
5699: 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);
5700: else
5701: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5702: fprintf(ficresvij,"# Age");
5703: for(i=1; i<=nlstate;i++)
5704: for(j=1; j<=nlstate;j++)
5705: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5706: fprintf(ficresvij,"\n");
5707:
5708: xp=vector(1,npar);
5709: dnewm=matrix(1,nlstate,1,npar);
5710: doldm=matrix(1,nlstate,1,nlstate);
5711: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5712: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5713:
5714: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5715: gpp=vector(nlstate+1,nlstate+ndeath);
5716: gmp=vector(nlstate+1,nlstate+ndeath);
5717: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5718:
1.218 brouard 5719: if(estepm < stepm){
5720: printf ("Problem %d lower than %d\n",estepm, stepm);
5721: }
5722: else hstepm=estepm;
5723: /* For example we decided to compute the life expectancy with the smallest unit */
5724: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5725: nhstepm is the number of hstepm from age to agelim
5726: nstepm is the number of stepm from age to agelim.
5727: Look at function hpijx to understand why because of memory size limitations,
5728: we decided (b) to get a life expectancy respecting the most precise curvature of the
5729: survival function given by stepm (the optimization length). Unfortunately it
5730: means that if the survival funtion is printed every two years of age and if
5731: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5732: results. So we changed our mind and took the option of the best precision.
5733: */
5734: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5735: agelim = AGESUP;
5736: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5737: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5738: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5739: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5740: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
5741: gp=matrix(0,nhstepm,1,nlstate);
5742: gm=matrix(0,nhstepm,1,nlstate);
5743:
5744:
5745: for(theta=1; theta <=npar; theta++){
5746: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
5747: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5748: }
5749:
1.242 brouard 5750: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 5751:
5752: if (popbased==1) {
5753: if(mobilav ==0){
5754: for(i=1; i<=nlstate;i++)
5755: prlim[i][i]=probs[(int)age][i][ij];
5756: }else{ /* mobilav */
5757: for(i=1; i<=nlstate;i++)
5758: prlim[i][i]=mobaverage[(int)age][i][ij];
5759: }
5760: }
5761:
1.235 brouard 5762: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Returns p3mat[i][j][h] for h=1 to nhstepm */
1.218 brouard 5763: for(j=1; j<= nlstate; j++){
5764: for(h=0; h<=nhstepm; h++){
5765: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
5766: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
5767: }
5768: }
5769: /* Next for computing probability of death (h=1 means
5770: computed over hstepm matrices product = hstepm*stepm months)
5771: as a weighted average of prlim.
5772: */
5773: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5774: for(i=1,gpp[j]=0.; i<= nlstate; i++)
5775: gpp[j] += prlim[i][i]*p3mat[i][j][1];
5776: }
5777: /* end probability of death */
5778:
5779: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
5780: xp[i] = x[i] - (i==theta ?delti[theta]:0);
5781:
1.242 brouard 5782: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 5783:
5784: if (popbased==1) {
5785: if(mobilav ==0){
5786: for(i=1; i<=nlstate;i++)
5787: prlim[i][i]=probs[(int)age][i][ij];
5788: }else{ /* mobilav */
5789: for(i=1; i<=nlstate;i++)
5790: prlim[i][i]=mobaverage[(int)age][i][ij];
5791: }
5792: }
5793:
1.235 brouard 5794: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 5795:
5796: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
5797: for(h=0; h<=nhstepm; h++){
5798: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
5799: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
5800: }
5801: }
5802: /* This for computing probability of death (h=1 means
5803: computed over hstepm matrices product = hstepm*stepm months)
5804: as a weighted average of prlim.
5805: */
5806: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5807: for(i=1,gmp[j]=0.; i<= nlstate; i++)
5808: gmp[j] += prlim[i][i]*p3mat[i][j][1];
5809: }
5810: /* end probability of death */
5811:
5812: for(j=1; j<= nlstate; j++) /* vareij */
5813: for(h=0; h<=nhstepm; h++){
5814: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
5815: }
5816:
5817: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu */
5818: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
5819: }
5820:
5821: } /* End theta */
5822:
5823: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
5824:
5825: for(h=0; h<=nhstepm; h++) /* veij */
5826: for(j=1; j<=nlstate;j++)
5827: for(theta=1; theta <=npar; theta++)
5828: trgradg[h][j][theta]=gradg[h][theta][j];
5829:
5830: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
5831: for(theta=1; theta <=npar; theta++)
5832: trgradgp[j][theta]=gradgp[theta][j];
5833:
5834:
5835: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5836: for(i=1;i<=nlstate;i++)
5837: for(j=1;j<=nlstate;j++)
5838: vareij[i][j][(int)age] =0.;
5839:
5840: for(h=0;h<=nhstepm;h++){
5841: for(k=0;k<=nhstepm;k++){
5842: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
5843: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
5844: for(i=1;i<=nlstate;i++)
5845: for(j=1;j<=nlstate;j++)
5846: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
5847: }
5848: }
5849:
5850: /* pptj */
5851: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
5852: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
5853: for(j=nlstate+1;j<=nlstate+ndeath;j++)
5854: for(i=nlstate+1;i<=nlstate+ndeath;i++)
5855: varppt[j][i]=doldmp[j][i];
5856: /* end ppptj */
5857: /* x centered again */
5858:
1.242 brouard 5859: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 5860:
5861: if (popbased==1) {
5862: if(mobilav ==0){
5863: for(i=1; i<=nlstate;i++)
5864: prlim[i][i]=probs[(int)age][i][ij];
5865: }else{ /* mobilav */
5866: for(i=1; i<=nlstate;i++)
5867: prlim[i][i]=mobaverage[(int)age][i][ij];
5868: }
5869: }
5870:
5871: /* This for computing probability of death (h=1 means
5872: computed over hstepm (estepm) matrices product = hstepm*stepm months)
5873: as a weighted average of prlim.
5874: */
1.235 brouard 5875: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 5876: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5877: for(i=1,gmp[j]=0.;i<= nlstate; i++)
5878: gmp[j] += prlim[i][i]*p3mat[i][j][1];
5879: }
5880: /* end probability of death */
5881:
5882: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
5883: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5884: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
5885: for(i=1; i<=nlstate;i++){
5886: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
5887: }
5888: }
5889: fprintf(ficresprobmorprev,"\n");
5890:
5891: fprintf(ficresvij,"%.0f ",age );
5892: for(i=1; i<=nlstate;i++)
5893: for(j=1; j<=nlstate;j++){
5894: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
5895: }
5896: fprintf(ficresvij,"\n");
5897: free_matrix(gp,0,nhstepm,1,nlstate);
5898: free_matrix(gm,0,nhstepm,1,nlstate);
5899: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
5900: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
5901: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5902: } /* End age */
5903: free_vector(gpp,nlstate+1,nlstate+ndeath);
5904: free_vector(gmp,nlstate+1,nlstate+ndeath);
5905: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
5906: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
5907: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
5908: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
5909: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
5910: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
5911: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
5912: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
5913: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
5914: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
5915: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
5916: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
5917: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
5918: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
5919: 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);
5920: /* 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 5921: */
1.218 brouard 5922: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
5923: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 5924:
1.218 brouard 5925: free_vector(xp,1,npar);
5926: free_matrix(doldm,1,nlstate,1,nlstate);
5927: free_matrix(dnewm,1,nlstate,1,npar);
5928: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5929: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
5930: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5931: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5932: fclose(ficresprobmorprev);
5933: fflush(ficgp);
5934: fflush(fichtm);
5935: } /* end varevsij */
1.126 brouard 5936:
5937: /************ Variance of prevlim ******************/
1.235 brouard 5938: void varprevlim(char fileres[], 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 5939: {
1.205 brouard 5940: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 5941: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 5942:
1.126 brouard 5943: double **dnewm,**doldm;
5944: int i, j, nhstepm, hstepm;
5945: double *xp;
5946: double *gp, *gm;
5947: double **gradg, **trgradg;
1.208 brouard 5948: double **mgm, **mgp;
1.126 brouard 5949: double age,agelim;
5950: int theta;
5951:
5952: pstamp(ficresvpl);
5953: fprintf(ficresvpl,"# Standard deviation of period (stable) prevalences \n");
1.241 brouard 5954: fprintf(ficresvpl,"# Age ");
5955: if(nresult >=1)
5956: fprintf(ficresvpl," Result# ");
1.126 brouard 5957: for(i=1; i<=nlstate;i++)
5958: fprintf(ficresvpl," %1d-%1d",i,i);
5959: fprintf(ficresvpl,"\n");
5960:
5961: xp=vector(1,npar);
5962: dnewm=matrix(1,nlstate,1,npar);
5963: doldm=matrix(1,nlstate,1,nlstate);
5964:
5965: hstepm=1*YEARM; /* Every year of age */
5966: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
5967: agelim = AGESUP;
5968: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5969: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5970: if (stepm >= YEARM) hstepm=1;
5971: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
5972: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 5973: mgp=matrix(1,npar,1,nlstate);
5974: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 5975: gp=vector(1,nlstate);
5976: gm=vector(1,nlstate);
5977:
5978: for(theta=1; theta <=npar; theta++){
5979: for(i=1; i<=npar; i++){ /* Computes gradient */
5980: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5981: }
1.209 brouard 5982: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 5983: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 5984: else
1.235 brouard 5985: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 5986: for(i=1;i<=nlstate;i++){
1.126 brouard 5987: gp[i] = prlim[i][i];
1.208 brouard 5988: mgp[theta][i] = prlim[i][i];
5989: }
1.126 brouard 5990: for(i=1; i<=npar; i++) /* Computes gradient */
5991: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.209 brouard 5992: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 5993: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 5994: else
1.235 brouard 5995: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 5996: for(i=1;i<=nlstate;i++){
1.126 brouard 5997: gm[i] = prlim[i][i];
1.208 brouard 5998: mgm[theta][i] = prlim[i][i];
5999: }
1.126 brouard 6000: for(i=1;i<=nlstate;i++)
6001: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6002: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6003: } /* End theta */
6004:
6005: trgradg =matrix(1,nlstate,1,npar);
6006:
6007: for(j=1; j<=nlstate;j++)
6008: for(theta=1; theta <=npar; theta++)
6009: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6010: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6011: /* printf("\nmgm mgp %d ",(int)age); */
6012: /* for(j=1; j<=nlstate;j++){ */
6013: /* printf(" %d ",j); */
6014: /* for(theta=1; theta <=npar; theta++) */
6015: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6016: /* printf("\n "); */
6017: /* } */
6018: /* } */
6019: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6020: /* printf("\n gradg %d ",(int)age); */
6021: /* for(j=1; j<=nlstate;j++){ */
6022: /* printf("%d ",j); */
6023: /* for(theta=1; theta <=npar; theta++) */
6024: /* printf("%d %lf ",theta,gradg[theta][j]); */
6025: /* printf("\n "); */
6026: /* } */
6027: /* } */
1.126 brouard 6028:
6029: for(i=1;i<=nlstate;i++)
6030: varpl[i][(int)age] =0.;
1.209 brouard 6031: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.205 brouard 6032: matprod2(dnewm,trgradg,1,nlstate,1,npar,1,npar,matcov);
6033: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg);
6034: }else{
1.126 brouard 6035: matprod2(dnewm,trgradg,1,nlstate,1,npar,1,npar,matcov);
6036: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6037: }
1.126 brouard 6038: for(i=1;i<=nlstate;i++)
6039: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6040:
6041: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6042: if(nresult >=1)
6043: fprintf(ficresvpl,"%d ",nres );
1.126 brouard 6044: for(i=1; i<=nlstate;i++)
6045: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
6046: fprintf(ficresvpl,"\n");
6047: free_vector(gp,1,nlstate);
6048: free_vector(gm,1,nlstate);
1.208 brouard 6049: free_matrix(mgm,1,npar,1,nlstate);
6050: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6051: free_matrix(gradg,1,npar,1,nlstate);
6052: free_matrix(trgradg,1,nlstate,1,npar);
6053: } /* End age */
6054:
6055: free_vector(xp,1,npar);
6056: free_matrix(doldm,1,nlstate,1,npar);
6057: free_matrix(dnewm,1,nlstate,1,nlstate);
6058:
6059: }
6060:
6061: /************ Variance of one-step probabilities ******************/
6062: 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 6063: {
6064: int i, j=0, k1, l1, tj;
6065: int k2, l2, j1, z1;
6066: int k=0, l;
6067: int first=1, first1, first2;
6068: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6069: double **dnewm,**doldm;
6070: double *xp;
6071: double *gp, *gm;
6072: double **gradg, **trgradg;
6073: double **mu;
6074: double age, cov[NCOVMAX+1];
6075: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6076: int theta;
6077: char fileresprob[FILENAMELENGTH];
6078: char fileresprobcov[FILENAMELENGTH];
6079: char fileresprobcor[FILENAMELENGTH];
6080: double ***varpij;
6081:
6082: strcpy(fileresprob,"PROB_");
6083: strcat(fileresprob,fileres);
6084: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6085: printf("Problem with resultfile: %s\n", fileresprob);
6086: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6087: }
6088: strcpy(fileresprobcov,"PROBCOV_");
6089: strcat(fileresprobcov,fileresu);
6090: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6091: printf("Problem with resultfile: %s\n", fileresprobcov);
6092: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6093: }
6094: strcpy(fileresprobcor,"PROBCOR_");
6095: strcat(fileresprobcor,fileresu);
6096: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6097: printf("Problem with resultfile: %s\n", fileresprobcor);
6098: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6099: }
6100: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6101: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6102: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6103: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6104: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6105: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6106: pstamp(ficresprob);
6107: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6108: fprintf(ficresprob,"# Age");
6109: pstamp(ficresprobcov);
6110: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6111: fprintf(ficresprobcov,"# Age");
6112: pstamp(ficresprobcor);
6113: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6114: fprintf(ficresprobcor,"# Age");
1.126 brouard 6115:
6116:
1.222 brouard 6117: for(i=1; i<=nlstate;i++)
6118: for(j=1; j<=(nlstate+ndeath);j++){
6119: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6120: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6121: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6122: }
6123: /* fprintf(ficresprob,"\n");
6124: fprintf(ficresprobcov,"\n");
6125: fprintf(ficresprobcor,"\n");
6126: */
6127: xp=vector(1,npar);
6128: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6129: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6130: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6131: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6132: first=1;
6133: fprintf(ficgp,"\n# Routine varprob");
6134: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6135: fprintf(fichtm,"\n");
6136:
6137: 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.</li>\n",optionfilehtmcov);
6138: 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);
6139: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6140: and drawn. It helps understanding how is the covariance between two incidences.\
6141: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6142: 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 6143: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6144: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6145: standard deviations wide on each axis. <br>\
6146: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6147: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6148: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6149:
1.222 brouard 6150: cov[1]=1;
6151: /* tj=cptcoveff; */
1.225 brouard 6152: tj = (int) pow(2,cptcoveff);
1.222 brouard 6153: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6154: j1=0;
1.224 brouard 6155: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6156: if (cptcovn>0) {
6157: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6158: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6159: fprintf(ficresprob, "**********\n#\n");
6160: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6161: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6162: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6163:
1.222 brouard 6164: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6165: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6166: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6167:
6168:
1.222 brouard 6169: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6170: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6171: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6172:
1.222 brouard 6173: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6174: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6175: fprintf(ficresprobcor, "**********\n#");
6176: if(invalidvarcomb[j1]){
6177: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6178: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6179: continue;
6180: }
6181: }
6182: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6183: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6184: gp=vector(1,(nlstate)*(nlstate+ndeath));
6185: gm=vector(1,(nlstate)*(nlstate+ndeath));
6186: for (age=bage; age<=fage; age ++){
6187: cov[2]=age;
6188: if(nagesqr==1)
6189: cov[3]= age*age;
6190: for (k=1; k<=cptcovn;k++) {
6191: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6192: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6193: * 1 1 1 1 1
6194: * 2 2 1 1 1
6195: * 3 1 2 1 1
6196: */
6197: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6198: }
6199: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6200: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6201: for (k=1; k<=cptcovprod;k++)
6202: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6203:
6204:
1.222 brouard 6205: for(theta=1; theta <=npar; theta++){
6206: for(i=1; i<=npar; i++)
6207: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6208:
1.222 brouard 6209: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6210:
1.222 brouard 6211: k=0;
6212: for(i=1; i<= (nlstate); i++){
6213: for(j=1; j<=(nlstate+ndeath);j++){
6214: k=k+1;
6215: gp[k]=pmmij[i][j];
6216: }
6217: }
1.220 brouard 6218:
1.222 brouard 6219: for(i=1; i<=npar; i++)
6220: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6221:
1.222 brouard 6222: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6223: k=0;
6224: for(i=1; i<=(nlstate); i++){
6225: for(j=1; j<=(nlstate+ndeath);j++){
6226: k=k+1;
6227: gm[k]=pmmij[i][j];
6228: }
6229: }
1.220 brouard 6230:
1.222 brouard 6231: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6232: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6233: }
1.126 brouard 6234:
1.222 brouard 6235: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6236: for(theta=1; theta <=npar; theta++)
6237: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6238:
1.222 brouard 6239: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6240: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6241:
1.222 brouard 6242: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6243:
1.222 brouard 6244: k=0;
6245: for(i=1; i<=(nlstate); i++){
6246: for(j=1; j<=(nlstate+ndeath);j++){
6247: k=k+1;
6248: mu[k][(int) age]=pmmij[i][j];
6249: }
6250: }
6251: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6252: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6253: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6254:
1.222 brouard 6255: /*printf("\n%d ",(int)age);
6256: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6257: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6258: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6259: }*/
1.220 brouard 6260:
1.222 brouard 6261: fprintf(ficresprob,"\n%d ",(int)age);
6262: fprintf(ficresprobcov,"\n%d ",(int)age);
6263: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6264:
1.222 brouard 6265: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6266: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6267: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6268: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6269: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6270: }
6271: i=0;
6272: for (k=1; k<=(nlstate);k++){
6273: for (l=1; l<=(nlstate+ndeath);l++){
6274: i++;
6275: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6276: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6277: for (j=1; j<=i;j++){
6278: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6279: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6280: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6281: }
6282: }
6283: }/* end of loop for state */
6284: } /* end of loop for age */
6285: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6286: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6287: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6288: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6289:
6290: /* Confidence intervalle of pij */
6291: /*
6292: fprintf(ficgp,"\nunset parametric;unset label");
6293: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6294: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6295: 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);
6296: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6297: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6298: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6299: */
6300:
6301: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6302: first1=1;first2=2;
6303: for (k2=1; k2<=(nlstate);k2++){
6304: for (l2=1; l2<=(nlstate+ndeath);l2++){
6305: if(l2==k2) continue;
6306: j=(k2-1)*(nlstate+ndeath)+l2;
6307: for (k1=1; k1<=(nlstate);k1++){
6308: for (l1=1; l1<=(nlstate+ndeath);l1++){
6309: if(l1==k1) continue;
6310: i=(k1-1)*(nlstate+ndeath)+l1;
6311: if(i<=j) continue;
6312: for (age=bage; age<=fage; age ++){
6313: if ((int)age %5==0){
6314: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6315: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6316: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6317: mu1=mu[i][(int) age]/stepm*YEARM ;
6318: mu2=mu[j][(int) age]/stepm*YEARM;
6319: c12=cv12/sqrt(v1*v2);
6320: /* Computing eigen value of matrix of covariance */
6321: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6322: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6323: if ((lc2 <0) || (lc1 <0) ){
6324: if(first2==1){
6325: first1=0;
6326: 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);
6327: }
6328: 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);
6329: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6330: /* lc2=fabs(lc2); */
6331: }
1.220 brouard 6332:
1.222 brouard 6333: /* Eigen vectors */
6334: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
6335: /*v21=sqrt(1.-v11*v11); *//* error */
6336: v21=(lc1-v1)/cv12*v11;
6337: v12=-v21;
6338: v22=v11;
6339: tnalp=v21/v11;
6340: if(first1==1){
6341: first1=0;
6342: 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);
6343: }
6344: 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);
6345: /*printf(fignu*/
6346: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6347: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6348: if(first==1){
6349: first=0;
6350: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6351: fprintf(ficgp,"\nset parametric;unset label");
6352: 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);
6353: fprintf(ficgp,"\nset ter svg size 640, 480");
6354: fprintf(fichtmcov,"\n<br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6355: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6356: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6357: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6358: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6359: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6360: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6361: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6362: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6363: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6364: 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", \
6365: mu1,std,v11,sqrt(lc1),v12,sqrt(lc2), \
6366: mu2,std,v21,sqrt(lc1),v22,sqrt(lc2));
6367: }else{
6368: first=0;
6369: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6370: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6371: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6372: 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", \
6373: mu1,std,v11,sqrt(lc1),v12,sqrt(lc2), \
6374: mu2,std,v21,sqrt(lc1),v22,sqrt(lc2));
6375: }/* if first */
6376: } /* age mod 5 */
6377: } /* end loop age */
6378: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6379: first=1;
6380: } /*l12 */
6381: } /* k12 */
6382: } /*l1 */
6383: }/* k1 */
6384: } /* loop on combination of covariates j1 */
6385: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6386: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6387: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6388: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6389: free_vector(xp,1,npar);
6390: fclose(ficresprob);
6391: fclose(ficresprobcov);
6392: fclose(ficresprobcor);
6393: fflush(ficgp);
6394: fflush(fichtmcov);
6395: }
1.126 brouard 6396:
6397:
6398: /******************* Printing html file ***********/
1.201 brouard 6399: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6400: int lastpass, int stepm, int weightopt, char model[],\
6401: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.258 brouard 6402: int popforecast, int mobilav, int prevfcast, int mobilavproj, int backcast, int estepm , \
1.213 brouard 6403: double jprev1, double mprev1,double anprev1, double dateprev1, \
6404: double jprev2, double mprev2,double anprev2, double dateprev2){
1.237 brouard 6405: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6406:
6407: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6408: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6409: </ul>");
1.237 brouard 6410: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6411: </ul>", model);
1.214 brouard 6412: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6413: 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",
6414: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6415: 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 6416: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6417: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6418: fprintf(fichtm,"\
6419: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6420: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6421: fprintf(fichtm,"\
1.217 brouard 6422: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6423: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6424: fprintf(fichtm,"\
1.126 brouard 6425: - Period (stable) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6426: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6427: fprintf(fichtm,"\
1.217 brouard 6428: - Period (stable) back prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
6429: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6430: fprintf(fichtm,"\
1.211 brouard 6431: - (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 6432: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6433: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6434: if(prevfcast==1){
6435: fprintf(fichtm,"\
6436: - Prevalence projections by age and states: \
1.201 brouard 6437: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6438: }
1.126 brouard 6439:
6440:
1.225 brouard 6441: m=pow(2,cptcoveff);
1.222 brouard 6442: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6443:
1.264 ! brouard 6444: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
! 6445:
! 6446: jj1=0;
! 6447:
! 6448: fprintf(fichtm," \n<ul>");
! 6449: for(nres=1; nres <= nresult; nres++) /* For each resultline */
! 6450: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
! 6451: if(m != 1 && TKresult[nres]!= k1)
! 6452: continue;
! 6453: jj1++;
! 6454: if (cptcovn > 0) {
! 6455: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
! 6456: for (cpt=1; cpt<=cptcoveff;cpt++){
! 6457: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
! 6458: }
! 6459: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
! 6460: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
! 6461: }
! 6462: fprintf(fichtm,"\">");
! 6463:
! 6464: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
! 6465: fprintf(fichtm,"************ Results for covariates");
! 6466: for (cpt=1; cpt<=cptcoveff;cpt++){
! 6467: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
! 6468: }
! 6469: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
! 6470: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
! 6471: }
! 6472: if(invalidvarcomb[k1]){
! 6473: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
! 6474: continue;
! 6475: }
! 6476: fprintf(fichtm,"</a></li>");
! 6477: } /* cptcovn >0 */
! 6478: }
! 6479: fprintf(fichtm," \n</ul>");
! 6480:
1.222 brouard 6481: jj1=0;
1.237 brouard 6482:
6483: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6484: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6485: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6486: continue;
1.220 brouard 6487:
1.222 brouard 6488: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6489: jj1++;
6490: if (cptcovn > 0) {
1.264 ! brouard 6491: fprintf(fichtm,"\n<p><a name=\"rescov");
! 6492: for (cpt=1; cpt<=cptcoveff;cpt++){
! 6493: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
! 6494: }
! 6495: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
! 6496: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
! 6497: }
! 6498: fprintf(fichtm,"\"</a>");
! 6499:
1.222 brouard 6500: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6501: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6502: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6503: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6504: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6505: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6506: }
1.237 brouard 6507: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6508: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6509: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6510: }
6511:
1.230 brouard 6512: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6513: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6514: if(invalidvarcomb[k1]){
6515: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6516: printf("\nCombination (%d) ignored because no cases \n",k1);
6517: continue;
6518: }
6519: }
6520: /* aij, bij */
1.259 brouard 6521: 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 6522: <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 6523: /* Pij */
1.241 brouard 6524: 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> \
6525: <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 6526: /* Quasi-incidences */
6527: 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 6528: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6529: 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 6530: 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> \
6531: <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 6532: /* Survival functions (period) in state j */
6533: for(cpt=1; cpt<=nlstate;cpt++){
1.241 brouard 6534: 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> \
6535: <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 6536: }
6537: /* State specific survival functions (period) */
6538: for(cpt=1; cpt<=nlstate;cpt++){
6539: fprintf(fichtm,"<br>\n- Survival functions from state %d in each live state and total.\
1.220 brouard 6540: Or probability to survive in various states (1 to %d) being in state %d at different ages. \
1.241 brouard 6541: <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 6542: }
6543: /* Period (stable) prevalence in each health state */
6544: for(cpt=1; cpt<=nlstate;cpt++){
1.264 ! brouard 6545: 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> \
! 6546: <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 6547: }
6548: if(backcast==1){
6549: /* Period (stable) back prevalence in each health state */
6550: for(cpt=1; cpt<=nlstate;cpt++){
1.264 ! brouard 6551: 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 6552: <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 6553: }
1.217 brouard 6554: }
1.222 brouard 6555: if(prevfcast==1){
6556: /* Projection of prevalence up to period (stable) prevalence in each health state */
6557: for(cpt=1; cpt<=nlstate;cpt++){
1.258 brouard 6558: fprintf(fichtm,"<br>\n- Projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d) up to period (stable) prevalence in state %d. Or probability to be 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> \
6559: <img src=\"%s_%d-%d-%d.svg\">", dateprev1, dateprev2, mobilavproj, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 6560: }
6561: }
1.220 brouard 6562:
1.222 brouard 6563: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 6564: 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> \
6565: <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 6566: }
6567: /* } /\* end i1 *\/ */
6568: }/* End k1 */
6569: fprintf(fichtm,"</ul>");
1.126 brouard 6570:
1.222 brouard 6571: fprintf(fichtm,"\
1.126 brouard 6572: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 6573: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 6574: - 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 6575: But because parameters are usually highly correlated (a higher incidence of disability \
6576: and a higher incidence of recovery can give very close observed transition) it might \
6577: be very useful to look not only at linear confidence intervals estimated from the \
6578: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
6579: (parameters) of the logistic regression, it might be more meaningful to visualize the \
6580: covariance matrix of the one-step probabilities. \
6581: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 6582:
1.222 brouard 6583: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
6584: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
6585: fprintf(fichtm,"\
1.126 brouard 6586: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6587: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 6588:
1.222 brouard 6589: fprintf(fichtm,"\
1.126 brouard 6590: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6591: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
6592: fprintf(fichtm,"\
1.126 brouard 6593: - 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): \
6594: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6595: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 6596: fprintf(fichtm,"\
1.126 brouard 6597: - (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): \
6598: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6599: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 6600: fprintf(fichtm,"\
1.128 brouard 6601: - Variances and covariances of health expectancies by age. Status (i) based health expectancies (in state j), e<sup>ij</sup> are weighted by the period prevalences in each state i (if popbased=1, an additional computation is done using the cross-sectional prevalences, i.e population based) (estepm=%d months): <a href=\"%s\">%s</a><br>\n",
1.222 brouard 6602: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
6603: fprintf(fichtm,"\
1.128 brouard 6604: - 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 6605: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
6606: fprintf(fichtm,"\
1.126 brouard 6607: - Standard deviation of period (stable) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 6608: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 6609:
6610: /* if(popforecast==1) fprintf(fichtm,"\n */
6611: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
6612: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
6613: /* <br>",fileres,fileres,fileres,fileres); */
6614: /* else */
6615: /* 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 6616: fflush(fichtm);
6617: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 6618:
1.225 brouard 6619: m=pow(2,cptcoveff);
1.222 brouard 6620: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6621:
1.222 brouard 6622: jj1=0;
1.237 brouard 6623:
1.241 brouard 6624: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 6625: for(k1=1; k1<=m;k1++){
1.253 brouard 6626: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6627: continue;
1.222 brouard 6628: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6629: jj1++;
1.126 brouard 6630: if (cptcovn > 0) {
6631: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6632: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 6633: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
6634: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6635: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6636: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6637: }
6638:
1.126 brouard 6639: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6640:
1.222 brouard 6641: if(invalidvarcomb[k1]){
6642: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
6643: continue;
6644: }
1.126 brouard 6645: }
6646: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 6647: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 6648: 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 6649: <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 6650: }
6651: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 6652: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
6653: true period expectancies (those weighted with period prevalences are also\
6654: drawn in addition to the population based expectancies computed using\
1.241 brouard 6655: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
6656: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 6657: /* } /\* end i1 *\/ */
6658: }/* End k1 */
1.241 brouard 6659: }/* End nres */
1.222 brouard 6660: fprintf(fichtm,"</ul>");
6661: fflush(fichtm);
1.126 brouard 6662: }
6663:
6664: /******************* Gnuplot file **************/
1.223 brouard 6665: void printinggnuplot(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , int prevfcast, int backcast, char pathc[], double p[]){
1.126 brouard 6666:
6667: char dirfileres[132],optfileres[132];
1.264 ! brouard 6668: char gplotcondition[132], gplotlabel[132];
1.237 brouard 6669: 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 6670: int lv=0, vlv=0, kl=0;
1.130 brouard 6671: int ng=0;
1.201 brouard 6672: int vpopbased;
1.223 brouard 6673: int ioffset; /* variable offset for columns */
1.235 brouard 6674: int nres=0; /* Index of resultline */
1.219 brouard 6675:
1.126 brouard 6676: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
6677: /* printf("Problem with file %s",optionfilegnuplot); */
6678: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
6679: /* } */
6680:
6681: /*#ifdef windows */
6682: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 6683: /*#endif */
1.225 brouard 6684: m=pow(2,cptcoveff);
1.126 brouard 6685:
1.202 brouard 6686: /* Contribution to likelihood */
6687: /* Plot the probability implied in the likelihood */
1.223 brouard 6688: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
6689: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
6690: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
6691: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 6692: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 6693: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
6694: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 6695: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
6696: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
6697: 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));
6698: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
6699: 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));
6700: for (i=1; i<= nlstate ; i ++) {
6701: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
6702: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
6703: 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);
6704: for (j=2; j<= nlstate+ndeath ; j ++) {
6705: 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);
6706: }
6707: fprintf(ficgp,";\nset out; unset ylabel;\n");
6708: }
6709: /* 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 */
6710: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
6711: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
6712: fprintf(ficgp,"\nset out;unset log\n");
6713: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 6714:
1.126 brouard 6715: strcpy(dirfileres,optionfilefiname);
6716: strcpy(optfileres,"vpl");
1.223 brouard 6717: /* 1eme*/
1.238 brouard 6718: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
6719: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 6720: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 6721: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 6722: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 6723: continue;
6724: /* We are interested in selected combination by the resultline */
1.246 brouard 6725: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.238 brouard 6726: fprintf(ficgp,"\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 ! brouard 6727: strcpy(gplotlabel,"(");
1.238 brouard 6728: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
6729: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
6730: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6731: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6732: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6733: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
6734: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 6735: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 6736: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 ! brouard 6737: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 6738: }
6739: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 6740: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 6741: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 ! brouard 6742: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
! 6743: }
! 6744: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 6745: /* printf("\n#\n"); */
1.238 brouard 6746: fprintf(ficgp,"\n#\n");
6747: if(invalidvarcomb[k1]){
1.260 brouard 6748: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 6749: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
6750: continue;
6751: }
1.235 brouard 6752:
1.241 brouard 6753: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
6754: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.264 ! brouard 6755: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.260 brouard 6756: 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);
6757: /* 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); */
6758: /* k1-1 error should be nres-1*/
1.238 brouard 6759: for (i=1; i<= nlstate ; i ++) {
6760: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
6761: else fprintf(ficgp," %%*lf (%%*lf)");
6762: }
1.260 brouard 6763: fprintf(ficgp,"\" t\"Period (stable) prevalence\" w l lt 0,\"%s\" every :::%d::%d u 1:($2==%d ? $3+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 6764: for (i=1; i<= nlstate ; i ++) {
6765: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
6766: else fprintf(ficgp," %%*lf (%%*lf)");
6767: }
1.260 brouard 6768: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 6769: for (i=1; i<= nlstate ; i ++) {
6770: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
6771: else fprintf(ficgp," %%*lf (%%*lf)");
6772: }
6773: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1));
6774: if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
6775: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 6776: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 6777: if(cptcoveff ==0){
1.245 brouard 6778: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 6779: }else{
6780: kl=0;
6781: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
6782: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
6783: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6784: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6785: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6786: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 6787: kl++;
1.238 brouard 6788: /* 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 *\/ */
6789: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
6790: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
6791: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
6792: if(k==cptcoveff){
1.245 brouard 6793: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 6794: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 6795: }else{
6796: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
6797: kl++;
6798: }
6799: } /* end covariate */
6800: } /* end if no covariate */
6801: } /* end if backcast */
1.264 ! brouard 6802: fprintf(ficgp,"\nset out ;unset label;\n");
1.238 brouard 6803: } /* nres */
1.201 brouard 6804: } /* k1 */
6805: } /* cpt */
1.235 brouard 6806:
6807:
1.126 brouard 6808: /*2 eme*/
1.238 brouard 6809: for (k1=1; k1<= m ; k1 ++){
6810: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 6811: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 6812: continue;
6813: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 ! brouard 6814: strcpy(gplotlabel,"(");
1.238 brouard 6815: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 6816: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 6817: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6818: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6819: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6820: vlv= nbcode[Tvaraff[k]][lv];
6821: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 ! brouard 6822: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 6823: }
1.237 brouard 6824: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 6825: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 6826: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 6827: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 ! brouard 6828: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 6829: }
1.264 ! brouard 6830: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 6831: fprintf(ficgp,"\n#\n");
1.223 brouard 6832: if(invalidvarcomb[k1]){
6833: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
6834: continue;
6835: }
1.219 brouard 6836:
1.241 brouard 6837: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 6838: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 ! brouard 6839: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
! 6840: if(vpopbased==0){
1.238 brouard 6841: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 ! brouard 6842: }else
1.238 brouard 6843: fprintf(ficgp,"\nreplot ");
6844: for (i=1; i<= nlstate+1 ; i ++) {
6845: k=2*i;
1.261 brouard 6846: 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 6847: for (j=1; j<= nlstate+1 ; j ++) {
6848: if (j==i) fprintf(ficgp," %%lf (%%lf)");
6849: else fprintf(ficgp," %%*lf (%%*lf)");
6850: }
6851: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
6852: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 6853: 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 6854: for (j=1; j<= nlstate+1 ; j ++) {
6855: if (j==i) fprintf(ficgp," %%lf (%%lf)");
6856: else fprintf(ficgp," %%*lf (%%*lf)");
6857: }
6858: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 6859: 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 6860: for (j=1; j<= nlstate+1 ; j ++) {
6861: if (j==i) fprintf(ficgp," %%lf (%%lf)");
6862: else fprintf(ficgp," %%*lf (%%*lf)");
6863: }
6864: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
6865: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
6866: } /* state */
6867: } /* vpopbased */
1.264 ! brouard 6868: 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 6869: } /* end nres */
6870: } /* k1 end 2 eme*/
6871:
6872:
6873: /*3eme*/
6874: for (k1=1; k1<= m ; k1 ++){
6875: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 6876: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 6877: continue;
6878:
6879: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 6880: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 ! brouard 6881: strcpy(gplotlabel,"(");
1.238 brouard 6882: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
6883: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
6884: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6885: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6886: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6887: vlv= nbcode[Tvaraff[k]][lv];
6888: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 ! brouard 6889: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 6890: }
6891: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6892: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 ! brouard 6893: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 6894: }
1.264 ! brouard 6895: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 6896: fprintf(ficgp,"\n#\n");
6897: if(invalidvarcomb[k1]){
6898: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
6899: continue;
6900: }
6901:
6902: /* k=2+nlstate*(2*cpt-2); */
6903: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 6904: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 ! brouard 6905: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 6906: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 6907: 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 6908: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
6909: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
6910: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
6911: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
6912: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
6913: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 6914:
1.238 brouard 6915: */
6916: for (i=1; i< nlstate ; i ++) {
1.261 brouard 6917: 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 6918: /* 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 6919:
1.238 brouard 6920: }
1.261 brouard 6921: 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 6922: }
1.264 ! brouard 6923: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 6924: } /* end nres */
6925: } /* end kl 3eme */
1.126 brouard 6926:
1.223 brouard 6927: /* 4eme */
1.201 brouard 6928: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 6929: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
6930: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 6931: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 6932: continue;
1.238 brouard 6933: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 ! brouard 6934: strcpy(gplotlabel,"(");
1.238 brouard 6935: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
6936: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
6937: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
6938: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6939: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6940: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6941: vlv= nbcode[Tvaraff[k]][lv];
6942: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 ! brouard 6943: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 6944: }
6945: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6946: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 ! brouard 6947: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 6948: }
1.264 ! brouard 6949: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 6950: fprintf(ficgp,"\n#\n");
6951: if(invalidvarcomb[k1]){
6952: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
6953: continue;
1.223 brouard 6954: }
1.238 brouard 6955:
1.241 brouard 6956: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 ! brouard 6957: 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 6958: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
6959: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
6960: k=3;
6961: for (i=1; i<= nlstate ; i ++){
6962: if(i==1){
6963: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
6964: }else{
6965: fprintf(ficgp,", '' ");
6966: }
6967: l=(nlstate+ndeath)*(i-1)+1;
6968: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
6969: for (j=2; j<= nlstate+ndeath ; j ++)
6970: fprintf(ficgp,"+$%d",k+l+j-1);
6971: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
6972: } /* nlstate */
1.264 ! brouard 6973: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 6974: } /* end cpt state*/
6975: } /* end nres */
6976: } /* end covariate k1 */
6977:
1.220 brouard 6978: /* 5eme */
1.201 brouard 6979: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 6980: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
6981: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 6982: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 6983: continue;
1.238 brouard 6984: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 ! brouard 6985: strcpy(gplotlabel,"(");
1.238 brouard 6986: 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);
6987: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
6988: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
6989: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6990: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6991: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6992: vlv= nbcode[Tvaraff[k]][lv];
6993: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 ! brouard 6994: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 6995: }
6996: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6997: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 ! brouard 6998: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 6999: }
1.264 ! brouard 7000: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7001: fprintf(ficgp,"\n#\n");
7002: if(invalidvarcomb[k1]){
7003: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7004: continue;
7005: }
1.227 brouard 7006:
1.241 brouard 7007: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 ! brouard 7008: 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 7009: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7010: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7011: k=3;
7012: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7013: if(j==1)
7014: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7015: else
7016: fprintf(ficgp,", '' ");
7017: l=(nlstate+ndeath)*(cpt-1) +j;
7018: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7019: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7020: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7021: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7022: } /* nlstate */
7023: fprintf(ficgp,", '' ");
7024: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7025: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7026: l=(nlstate+ndeath)*(cpt-1) +j;
7027: if(j < nlstate)
7028: fprintf(ficgp,"$%d +",k+l);
7029: else
7030: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7031: }
1.264 ! brouard 7032: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7033: } /* end cpt state*/
7034: } /* end covariate */
7035: } /* end nres */
1.227 brouard 7036:
1.220 brouard 7037: /* 6eme */
1.202 brouard 7038: /* CV preval stable (period) for each covariate */
1.237 brouard 7039: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7040: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7041: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7042: continue;
1.255 brouard 7043: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 ! brouard 7044: strcpy(gplotlabel,"(");
1.211 brouard 7045: fprintf(ficgp,"\n#\n#\n#CV preval stable (period): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7046: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7047: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7048: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7049: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7050: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7051: vlv= nbcode[Tvaraff[k]][lv];
7052: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 ! brouard 7053: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7054: }
1.237 brouard 7055: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7056: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 ! brouard 7057: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7058: }
1.264 ! brouard 7059: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7060: fprintf(ficgp,"\n#\n");
1.223 brouard 7061: if(invalidvarcomb[k1]){
1.227 brouard 7062: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7063: continue;
1.223 brouard 7064: }
1.227 brouard 7065:
1.241 brouard 7066: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 ! brouard 7067: 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 7068: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7069: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7070: k=3; /* Offset */
1.255 brouard 7071: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7072: if(i==1)
7073: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7074: else
7075: fprintf(ficgp,", '' ");
1.255 brouard 7076: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7077: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7078: for (j=2; j<= nlstate ; j ++)
7079: fprintf(ficgp,"+$%d",k+l+j-1);
7080: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7081: } /* nlstate */
1.264 ! brouard 7082: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7083: } /* end cpt state*/
7084: } /* end covariate */
1.227 brouard 7085:
7086:
1.220 brouard 7087: /* 7eme */
1.218 brouard 7088: if(backcast == 1){
1.217 brouard 7089: /* CV back preval stable (period) for each covariate */
1.237 brouard 7090: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7091: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7092: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7093: continue;
1.255 brouard 7094: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life ending state */
1.264 ! brouard 7095: strcpy(gplotlabel,"(");
! 7096: fprintf(ficgp,"\n#\n#\n#CV Back preval stable (period): 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7097: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7098: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7099: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7100: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7101: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7102: vlv= nbcode[Tvaraff[k]][lv];
7103: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 ! brouard 7104: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7105: }
1.237 brouard 7106: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7107: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 ! brouard 7108: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7109: }
1.264 ! brouard 7110: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7111: fprintf(ficgp,"\n#\n");
7112: if(invalidvarcomb[k1]){
7113: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7114: continue;
7115: }
7116:
1.241 brouard 7117: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.264 ! brouard 7118: fprintf(ficgp,"set label \"Ending alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.227 brouard 7119: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7120: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7121: k=3; /* Offset */
1.255 brouard 7122: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7123: if(i==1)
7124: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7125: else
7126: fprintf(ficgp,", '' ");
7127: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7128: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7129: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7130: /* 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 7131: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7132: /* for (j=2; j<= nlstate ; j ++) */
7133: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7134: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
7135: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",i,cpt);
7136: } /* nlstate */
1.264 ! brouard 7137: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7138: } /* end cpt state*/
7139: } /* end covariate */
7140: } /* End if backcast */
7141:
1.223 brouard 7142: /* 8eme */
1.218 brouard 7143: if(prevfcast==1){
7144: /* Projection from cross-sectional to stable (period) for each covariate */
7145:
1.237 brouard 7146: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7147: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7148: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7149: continue;
1.211 brouard 7150: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 ! brouard 7151: strcpy(gplotlabel,"(");
1.227 brouard 7152: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to stable (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
7153: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7154: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7155: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7156: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7157: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7158: vlv= nbcode[Tvaraff[k]][lv];
7159: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 ! brouard 7160: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7161: }
1.237 brouard 7162: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7163: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 ! brouard 7164: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7165: }
1.264 ! brouard 7166: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7167: fprintf(ficgp,"\n#\n");
7168: if(invalidvarcomb[k1]){
7169: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7170: continue;
7171: }
7172:
7173: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7174: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 ! brouard 7175: 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 7176: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7177: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7178: for (i=1; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7179: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7180: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7181: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7182: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7183: if(i==1){
7184: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7185: }else{
7186: fprintf(ficgp,",\\\n '' ");
7187: }
7188: if(cptcoveff ==0){ /* No covariate */
7189: ioffset=2; /* Age is in 2 */
7190: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7191: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7192: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7193: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7194: fprintf(ficgp," u %d:(", ioffset);
7195: if(i==nlstate+1)
7196: fprintf(ficgp," $%d/(1.-$%d)) t 'pw.%d' with line ", \
7197: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7198: else
7199: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7200: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7201: }else{ /* more than 2 covariates */
7202: if(cptcoveff ==1){
7203: ioffset=4; /* Age is in 4 */
7204: }else{
7205: ioffset=6; /* Age is in 6 */
7206: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7207: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7208: }
7209: fprintf(ficgp," u %d:(",ioffset);
7210: kl=0;
7211: strcpy(gplotcondition,"(");
7212: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7213: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7214: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7215: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7216: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7217: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7218: kl++;
7219: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7220: kl++;
7221: if(k <cptcoveff && cptcoveff>1)
7222: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7223: }
7224: strcpy(gplotcondition+strlen(gplotcondition),")");
7225: /* 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 *\/ */
7226: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7227: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7228: /* '' 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*/
7229: if(i==nlstate+1){
7230: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p.%d' with line ", gplotcondition, \
7231: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7232: }else{
7233: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7234: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7235: }
7236: } /* end if covariate */
7237: } /* nlstate */
1.264 ! brouard 7238: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7239: } /* end cpt state*/
7240: } /* end covariate */
7241: } /* End if prevfcast */
1.227 brouard 7242:
7243:
1.238 brouard 7244: /* 9eme writing MLE parameters */
7245: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7246: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7247: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7248: for(k=1; k <=(nlstate+ndeath); k++){
7249: if (k != i) {
1.227 brouard 7250: fprintf(ficgp,"# current state %d\n",k);
7251: for(j=1; j <=ncovmodel; j++){
7252: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7253: jk++;
7254: }
7255: fprintf(ficgp,"\n");
1.126 brouard 7256: }
7257: }
1.223 brouard 7258: }
1.187 brouard 7259: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7260:
1.145 brouard 7261: /*goto avoid;*/
1.238 brouard 7262: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7263: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7264: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7265: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7266: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7267: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7268: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7269: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7270: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7271: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7272: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7273: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7274: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7275: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7276: fprintf(ficgp,"#\n");
1.223 brouard 7277: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7278: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7279: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7280: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 ! brouard 7281: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
! 7282: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7283: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 ! brouard 7284: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7285: continue;
1.264 ! brouard 7286: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
! 7287: strcpy(gplotlabel,"(");
! 7288: sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);
! 7289: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
! 7290: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
! 7291: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
! 7292: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
! 7293: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
! 7294: vlv= nbcode[Tvaraff[k]][lv];
! 7295: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
! 7296: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
! 7297: }
1.237 brouard 7298: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7299: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 ! brouard 7300: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7301: }
1.264 ! brouard 7302: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7303: fprintf(ficgp,"\n#\n");
1.264 ! brouard 7304: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
! 7305: fprintf(ficgp,"\nset label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7306: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7307: if (ng==1){
7308: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7309: fprintf(ficgp,"\nunset log y");
7310: }else if (ng==2){
7311: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7312: fprintf(ficgp,"\nset log y");
7313: }else if (ng==3){
7314: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7315: fprintf(ficgp,"\nset log y");
7316: }else
7317: fprintf(ficgp,"\nunset title ");
7318: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7319: i=1;
7320: for(k2=1; k2<=nlstate; k2++) {
7321: k3=i;
7322: for(k=1; k<=(nlstate+ndeath); k++) {
7323: if (k != k2){
7324: switch( ng) {
7325: case 1:
7326: if(nagesqr==0)
7327: fprintf(ficgp," p%d+p%d*x",i,i+1);
7328: else /* nagesqr =1 */
7329: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7330: break;
7331: case 2: /* ng=2 */
7332: if(nagesqr==0)
7333: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
7334: else /* nagesqr =1 */
7335: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7336: break;
7337: case 3:
7338: if(nagesqr==0)
7339: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
7340: else /* nagesqr =1 */
7341: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
7342: break;
7343: }
7344: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 7345: ijp=1; /* product no age */
7346: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
7347: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 7348: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.237 brouard 7349: if(j==Tage[ij]) { /* Product by age */
7350: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
1.238 brouard 7351: if(DummyV[j]==0){
1.237 brouard 7352: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
7353: }else{ /* quantitative */
7354: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
1.264 ! brouard 7355: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.237 brouard 7356: }
7357: ij++;
7358: }
7359: }else if(j==Tprod[ijp]) { /* */
7360: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
7361: if(ijp <=cptcovprod) { /* Product */
1.238 brouard 7362: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
7363: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
1.264 ! brouard 7364: /* 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)]); */
1.237 brouard 7365: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
7366: }else{ /* Vn is dummy and Vm is quanti */
1.264 ! brouard 7367: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
1.237 brouard 7368: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7369: }
7370: }else{ /* Vn*Vm Vn is quanti */
1.238 brouard 7371: if(DummyV[Tvard[ijp][2]]==0){
1.237 brouard 7372: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
7373: }else{ /* Both quanti */
7374: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7375: }
7376: }
1.238 brouard 7377: ijp++;
1.237 brouard 7378: }
7379: } else{ /* simple covariate */
1.264 ! brouard 7380: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 7381: if(Dummy[j]==0){
7382: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
7383: }else{ /* quantitative */
7384: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 ! brouard 7385: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 7386: }
1.237 brouard 7387: } /* end simple */
7388: } /* end j */
1.223 brouard 7389: }else{
7390: i=i-ncovmodel;
7391: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
7392: fprintf(ficgp," (1.");
7393: }
1.227 brouard 7394:
1.223 brouard 7395: if(ng != 1){
7396: fprintf(ficgp,")/(1");
1.227 brouard 7397:
1.264 ! brouard 7398: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 7399: if(nagesqr==0)
1.264 ! brouard 7400: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 7401: else /* nagesqr =1 */
1.264 ! brouard 7402: 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 7403:
1.223 brouard 7404: ij=1;
7405: for(j=3; j <=ncovmodel-nagesqr; j++){
1.237 brouard 7406: if((j-2)==Tage[ij]) { /* Bug valgrind */
7407: if(ij <=cptcovage) { /* Bug valgrind */
1.264 ! brouard 7408: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
! 7409: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 7410: ij++;
7411: }
7412: }
7413: else
1.264 ! brouard 7414: 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 7415: }
7416: fprintf(ficgp,")");
7417: }
7418: fprintf(ficgp,")");
7419: if(ng ==2)
7420: fprintf(ficgp," t \"p%d%d\" ", k2,k);
7421: else /* ng= 3 */
7422: fprintf(ficgp," t \"i%d%d\" ", k2,k);
7423: }else{ /* end ng <> 1 */
7424: if( k !=k2) /* logit p11 is hard to draw */
7425: fprintf(ficgp," t \"logit(p%d%d)\" ", k2,k);
7426: }
7427: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
7428: fprintf(ficgp,",");
7429: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
7430: fprintf(ficgp,",");
7431: i=i+ncovmodel;
7432: } /* end k */
7433: } /* end k2 */
1.264 ! brouard 7434: fprintf(ficgp,"\n set out; unset label;\n");
! 7435: } /* end k1 */
1.223 brouard 7436: } /* end ng */
7437: /* avoid: */
7438: fflush(ficgp);
1.126 brouard 7439: } /* end gnuplot */
7440:
7441:
7442: /*************** Moving average **************/
1.219 brouard 7443: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 7444: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 7445:
1.222 brouard 7446: int i, cpt, cptcod;
7447: int modcovmax =1;
7448: int mobilavrange, mob;
7449: int iage=0;
7450:
7451: double sum=0.;
7452: double age;
7453: double *sumnewp, *sumnewm;
7454: double *agemingood, *agemaxgood; /* Currently identical for all covariates */
7455:
7456:
1.225 brouard 7457: /* modcovmax=2*cptcoveff;/\* Max number of modalities. We suppose */
1.222 brouard 7458: /* a covariate has 2 modalities, should be equal to ncovcombmax *\/ */
7459:
7460: sumnewp = vector(1,ncovcombmax);
7461: sumnewm = vector(1,ncovcombmax);
7462: agemingood = vector(1,ncovcombmax);
7463: agemaxgood = vector(1,ncovcombmax);
7464:
7465: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
7466: sumnewm[cptcod]=0.;
7467: sumnewp[cptcod]=0.;
7468: agemingood[cptcod]=0;
7469: agemaxgood[cptcod]=0;
7470: }
7471: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
7472:
7473: if(mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
7474: if(mobilav==1) mobilavrange=5; /* default */
7475: else mobilavrange=mobilav;
7476: for (age=bage; age<=fage; age++)
7477: for (i=1; i<=nlstate;i++)
7478: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
7479: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
7480: /* We keep the original values on the extreme ages bage, fage and for
7481: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
7482: we use a 5 terms etc. until the borders are no more concerned.
7483: */
7484: for (mob=3;mob <=mobilavrange;mob=mob+2){
7485: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
7486: for (i=1; i<=nlstate;i++){
7487: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
7488: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
7489: for (cpt=1;cpt<=(mob-1)/2;cpt++){
7490: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
7491: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
7492: }
7493: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
7494: }
7495: }
7496: }/* end age */
7497: }/* end mob */
7498: }else
7499: return -1;
7500: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
7501: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
7502: if(invalidvarcomb[cptcod]){
7503: printf("\nCombination (%d) ignored because no cases \n",cptcod);
7504: continue;
7505: }
1.219 brouard 7506:
1.222 brouard 7507: agemingood[cptcod]=fage-(mob-1)/2;
7508: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, finding the youngest wrong */
7509: sumnewm[cptcod]=0.;
7510: for (i=1; i<=nlstate;i++){
7511: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7512: }
7513: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
7514: agemingood[cptcod]=age;
7515: }else{ /* bad */
7516: for (i=1; i<=nlstate;i++){
7517: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
7518: } /* i */
7519: } /* end bad */
7520: }/* age */
7521: sum=0.;
7522: for (i=1; i<=nlstate;i++){
7523: sum+=mobaverage[(int)agemingood[cptcod]][i][cptcod];
7524: }
7525: if(fabs(sum - 1.) > 1.e-3) { /* bad */
7526: printf("For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one at any descending age!\n",cptcod);
7527: /* for (i=1; i<=nlstate;i++){ */
7528: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
7529: /* } /\* i *\/ */
7530: } /* end bad */
7531: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
7532: /* From youngest, finding the oldest wrong */
7533: agemaxgood[cptcod]=bage+(mob-1)/2;
7534: for (age=bage+(mob-1)/2; age<=fage; age++){
7535: sumnewm[cptcod]=0.;
7536: for (i=1; i<=nlstate;i++){
7537: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7538: }
7539: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
7540: agemaxgood[cptcod]=age;
7541: }else{ /* bad */
7542: for (i=1; i<=nlstate;i++){
7543: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
7544: } /* i */
7545: } /* end bad */
7546: }/* age */
7547: sum=0.;
7548: for (i=1; i<=nlstate;i++){
7549: sum+=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
7550: }
7551: if(fabs(sum - 1.) > 1.e-3) { /* bad */
7552: printf("For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one at any ascending age!\n",cptcod);
7553: /* for (i=1; i<=nlstate;i++){ */
7554: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
7555: /* } /\* i *\/ */
7556: } /* end bad */
7557:
7558: for (age=bage; age<=fage; age++){
1.235 brouard 7559: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 7560: sumnewp[cptcod]=0.;
7561: sumnewm[cptcod]=0.;
7562: for (i=1; i<=nlstate;i++){
7563: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
7564: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7565: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
7566: }
7567: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
7568: }
7569: /* printf("\n"); */
7570: /* } */
7571: /* brutal averaging */
7572: for (i=1; i<=nlstate;i++){
7573: for (age=1; age<=bage; age++){
7574: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
7575: /* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); */
7576: }
7577: for (age=fage; age<=AGESUP; age++){
7578: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
7579: /* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); */
7580: }
7581: } /* end i status */
7582: for (i=nlstate+1; i<=nlstate+ndeath;i++){
7583: for (age=1; age<=AGESUP; age++){
7584: /*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*/
7585: mobaverage[(int)age][i][cptcod]=0.;
7586: }
7587: }
7588: }/* end cptcod */
7589: free_vector(sumnewm,1, ncovcombmax);
7590: free_vector(sumnewp,1, ncovcombmax);
7591: free_vector(agemaxgood,1, ncovcombmax);
7592: free_vector(agemingood,1, ncovcombmax);
7593: return 0;
7594: }/* End movingaverage */
1.218 brouard 7595:
1.126 brouard 7596:
7597: /************** Forecasting ******************/
1.235 brouard 7598: void prevforecast(char fileres[], double anproj1, double mproj1, double jproj1, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double bage, double fage, int firstpass, int lastpass, double anproj2, double p[], int cptcoveff){
1.126 brouard 7599: /* proj1, year, month, day of starting projection
7600: agemin, agemax range of age
7601: dateprev1 dateprev2 range of dates during which prevalence is computed
7602: anproj2 year of en of projection (same day and month as proj1).
7603: */
1.235 brouard 7604: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 7605: double agec; /* generic age */
7606: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
7607: double *popeffectif,*popcount;
7608: double ***p3mat;
1.218 brouard 7609: /* double ***mobaverage; */
1.126 brouard 7610: char fileresf[FILENAMELENGTH];
7611:
7612: agelim=AGESUP;
1.211 brouard 7613: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
7614: in each health status at the date of interview (if between dateprev1 and dateprev2).
7615: We still use firstpass and lastpass as another selection.
7616: */
1.214 brouard 7617: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
7618: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 7619:
1.201 brouard 7620: strcpy(fileresf,"F_");
7621: strcat(fileresf,fileresu);
1.126 brouard 7622: if((ficresf=fopen(fileresf,"w"))==NULL) {
7623: printf("Problem with forecast resultfile: %s\n", fileresf);
7624: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
7625: }
1.235 brouard 7626: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
7627: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 7628:
1.225 brouard 7629: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 7630:
7631:
7632: stepsize=(int) (stepm+YEARM-1)/YEARM;
7633: if (stepm<=12) stepsize=1;
7634: if(estepm < stepm){
7635: printf ("Problem %d lower than %d\n",estepm, stepm);
7636: }
7637: else hstepm=estepm;
7638:
7639: hstepm=hstepm/stepm;
7640: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
7641: fractional in yp1 */
7642: anprojmean=yp;
7643: yp2=modf((yp1*12),&yp);
7644: mprojmean=yp;
7645: yp1=modf((yp2*30.5),&yp);
7646: jprojmean=yp;
7647: if(jprojmean==0) jprojmean=1;
7648: if(mprojmean==0) jprojmean=1;
7649:
1.227 brouard 7650: i1=pow(2,cptcoveff);
1.126 brouard 7651: if (cptcovn < 1){i1=1;}
7652:
7653: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
7654:
7655: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 7656:
1.126 brouard 7657: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 7658: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7659: for(k=1; k<=i1;k++){
1.253 brouard 7660: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 7661: continue;
1.227 brouard 7662: if(invalidvarcomb[k]){
7663: printf("\nCombination (%d) projection ignored because no cases \n",k);
7664: continue;
7665: }
7666: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
7667: for(j=1;j<=cptcoveff;j++) {
7668: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
7669: }
1.235 brouard 7670: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7671: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 7672: }
1.227 brouard 7673: fprintf(ficresf," yearproj age");
7674: for(j=1; j<=nlstate+ndeath;j++){
7675: for(i=1; i<=nlstate;i++)
7676: fprintf(ficresf," p%d%d",i,j);
7677: fprintf(ficresf," wp.%d",j);
7678: }
7679: for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {
7680: fprintf(ficresf,"\n");
7681: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
7682: for (agec=fage; agec>=(ageminpar-1); agec--){
7683: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
7684: nhstepm = nhstepm/hstepm;
7685: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7686: oldm=oldms;savm=savms;
1.235 brouard 7687: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.227 brouard 7688:
7689: for (h=0; h<=nhstepm; h++){
7690: if (h*hstepm/YEARM*stepm ==yearp) {
7691: fprintf(ficresf,"\n");
7692: for(j=1;j<=cptcoveff;j++)
7693: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
7694: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
7695: }
7696: for(j=1; j<=nlstate+ndeath;j++) {
7697: ppij=0.;
7698: for(i=1; i<=nlstate;i++) {
7699: if (mobilav==1)
7700: ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][i][k];
7701: else {
7702: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
7703: }
7704: if (h*hstepm/YEARM*stepm== yearp) {
7705: fprintf(ficresf," %.3f", p3mat[i][j][h]);
7706: }
7707: } /* end i */
7708: if (h*hstepm/YEARM*stepm==yearp) {
7709: fprintf(ficresf," %.3f", ppij);
7710: }
7711: }/* end j */
7712: } /* end h */
7713: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7714: } /* end agec */
7715: } /* end yearp */
7716: } /* end k */
1.219 brouard 7717:
1.126 brouard 7718: fclose(ficresf);
1.215 brouard 7719: printf("End of Computing forecasting \n");
7720: fprintf(ficlog,"End of Computing forecasting\n");
7721:
1.126 brouard 7722: }
7723:
1.218 brouard 7724: /* /\************** Back Forecasting ******************\/ */
1.225 brouard 7725: /* void prevbackforecast(char fileres[], 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){ */
1.218 brouard 7726: /* /\* back1, year, month, day of starting backection */
7727: /* agemin, agemax range of age */
7728: /* dateprev1 dateprev2 range of dates during which prevalence is computed */
7729: /* anback2 year of en of backection (same day and month as back1). */
7730: /* *\/ */
7731: /* int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1; */
7732: /* double agec; /\* generic age *\/ */
7733: /* double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean; */
7734: /* double *popeffectif,*popcount; */
7735: /* double ***p3mat; */
7736: /* /\* double ***mobaverage; *\/ */
7737: /* char fileresfb[FILENAMELENGTH]; */
7738:
7739: /* agelim=AGESUP; */
7740: /* /\* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people */
7741: /* in each health status at the date of interview (if between dateprev1 and dateprev2). */
7742: /* We still use firstpass and lastpass as another selection. */
7743: /* *\/ */
7744: /* /\* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ *\/ */
7745: /* /\* firstpass, lastpass, stepm, weightopt, model); *\/ */
7746: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
7747:
7748: /* strcpy(fileresfb,"FB_"); */
7749: /* strcat(fileresfb,fileresu); */
7750: /* if((ficresfb=fopen(fileresfb,"w"))==NULL) { */
7751: /* printf("Problem with back forecast resultfile: %s\n", fileresfb); */
7752: /* fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb); */
7753: /* } */
7754: /* printf("Computing back forecasting: result on file '%s', please wait... \n", fileresfb); */
7755: /* fprintf(ficlog,"Computing back forecasting: result on file '%s', please wait... \n", fileresfb); */
7756:
1.225 brouard 7757: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.218 brouard 7758:
7759: /* /\* if (mobilav!=0) { *\/ */
7760: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
7761: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
7762: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
7763: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
7764: /* /\* } *\/ */
7765: /* /\* } *\/ */
7766:
7767: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
7768: /* if (stepm<=12) stepsize=1; */
7769: /* if(estepm < stepm){ */
7770: /* printf ("Problem %d lower than %d\n",estepm, stepm); */
7771: /* } */
7772: /* else hstepm=estepm; */
7773:
7774: /* hstepm=hstepm/stepm; */
7775: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
7776: /* fractional in yp1 *\/ */
7777: /* anprojmean=yp; */
7778: /* yp2=modf((yp1*12),&yp); */
7779: /* mprojmean=yp; */
7780: /* yp1=modf((yp2*30.5),&yp); */
7781: /* jprojmean=yp; */
7782: /* if(jprojmean==0) jprojmean=1; */
7783: /* if(mprojmean==0) jprojmean=1; */
7784:
1.225 brouard 7785: /* i1=cptcoveff; */
1.218 brouard 7786: /* if (cptcovn < 1){i1=1;} */
1.217 brouard 7787:
1.218 brouard 7788: /* fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2); */
1.217 brouard 7789:
1.218 brouard 7790: /* fprintf(ficresfb,"#****** Routine prevbackforecast **\n"); */
7791:
7792: /* /\* if (h==(int)(YEARM*yearp)){ *\/ */
7793: /* for(cptcov=1, k=0;cptcov<=i1;cptcov++){ */
1.225 brouard 7794: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
1.218 brouard 7795: /* k=k+1; */
7796: /* fprintf(ficresfb,"\n#****** hbijx=probability over h years, hp.jx is weighted by observed prev \n#"); */
1.225 brouard 7797: /* for(j=1;j<=cptcoveff;j++) { */
1.218 brouard 7798: /* fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
7799: /* } */
7800: /* fprintf(ficresfb," yearbproj age"); */
7801: /* for(j=1; j<=nlstate+ndeath;j++){ */
7802: /* for(i=1; i<=nlstate;i++) */
7803: /* fprintf(ficresfb," p%d%d",i,j); */
7804: /* fprintf(ficresfb," p.%d",j); */
7805: /* } */
7806: /* for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) { */
7807: /* /\* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { *\/ */
7808: /* fprintf(ficresfb,"\n"); */
7809: /* fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
7810: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
7811: /* nhstepm=(int) rint((agelim-agec)*YEARM/stepm); */
7812: /* nhstepm = nhstepm/hstepm; */
7813: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7814: /* oldm=oldms;savm=savms; */
7815: /* hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm,oldm,savm, dnewm, doldm, dsavm, k); */
7816: /* for (h=0; h<=nhstepm; h++){ */
7817: /* if (h*hstepm/YEARM*stepm ==yearp) { */
7818: /* fprintf(ficresfb,"\n"); */
1.225 brouard 7819: /* for(j=1;j<=cptcoveff;j++) */
1.218 brouard 7820: /* fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
7821: /* fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec+h*hstepm/YEARM*stepm); */
7822: /* } */
7823: /* for(j=1; j<=nlstate+ndeath;j++) { */
7824: /* ppij=0.; */
7825: /* for(i=1; i<=nlstate;i++) { */
7826: /* if (mobilav==1) */
7827: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][i][cptcod]; */
7828: /* else { */
7829: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][cptcod]; */
7830: /* } */
7831: /* if (h*hstepm/YEARM*stepm== yearp) { */
7832: /* fprintf(ficresfb," %.3f", p3mat[i][j][h]); */
7833: /* } */
7834: /* } /\* end i *\/ */
7835: /* if (h*hstepm/YEARM*stepm==yearp) { */
7836: /* fprintf(ficresfb," %.3f", ppij); */
7837: /* } */
7838: /* }/\* end j *\/ */
7839: /* } /\* end h *\/ */
7840: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7841: /* } /\* end agec *\/ */
7842: /* } /\* end yearp *\/ */
7843: /* } /\* end cptcod *\/ */
7844: /* } /\* end cptcov *\/ */
7845:
7846: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
7847:
7848: /* fclose(ficresfb); */
7849: /* printf("End of Computing Back forecasting \n"); */
7850: /* fprintf(ficlog,"End of Computing Back forecasting\n"); */
1.217 brouard 7851:
1.218 brouard 7852: /* } */
1.217 brouard 7853:
1.126 brouard 7854: /************** Forecasting *****not tested NB*************/
1.227 brouard 7855: /* 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 7856:
1.227 brouard 7857: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
7858: /* int *popage; */
7859: /* double calagedatem, agelim, kk1, kk2; */
7860: /* double *popeffectif,*popcount; */
7861: /* double ***p3mat,***tabpop,***tabpopprev; */
7862: /* /\* double ***mobaverage; *\/ */
7863: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 7864:
1.227 brouard 7865: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7866: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7867: /* agelim=AGESUP; */
7868: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 7869:
1.227 brouard 7870: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 7871:
7872:
1.227 brouard 7873: /* strcpy(filerespop,"POP_"); */
7874: /* strcat(filerespop,fileresu); */
7875: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
7876: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
7877: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
7878: /* } */
7879: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
7880: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 7881:
1.227 brouard 7882: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 7883:
1.227 brouard 7884: /* /\* if (mobilav!=0) { *\/ */
7885: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
7886: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
7887: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
7888: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
7889: /* /\* } *\/ */
7890: /* /\* } *\/ */
1.126 brouard 7891:
1.227 brouard 7892: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
7893: /* if (stepm<=12) stepsize=1; */
1.126 brouard 7894:
1.227 brouard 7895: /* agelim=AGESUP; */
1.126 brouard 7896:
1.227 brouard 7897: /* hstepm=1; */
7898: /* hstepm=hstepm/stepm; */
1.218 brouard 7899:
1.227 brouard 7900: /* if (popforecast==1) { */
7901: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
7902: /* printf("Problem with population file : %s\n",popfile);exit(0); */
7903: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
7904: /* } */
7905: /* popage=ivector(0,AGESUP); */
7906: /* popeffectif=vector(0,AGESUP); */
7907: /* popcount=vector(0,AGESUP); */
1.126 brouard 7908:
1.227 brouard 7909: /* i=1; */
7910: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 7911:
1.227 brouard 7912: /* imx=i; */
7913: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
7914: /* } */
1.218 brouard 7915:
1.227 brouard 7916: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
7917: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
7918: /* k=k+1; */
7919: /* fprintf(ficrespop,"\n#******"); */
7920: /* for(j=1;j<=cptcoveff;j++) { */
7921: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
7922: /* } */
7923: /* fprintf(ficrespop,"******\n"); */
7924: /* fprintf(ficrespop,"# Age"); */
7925: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
7926: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 7927:
1.227 brouard 7928: /* for (cpt=0; cpt<=0;cpt++) { */
7929: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 7930:
1.227 brouard 7931: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
7932: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
7933: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 7934:
1.227 brouard 7935: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7936: /* oldm=oldms;savm=savms; */
7937: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 7938:
1.227 brouard 7939: /* for (h=0; h<=nhstepm; h++){ */
7940: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
7941: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
7942: /* } */
7943: /* for(j=1; j<=nlstate+ndeath;j++) { */
7944: /* kk1=0.;kk2=0; */
7945: /* for(i=1; i<=nlstate;i++) { */
7946: /* if (mobilav==1) */
7947: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
7948: /* else { */
7949: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
7950: /* } */
7951: /* } */
7952: /* if (h==(int)(calagedatem+12*cpt)){ */
7953: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
7954: /* /\*fprintf(ficrespop," %.3f", kk1); */
7955: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
7956: /* } */
7957: /* } */
7958: /* for(i=1; i<=nlstate;i++){ */
7959: /* kk1=0.; */
7960: /* for(j=1; j<=nlstate;j++){ */
7961: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
7962: /* } */
7963: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
7964: /* } */
1.218 brouard 7965:
1.227 brouard 7966: /* if (h==(int)(calagedatem+12*cpt)) */
7967: /* for(j=1; j<=nlstate;j++) */
7968: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
7969: /* } */
7970: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7971: /* } */
7972: /* } */
1.218 brouard 7973:
1.227 brouard 7974: /* /\******\/ */
1.218 brouard 7975:
1.227 brouard 7976: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
7977: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
7978: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
7979: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
7980: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 7981:
1.227 brouard 7982: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7983: /* oldm=oldms;savm=savms; */
7984: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
7985: /* for (h=0; h<=nhstepm; h++){ */
7986: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
7987: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
7988: /* } */
7989: /* for(j=1; j<=nlstate+ndeath;j++) { */
7990: /* kk1=0.;kk2=0; */
7991: /* for(i=1; i<=nlstate;i++) { */
7992: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
7993: /* } */
7994: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
7995: /* } */
7996: /* } */
7997: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7998: /* } */
7999: /* } */
8000: /* } */
8001: /* } */
1.218 brouard 8002:
1.227 brouard 8003: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8004:
1.227 brouard 8005: /* if (popforecast==1) { */
8006: /* free_ivector(popage,0,AGESUP); */
8007: /* free_vector(popeffectif,0,AGESUP); */
8008: /* free_vector(popcount,0,AGESUP); */
8009: /* } */
8010: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8011: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8012: /* fclose(ficrespop); */
8013: /* } /\* End of popforecast *\/ */
1.218 brouard 8014:
1.126 brouard 8015: int fileappend(FILE *fichier, char *optionfich)
8016: {
8017: if((fichier=fopen(optionfich,"a"))==NULL) {
8018: printf("Problem with file: %s\n", optionfich);
8019: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8020: return (0);
8021: }
8022: fflush(fichier);
8023: return (1);
8024: }
8025:
8026:
8027: /**************** function prwizard **********************/
8028: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8029: {
8030:
8031: /* Wizard to print covariance matrix template */
8032:
1.164 brouard 8033: char ca[32], cb[32];
8034: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8035: int numlinepar;
8036:
8037: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8038: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8039: for(i=1; i <=nlstate; i++){
8040: jj=0;
8041: for(j=1; j <=nlstate+ndeath; j++){
8042: if(j==i) continue;
8043: jj++;
8044: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8045: printf("%1d%1d",i,j);
8046: fprintf(ficparo,"%1d%1d",i,j);
8047: for(k=1; k<=ncovmodel;k++){
8048: /* printf(" %lf",param[i][j][k]); */
8049: /* fprintf(ficparo," %lf",param[i][j][k]); */
8050: printf(" 0.");
8051: fprintf(ficparo," 0.");
8052: }
8053: printf("\n");
8054: fprintf(ficparo,"\n");
8055: }
8056: }
8057: printf("# Scales (for hessian or gradient estimation)\n");
8058: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8059: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8060: for(i=1; i <=nlstate; i++){
8061: jj=0;
8062: for(j=1; j <=nlstate+ndeath; j++){
8063: if(j==i) continue;
8064: jj++;
8065: fprintf(ficparo,"%1d%1d",i,j);
8066: printf("%1d%1d",i,j);
8067: fflush(stdout);
8068: for(k=1; k<=ncovmodel;k++){
8069: /* printf(" %le",delti3[i][j][k]); */
8070: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8071: printf(" 0.");
8072: fprintf(ficparo," 0.");
8073: }
8074: numlinepar++;
8075: printf("\n");
8076: fprintf(ficparo,"\n");
8077: }
8078: }
8079: printf("# Covariance matrix\n");
8080: /* # 121 Var(a12)\n\ */
8081: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8082: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
8083: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
8084: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
8085: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
8086: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
8087: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8088: fflush(stdout);
8089: fprintf(ficparo,"# Covariance matrix\n");
8090: /* # 121 Var(a12)\n\ */
8091: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8092: /* # ...\n\ */
8093: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8094:
8095: for(itimes=1;itimes<=2;itimes++){
8096: jj=0;
8097: for(i=1; i <=nlstate; i++){
8098: for(j=1; j <=nlstate+ndeath; j++){
8099: if(j==i) continue;
8100: for(k=1; k<=ncovmodel;k++){
8101: jj++;
8102: ca[0]= k+'a'-1;ca[1]='\0';
8103: if(itimes==1){
8104: printf("#%1d%1d%d",i,j,k);
8105: fprintf(ficparo,"#%1d%1d%d",i,j,k);
8106: }else{
8107: printf("%1d%1d%d",i,j,k);
8108: fprintf(ficparo,"%1d%1d%d",i,j,k);
8109: /* printf(" %.5le",matcov[i][j]); */
8110: }
8111: ll=0;
8112: for(li=1;li <=nlstate; li++){
8113: for(lj=1;lj <=nlstate+ndeath; lj++){
8114: if(lj==li) continue;
8115: for(lk=1;lk<=ncovmodel;lk++){
8116: ll++;
8117: if(ll<=jj){
8118: cb[0]= lk +'a'-1;cb[1]='\0';
8119: if(ll<jj){
8120: if(itimes==1){
8121: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8122: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8123: }else{
8124: printf(" 0.");
8125: fprintf(ficparo," 0.");
8126: }
8127: }else{
8128: if(itimes==1){
8129: printf(" Var(%s%1d%1d)",ca,i,j);
8130: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
8131: }else{
8132: printf(" 0.");
8133: fprintf(ficparo," 0.");
8134: }
8135: }
8136: }
8137: } /* end lk */
8138: } /* end lj */
8139: } /* end li */
8140: printf("\n");
8141: fprintf(ficparo,"\n");
8142: numlinepar++;
8143: } /* end k*/
8144: } /*end j */
8145: } /* end i */
8146: } /* end itimes */
8147:
8148: } /* end of prwizard */
8149: /******************* Gompertz Likelihood ******************************/
8150: double gompertz(double x[])
8151: {
8152: double A,B,L=0.0,sump=0.,num=0.;
8153: int i,n=0; /* n is the size of the sample */
8154:
1.220 brouard 8155: for (i=1;i<=imx ; i++) {
1.126 brouard 8156: sump=sump+weight[i];
8157: /* sump=sump+1;*/
8158: num=num+1;
8159: }
8160:
8161:
8162: /* for (i=0; i<=imx; i++)
8163: 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]);*/
8164:
8165: for (i=1;i<=imx ; i++)
8166: {
8167: if (cens[i] == 1 && wav[i]>1)
8168: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
8169:
8170: if (cens[i] == 0 && wav[i]>1)
8171: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
8172: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
8173:
8174: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
8175: if (wav[i] > 1 ) { /* ??? */
8176: L=L+A*weight[i];
8177: /* 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]);*/
8178: }
8179: }
8180:
8181: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
8182:
8183: return -2*L*num/sump;
8184: }
8185:
1.136 brouard 8186: #ifdef GSL
8187: /******************* Gompertz_f Likelihood ******************************/
8188: double gompertz_f(const gsl_vector *v, void *params)
8189: {
8190: double A,B,LL=0.0,sump=0.,num=0.;
8191: double *x= (double *) v->data;
8192: int i,n=0; /* n is the size of the sample */
8193:
8194: for (i=0;i<=imx-1 ; i++) {
8195: sump=sump+weight[i];
8196: /* sump=sump+1;*/
8197: num=num+1;
8198: }
8199:
8200:
8201: /* for (i=0; i<=imx; i++)
8202: 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]);*/
8203: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
8204: for (i=1;i<=imx ; i++)
8205: {
8206: if (cens[i] == 1 && wav[i]>1)
8207: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
8208:
8209: if (cens[i] == 0 && wav[i]>1)
8210: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
8211: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
8212:
8213: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
8214: if (wav[i] > 1 ) { /* ??? */
8215: LL=LL+A*weight[i];
8216: /* 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]);*/
8217: }
8218: }
8219:
8220: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
8221: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
8222:
8223: return -2*LL*num/sump;
8224: }
8225: #endif
8226:
1.126 brouard 8227: /******************* Printing html file ***********/
1.201 brouard 8228: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 8229: int lastpass, int stepm, int weightopt, char model[],\
8230: int imx, double p[],double **matcov,double agemortsup){
8231: int i,k;
8232:
8233: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
8234: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
8235: for (i=1;i<=2;i++)
8236: 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 8237: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 8238: fprintf(fichtm,"</ul>");
8239:
8240: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
8241:
8242: 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>");
8243:
8244: for (k=agegomp;k<(agemortsup-2);k++)
8245: 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]);
8246:
8247:
8248: fflush(fichtm);
8249: }
8250:
8251: /******************* Gnuplot file **************/
1.201 brouard 8252: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 8253:
8254: char dirfileres[132],optfileres[132];
1.164 brouard 8255:
1.126 brouard 8256: int ng;
8257:
8258:
8259: /*#ifdef windows */
8260: fprintf(ficgp,"cd \"%s\" \n",pathc);
8261: /*#endif */
8262:
8263:
8264: strcpy(dirfileres,optionfilefiname);
8265: strcpy(optfileres,"vpl");
1.199 brouard 8266: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 8267: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 8268: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 8269: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 8270: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
8271:
8272: }
8273:
1.136 brouard 8274: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
8275: {
1.126 brouard 8276:
1.136 brouard 8277: /*-------- data file ----------*/
8278: FILE *fic;
8279: char dummy[]=" ";
1.240 brouard 8280: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 8281: int lstra;
1.136 brouard 8282: int linei, month, year,iout;
8283: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 8284: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 8285: char *stratrunc;
1.223 brouard 8286:
1.240 brouard 8287: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
8288: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 8289:
1.240 brouard 8290: for(v=1; v <=ncovcol;v++){
8291: DummyV[v]=0;
8292: FixedV[v]=0;
8293: }
8294: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
8295: DummyV[v]=1;
8296: FixedV[v]=0;
8297: }
8298: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
8299: DummyV[v]=0;
8300: FixedV[v]=1;
8301: }
8302: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
8303: DummyV[v]=1;
8304: FixedV[v]=1;
8305: }
8306: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
8307: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
8308: 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]);
8309: }
1.126 brouard 8310:
1.136 brouard 8311: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 8312: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
8313: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 8314: }
1.126 brouard 8315:
1.136 brouard 8316: i=1;
8317: linei=0;
8318: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
8319: linei=linei+1;
8320: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
8321: if(line[j] == '\t')
8322: line[j] = ' ';
8323: }
8324: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
8325: ;
8326: };
8327: line[j+1]=0; /* Trims blanks at end of line */
8328: if(line[0]=='#'){
8329: fprintf(ficlog,"Comment line\n%s\n",line);
8330: printf("Comment line\n%s\n",line);
8331: continue;
8332: }
8333: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 8334: strcpy(line, linetmp);
1.223 brouard 8335:
8336: /* Loops on waves */
8337: for (j=maxwav;j>=1;j--){
8338: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 8339: cutv(stra, strb, line, ' ');
8340: if(strb[0]=='.') { /* Missing value */
8341: lval=-1;
8342: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
8343: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
8344: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
8345: 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);
8346: 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);
8347: return 1;
8348: }
8349: }else{
8350: errno=0;
8351: /* what_kind_of_number(strb); */
8352: dval=strtod(strb,&endptr);
8353: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
8354: /* if(strb != endptr && *endptr == '\0') */
8355: /* dval=dlval; */
8356: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
8357: if( strb[0]=='\0' || (*endptr != '\0')){
8358: 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);
8359: 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);
8360: return 1;
8361: }
8362: cotqvar[j][iv][i]=dval;
8363: cotvar[j][ntv+iv][i]=dval;
8364: }
8365: strcpy(line,stra);
1.223 brouard 8366: }/* end loop ntqv */
1.225 brouard 8367:
1.223 brouard 8368: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 8369: cutv(stra, strb, line, ' ');
8370: if(strb[0]=='.') { /* Missing value */
8371: lval=-1;
8372: }else{
8373: errno=0;
8374: lval=strtol(strb,&endptr,10);
8375: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
8376: if( strb[0]=='\0' || (*endptr != '\0')){
8377: 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);
8378: 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);
8379: return 1;
8380: }
8381: }
8382: if(lval <-1 || lval >1){
8383: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 8384: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
8385: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 8386: For example, for multinomial values like 1, 2 and 3,\n \
8387: build V1=0 V2=0 for the reference value (1),\n \
8388: V1=1 V2=0 for (2) \n \
1.223 brouard 8389: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 8390: output of IMaCh is often meaningless.\n \
1.223 brouard 8391: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 8392: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 8393: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
8394: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 8395: For example, for multinomial values like 1, 2 and 3,\n \
8396: build V1=0 V2=0 for the reference value (1),\n \
8397: V1=1 V2=0 for (2) \n \
1.223 brouard 8398: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 8399: output of IMaCh is often meaningless.\n \
1.223 brouard 8400: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 8401: return 1;
8402: }
8403: cotvar[j][iv][i]=(double)(lval);
8404: strcpy(line,stra);
1.223 brouard 8405: }/* end loop ntv */
1.225 brouard 8406:
1.223 brouard 8407: /* Statuses at wave */
1.137 brouard 8408: cutv(stra, strb, line, ' ');
1.223 brouard 8409: if(strb[0]=='.') { /* Missing value */
1.238 brouard 8410: lval=-1;
1.136 brouard 8411: }else{
1.238 brouard 8412: errno=0;
8413: lval=strtol(strb,&endptr,10);
8414: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
8415: if( strb[0]=='\0' || (*endptr != '\0')){
8416: 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);
8417: 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);
8418: return 1;
8419: }
1.136 brouard 8420: }
1.225 brouard 8421:
1.136 brouard 8422: s[j][i]=lval;
1.225 brouard 8423:
1.223 brouard 8424: /* Date of Interview */
1.136 brouard 8425: strcpy(line,stra);
8426: cutv(stra, strb,line,' ');
1.169 brouard 8427: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 8428: }
1.169 brouard 8429: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 8430: month=99;
8431: year=9999;
1.136 brouard 8432: }else{
1.225 brouard 8433: 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);
8434: 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);
8435: return 1;
1.136 brouard 8436: }
8437: anint[j][i]= (double) year;
8438: mint[j][i]= (double)month;
8439: strcpy(line,stra);
1.223 brouard 8440: } /* End loop on waves */
1.225 brouard 8441:
1.223 brouard 8442: /* Date of death */
1.136 brouard 8443: cutv(stra, strb,line,' ');
1.169 brouard 8444: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 8445: }
1.169 brouard 8446: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 8447: month=99;
8448: year=9999;
8449: }else{
1.141 brouard 8450: 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 8451: 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);
8452: return 1;
1.136 brouard 8453: }
8454: andc[i]=(double) year;
8455: moisdc[i]=(double) month;
8456: strcpy(line,stra);
8457:
1.223 brouard 8458: /* Date of birth */
1.136 brouard 8459: cutv(stra, strb,line,' ');
1.169 brouard 8460: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 8461: }
1.169 brouard 8462: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 8463: month=99;
8464: year=9999;
8465: }else{
1.141 brouard 8466: 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);
8467: 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 8468: return 1;
1.136 brouard 8469: }
8470: if (year==9999) {
1.141 brouard 8471: 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);
8472: 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 8473: return 1;
8474:
1.136 brouard 8475: }
8476: annais[i]=(double)(year);
8477: moisnais[i]=(double)(month);
8478: strcpy(line,stra);
1.225 brouard 8479:
1.223 brouard 8480: /* Sample weight */
1.136 brouard 8481: cutv(stra, strb,line,' ');
8482: errno=0;
8483: dval=strtod(strb,&endptr);
8484: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 8485: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
8486: 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 8487: fflush(ficlog);
8488: return 1;
8489: }
8490: weight[i]=dval;
8491: strcpy(line,stra);
1.225 brouard 8492:
1.223 brouard 8493: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
8494: cutv(stra, strb, line, ' ');
8495: if(strb[0]=='.') { /* Missing value */
1.225 brouard 8496: lval=-1;
1.223 brouard 8497: }else{
1.225 brouard 8498: errno=0;
8499: /* what_kind_of_number(strb); */
8500: dval=strtod(strb,&endptr);
8501: /* if(strb != endptr && *endptr == '\0') */
8502: /* dval=dlval; */
8503: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
8504: if( strb[0]=='\0' || (*endptr != '\0')){
8505: 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);
8506: 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);
8507: return 1;
8508: }
8509: coqvar[iv][i]=dval;
1.226 brouard 8510: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 8511: }
8512: strcpy(line,stra);
8513: }/* end loop nqv */
1.136 brouard 8514:
1.223 brouard 8515: /* Covariate values */
1.136 brouard 8516: for (j=ncovcol;j>=1;j--){
8517: cutv(stra, strb,line,' ');
1.223 brouard 8518: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 8519: lval=-1;
1.136 brouard 8520: }else{
1.225 brouard 8521: errno=0;
8522: lval=strtol(strb,&endptr,10);
8523: if( strb[0]=='\0' || (*endptr != '\0')){
8524: 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);
8525: 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);
8526: return 1;
8527: }
1.136 brouard 8528: }
8529: if(lval <-1 || lval >1){
1.225 brouard 8530: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 8531: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
8532: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 8533: For example, for multinomial values like 1, 2 and 3,\n \
8534: build V1=0 V2=0 for the reference value (1),\n \
8535: V1=1 V2=0 for (2) \n \
1.136 brouard 8536: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 8537: output of IMaCh is often meaningless.\n \
1.136 brouard 8538: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 8539: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 8540: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
8541: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 8542: For example, for multinomial values like 1, 2 and 3,\n \
8543: build V1=0 V2=0 for the reference value (1),\n \
8544: V1=1 V2=0 for (2) \n \
1.136 brouard 8545: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 8546: output of IMaCh is often meaningless.\n \
1.136 brouard 8547: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 8548: return 1;
1.136 brouard 8549: }
8550: covar[j][i]=(double)(lval);
8551: strcpy(line,stra);
8552: }
8553: lstra=strlen(stra);
1.225 brouard 8554:
1.136 brouard 8555: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
8556: stratrunc = &(stra[lstra-9]);
8557: num[i]=atol(stratrunc);
8558: }
8559: else
8560: num[i]=atol(stra);
8561: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
8562: 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;}*/
8563:
8564: i=i+1;
8565: } /* End loop reading data */
1.225 brouard 8566:
1.136 brouard 8567: *imax=i-1; /* Number of individuals */
8568: fclose(fic);
1.225 brouard 8569:
1.136 brouard 8570: return (0);
1.164 brouard 8571: /* endread: */
1.225 brouard 8572: printf("Exiting readdata: ");
8573: fclose(fic);
8574: return (1);
1.223 brouard 8575: }
1.126 brouard 8576:
1.234 brouard 8577: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 8578: char *p1 = *stri, *p2 = *stri;
1.235 brouard 8579: while (*p2 == ' ')
1.234 brouard 8580: p2++;
8581: /* while ((*p1++ = *p2++) !=0) */
8582: /* ; */
8583: /* do */
8584: /* while (*p2 == ' ') */
8585: /* p2++; */
8586: /* while (*p1++ == *p2++); */
8587: *stri=p2;
1.145 brouard 8588: }
8589:
1.235 brouard 8590: int decoderesult ( char resultline[], int nres)
1.230 brouard 8591: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
8592: {
1.235 brouard 8593: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 8594: char resultsav[MAXLINE];
1.234 brouard 8595: int resultmodel[MAXLINE];
8596: int modelresult[MAXLINE];
1.230 brouard 8597: char stra[80], strb[80], strc[80], strd[80],stre[80];
8598:
1.234 brouard 8599: removefirstspace(&resultline);
1.233 brouard 8600: printf("decoderesult:%s\n",resultline);
1.230 brouard 8601:
8602: if (strstr(resultline,"v") !=0){
8603: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
8604: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
8605: return 1;
8606: }
8607: trimbb(resultsav, resultline);
8608: if (strlen(resultsav) >1){
8609: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
8610: }
1.253 brouard 8611: if(j == 0){ /* Resultline but no = */
8612: TKresult[nres]=0; /* Combination for the nresult and the model */
8613: return (0);
8614: }
8615:
1.234 brouard 8616: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
8617: 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);
8618: 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);
8619: }
8620: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
8621: if(nbocc(resultsav,'=') >1){
8622: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
8623: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
8624: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
8625: }else
8626: cutl(strc,strd,resultsav,'=');
1.230 brouard 8627: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 8628:
1.230 brouard 8629: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
8630: Tvarsel[k]=atoi(strc);
8631: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
8632: /* cptcovsel++; */
8633: if (nbocc(stra,'=') >0)
8634: strcpy(resultsav,stra); /* and analyzes it */
8635: }
1.235 brouard 8636: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 8637: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
8638: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 8639: match=0;
1.236 brouard 8640: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 8641: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 8642: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 8643: match=1;
8644: break;
8645: }
8646: }
8647: if(match == 0){
8648: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
8649: }
8650: }
8651: }
1.235 brouard 8652: /* Checking for missing or useless values in comparison of current model needs */
8653: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 8654: match=0;
1.235 brouard 8655: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
8656: if(Typevar[k1]==0){ /* Single */
1.237 brouard 8657: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 8658: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 8659: ++match;
8660: }
8661: }
8662: }
8663: if(match == 0){
8664: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
8665: }else if(match > 1){
8666: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
8667: }
8668: }
1.235 brouard 8669:
1.234 brouard 8670: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 8671: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
8672: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
8673: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
8674: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
8675: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
8676: /* 1 0 0 0 */
8677: /* 2 1 0 0 */
8678: /* 3 0 1 0 */
8679: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
8680: /* 5 0 0 1 */
8681: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
8682: /* 7 0 1 1 */
8683: /* 8 1 1 1 */
1.237 brouard 8684: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
8685: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
8686: /* V5*age V5 known which value for nres? */
8687: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 8688: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
8689: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 8690: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 8691: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
8692: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 8693: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
8694: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
8695: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 8696: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
8697: k4++;;
8698: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
8699: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
8700: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 8701: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
8702: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
8703: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 8704: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
8705: k4q++;;
8706: }
8707: }
1.234 brouard 8708:
1.235 brouard 8709: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 8710: return (0);
8711: }
1.235 brouard 8712:
1.230 brouard 8713: int decodemodel( char model[], int lastobs)
8714: /**< This routine decodes the model and returns:
1.224 brouard 8715: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
8716: * - nagesqr = 1 if age*age in the model, otherwise 0.
8717: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
8718: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
8719: * - cptcovage number of covariates with age*products =2
8720: * - cptcovs number of simple covariates
8721: * - 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
8722: * which is a new column after the 9 (ncovcol) variables.
8723: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
8724: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
8725: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
8726: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
8727: */
1.136 brouard 8728: {
1.238 brouard 8729: int i, j, k, ks, v;
1.227 brouard 8730: int j1, k1, k2, k3, k4;
1.136 brouard 8731: char modelsav[80];
1.145 brouard 8732: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 8733: char *strpt;
1.136 brouard 8734:
1.145 brouard 8735: /*removespace(model);*/
1.136 brouard 8736: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 8737: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 8738: if (strstr(model,"AGE") !=0){
1.192 brouard 8739: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
8740: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 8741: return 1;
8742: }
1.141 brouard 8743: if (strstr(model,"v") !=0){
8744: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
8745: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
8746: return 1;
8747: }
1.187 brouard 8748: strcpy(modelsav,model);
8749: if ((strpt=strstr(model,"age*age")) !=0){
8750: printf(" strpt=%s, model=%s\n",strpt, model);
8751: if(strpt != model){
1.234 brouard 8752: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 8753: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 8754: corresponding column of parameters.\n",model);
1.234 brouard 8755: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 8756: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 8757: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 8758: return 1;
1.225 brouard 8759: }
1.187 brouard 8760: nagesqr=1;
8761: if (strstr(model,"+age*age") !=0)
1.234 brouard 8762: substrchaine(modelsav, model, "+age*age");
1.187 brouard 8763: else if (strstr(model,"age*age+") !=0)
1.234 brouard 8764: substrchaine(modelsav, model, "age*age+");
1.187 brouard 8765: else
1.234 brouard 8766: substrchaine(modelsav, model, "age*age");
1.187 brouard 8767: }else
8768: nagesqr=0;
8769: if (strlen(modelsav) >1){
8770: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
8771: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 8772: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 8773: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 8774: * cst, age and age*age
8775: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
8776: /* including age products which are counted in cptcovage.
8777: * but the covariates which are products must be treated
8778: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 8779: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
8780: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 8781:
8782:
1.187 brouard 8783: /* Design
8784: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
8785: * < ncovcol=8 >
8786: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
8787: * k= 1 2 3 4 5 6 7 8
8788: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
8789: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 8790: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
8791: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 8792: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
8793: * Tage[++cptcovage]=k
8794: * if products, new covar are created after ncovcol with k1
8795: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
8796: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
8797: * 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
8798: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
8799: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
8800: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
8801: * < ncovcol=8 >
8802: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
8803: * k= 1 2 3 4 5 6 7 8 9 10 11 12
8804: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
8805: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
8806: * p Tprod[1]@2={ 6, 5}
8807: *p Tvard[1][1]@4= {7, 8, 5, 6}
8808: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
8809: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
8810: *How to reorganize?
8811: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
8812: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
8813: * {2, 1, 4, 8, 5, 6, 3, 7}
8814: * Struct []
8815: */
1.225 brouard 8816:
1.187 brouard 8817: /* This loop fills the array Tvar from the string 'model'.*/
8818: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
8819: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
8820: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
8821: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
8822: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
8823: /* k=1 Tvar[1]=2 (from V2) */
8824: /* k=5 Tvar[5] */
8825: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 8826: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 8827: /* } */
1.198 brouard 8828: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 8829: /*
8830: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 8831: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
8832: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
8833: }
1.187 brouard 8834: cptcovage=0;
8835: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 8836: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 8837: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 8838: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
8839: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
8840: /*scanf("%d",i);*/
8841: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
8842: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
8843: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
8844: /* covar is not filled and then is empty */
8845: cptcovprod--;
8846: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
8847: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
8848: Typevar[k]=1; /* 1 for age product */
8849: cptcovage++; /* Sums the number of covariates which include age as a product */
8850: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
8851: /*printf("stre=%s ", stre);*/
8852: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
8853: cptcovprod--;
8854: cutl(stre,strb,strc,'V');
8855: Tvar[k]=atoi(stre);
8856: Typevar[k]=1; /* 1 for age product */
8857: cptcovage++;
8858: Tage[cptcovage]=k;
8859: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
8860: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
8861: cptcovn++;
8862: cptcovprodnoage++;k1++;
8863: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
8864: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
8865: because this model-covariate is a construction we invent a new column
8866: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
8867: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
8868: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
8869: Typevar[k]=2; /* 2 for double fixed dummy covariates */
8870: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
8871: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
8872: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
8873: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
8874: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
8875: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
8876: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
8877: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 8878: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 8879: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
8880: for (i=1; i<=lastobs;i++){
8881: /* Computes the new covariate which is a product of
8882: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
8883: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
8884: }
8885: } /* End age is not in the model */
8886: } /* End if model includes a product */
8887: else { /* no more sum */
8888: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
8889: /* scanf("%d",i);*/
8890: cutl(strd,strc,strb,'V');
8891: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
8892: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
8893: Tvar[k]=atoi(strd);
8894: Typevar[k]=0; /* 0 for simple covariates */
8895: }
8896: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 8897: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 8898: scanf("%d",i);*/
1.187 brouard 8899: } /* end of loop + on total covariates */
8900: } /* end if strlen(modelsave == 0) age*age might exist */
8901: } /* end if strlen(model == 0) */
1.136 brouard 8902:
8903: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
8904: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 8905:
1.136 brouard 8906: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 8907: printf("cptcovprod=%d ", cptcovprod);
8908: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
8909: scanf("%d ",i);*/
8910:
8911:
1.230 brouard 8912: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
8913: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 8914: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
8915: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
8916: k = 1 2 3 4 5 6 7 8 9
8917: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
8918: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 8919: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
8920: Dummy[k] 1 0 0 0 3 1 1 2 3
8921: Tmodelind[combination of covar]=k;
1.225 brouard 8922: */
8923: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 8924: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 8925: /* 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 8926: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 8927: printf("Model=%s\n\
8928: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
8929: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
8930: 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);
8931: fprintf(ficlog,"Model=%s\n\
8932: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
8933: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
8934: Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model);
1.240 brouard 8935: for(k=1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 8936: 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 */
8937: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 8938: Fixed[k]= 0;
8939: Dummy[k]= 0;
1.225 brouard 8940: ncoveff++;
1.232 brouard 8941: ncovf++;
1.234 brouard 8942: nsd++;
8943: modell[k].maintype= FTYPE;
8944: TvarsD[nsd]=Tvar[k];
8945: TvarsDind[nsd]=k;
8946: TvarF[ncovf]=Tvar[k];
8947: TvarFind[ncovf]=k;
8948: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
8949: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
8950: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
8951: Fixed[k]= 0;
8952: Dummy[k]= 0;
8953: ncoveff++;
8954: ncovf++;
8955: modell[k].maintype= FTYPE;
8956: TvarF[ncovf]=Tvar[k];
8957: TvarFind[ncovf]=k;
1.230 brouard 8958: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 8959: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 8960: }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 8961: Fixed[k]= 0;
8962: Dummy[k]= 1;
1.230 brouard 8963: nqfveff++;
1.234 brouard 8964: modell[k].maintype= FTYPE;
8965: modell[k].subtype= FQ;
8966: nsq++;
8967: TvarsQ[nsq]=Tvar[k];
8968: TvarsQind[nsq]=k;
1.232 brouard 8969: ncovf++;
1.234 brouard 8970: TvarF[ncovf]=Tvar[k];
8971: TvarFind[ncovf]=k;
1.231 brouard 8972: 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 8973: 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 8974: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 8975: Fixed[k]= 1;
8976: Dummy[k]= 0;
1.225 brouard 8977: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 8978: modell[k].maintype= VTYPE;
8979: modell[k].subtype= VD;
8980: nsd++;
8981: TvarsD[nsd]=Tvar[k];
8982: TvarsDind[nsd]=k;
8983: ncovv++; /* Only simple time varying variables */
8984: TvarV[ncovv]=Tvar[k];
1.242 brouard 8985: 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 8986: 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 */
8987: 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 8988: 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);
8989: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 8990: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 8991: Fixed[k]= 1;
8992: Dummy[k]= 1;
8993: nqtveff++;
8994: modell[k].maintype= VTYPE;
8995: modell[k].subtype= VQ;
8996: ncovv++; /* Only simple time varying variables */
8997: nsq++;
8998: TvarsQ[nsq]=Tvar[k];
8999: TvarsQind[nsq]=k;
9000: TvarV[ncovv]=Tvar[k];
1.242 brouard 9001: 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 9002: 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 */
9003: 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 9004: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9005: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9006: 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 9007: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9008: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9009: ncova++;
9010: TvarA[ncova]=Tvar[k];
9011: TvarAind[ncova]=k;
1.231 brouard 9012: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9013: Fixed[k]= 2;
9014: Dummy[k]= 2;
9015: modell[k].maintype= ATYPE;
9016: modell[k].subtype= APFD;
9017: /* ncoveff++; */
1.227 brouard 9018: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 9019: Fixed[k]= 2;
9020: Dummy[k]= 3;
9021: modell[k].maintype= ATYPE;
9022: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
9023: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 9024: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 9025: Fixed[k]= 3;
9026: Dummy[k]= 2;
9027: modell[k].maintype= ATYPE;
9028: modell[k].subtype= APVD; /* Product age * varying dummy */
9029: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 9030: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9031: Fixed[k]= 3;
9032: Dummy[k]= 3;
9033: modell[k].maintype= ATYPE;
9034: modell[k].subtype= APVQ; /* Product age * varying quantitative */
9035: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 9036: }
9037: }else if (Typevar[k] == 2) { /* product without age */
9038: k1=Tposprod[k];
9039: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 9040: if(Tvard[k1][2] <=ncovcol){
9041: Fixed[k]= 1;
9042: Dummy[k]= 0;
9043: modell[k].maintype= FTYPE;
9044: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
9045: ncovf++; /* Fixed variables without age */
9046: TvarF[ncovf]=Tvar[k];
9047: TvarFind[ncovf]=k;
9048: }else if(Tvard[k1][2] <=ncovcol+nqv){
9049: Fixed[k]= 0; /* or 2 ?*/
9050: Dummy[k]= 1;
9051: modell[k].maintype= FTYPE;
9052: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
9053: ncovf++; /* Varying variables without age */
9054: TvarF[ncovf]=Tvar[k];
9055: TvarFind[ncovf]=k;
9056: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9057: Fixed[k]= 1;
9058: Dummy[k]= 0;
9059: modell[k].maintype= VTYPE;
9060: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
9061: ncovv++; /* Varying variables without age */
9062: TvarV[ncovv]=Tvar[k];
9063: TvarVind[ncovv]=k;
9064: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9065: Fixed[k]= 1;
9066: Dummy[k]= 1;
9067: modell[k].maintype= VTYPE;
9068: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
9069: ncovv++; /* Varying variables without age */
9070: TvarV[ncovv]=Tvar[k];
9071: TvarVind[ncovv]=k;
9072: }
1.227 brouard 9073: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 9074: if(Tvard[k1][2] <=ncovcol){
9075: Fixed[k]= 0; /* or 2 ?*/
9076: Dummy[k]= 1;
9077: modell[k].maintype= FTYPE;
9078: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
9079: ncovf++; /* Fixed variables without age */
9080: TvarF[ncovf]=Tvar[k];
9081: TvarFind[ncovf]=k;
9082: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9083: Fixed[k]= 1;
9084: Dummy[k]= 1;
9085: modell[k].maintype= VTYPE;
9086: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
9087: ncovv++; /* Varying variables without age */
9088: TvarV[ncovv]=Tvar[k];
9089: TvarVind[ncovv]=k;
9090: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9091: Fixed[k]= 1;
9092: Dummy[k]= 1;
9093: modell[k].maintype= VTYPE;
9094: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
9095: ncovv++; /* Varying variables without age */
9096: TvarV[ncovv]=Tvar[k];
9097: TvarVind[ncovv]=k;
9098: ncovv++; /* Varying variables without age */
9099: TvarV[ncovv]=Tvar[k];
9100: TvarVind[ncovv]=k;
9101: }
1.227 brouard 9102: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 9103: if(Tvard[k1][2] <=ncovcol){
9104: Fixed[k]= 1;
9105: Dummy[k]= 1;
9106: modell[k].maintype= VTYPE;
9107: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
9108: ncovv++; /* Varying variables without age */
9109: TvarV[ncovv]=Tvar[k];
9110: TvarVind[ncovv]=k;
9111: }else if(Tvard[k1][2] <=ncovcol+nqv){
9112: Fixed[k]= 1;
9113: Dummy[k]= 1;
9114: modell[k].maintype= VTYPE;
9115: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
9116: ncovv++; /* Varying variables without age */
9117: TvarV[ncovv]=Tvar[k];
9118: TvarVind[ncovv]=k;
9119: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9120: Fixed[k]= 1;
9121: Dummy[k]= 0;
9122: modell[k].maintype= VTYPE;
9123: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
9124: ncovv++; /* Varying variables without age */
9125: TvarV[ncovv]=Tvar[k];
9126: TvarVind[ncovv]=k;
9127: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9128: Fixed[k]= 1;
9129: Dummy[k]= 1;
9130: modell[k].maintype= VTYPE;
9131: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
9132: ncovv++; /* Varying variables without age */
9133: TvarV[ncovv]=Tvar[k];
9134: TvarVind[ncovv]=k;
9135: }
1.227 brouard 9136: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9137: if(Tvard[k1][2] <=ncovcol){
9138: Fixed[k]= 1;
9139: Dummy[k]= 1;
9140: modell[k].maintype= VTYPE;
9141: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
9142: ncovv++; /* Varying variables without age */
9143: TvarV[ncovv]=Tvar[k];
9144: TvarVind[ncovv]=k;
9145: }else if(Tvard[k1][2] <=ncovcol+nqv){
9146: Fixed[k]= 1;
9147: Dummy[k]= 1;
9148: modell[k].maintype= VTYPE;
9149: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
9150: ncovv++; /* Varying variables without age */
9151: TvarV[ncovv]=Tvar[k];
9152: TvarVind[ncovv]=k;
9153: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9154: Fixed[k]= 1;
9155: Dummy[k]= 1;
9156: modell[k].maintype= VTYPE;
9157: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
9158: ncovv++; /* Varying variables without age */
9159: TvarV[ncovv]=Tvar[k];
9160: TvarVind[ncovv]=k;
9161: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9162: Fixed[k]= 1;
9163: Dummy[k]= 1;
9164: modell[k].maintype= VTYPE;
9165: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
9166: ncovv++; /* Varying variables without age */
9167: TvarV[ncovv]=Tvar[k];
9168: TvarVind[ncovv]=k;
9169: }
1.227 brouard 9170: }else{
1.240 brouard 9171: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9172: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9173: } /*end k1*/
1.225 brouard 9174: }else{
1.226 brouard 9175: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
9176: 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 9177: }
1.227 brouard 9178: 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 9179: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 9180: 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]);
9181: }
9182: /* Searching for doublons in the model */
9183: for(k1=1; k1<= cptcovt;k1++){
9184: for(k2=1; k2 <k1;k2++){
9185: if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){
1.234 brouard 9186: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
9187: if(Tvar[k1]==Tvar[k2]){
9188: printf("Error duplication in the model=%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]);
9189: fprintf(ficlog,"Error duplication in the model=%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]); fflush(ficlog);
9190: return(1);
9191: }
9192: }else if (Typevar[k1] ==2){
9193: k3=Tposprod[k1];
9194: k4=Tposprod[k2];
9195: 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])) ){
9196: 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]]);
9197: 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);
9198: return(1);
9199: }
9200: }
1.227 brouard 9201: }
9202: }
1.225 brouard 9203: }
9204: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
9205: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 9206: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
9207: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 9208: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 9209: /*endread:*/
1.225 brouard 9210: printf("Exiting decodemodel: ");
9211: return (1);
1.136 brouard 9212: }
9213:
1.169 brouard 9214: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 9215: {/* Check ages at death */
1.136 brouard 9216: int i, m;
1.218 brouard 9217: int firstone=0;
9218:
1.136 brouard 9219: for (i=1; i<=imx; i++) {
9220: for(m=2; (m<= maxwav); m++) {
9221: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
9222: anint[m][i]=9999;
1.216 brouard 9223: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
9224: s[m][i]=-1;
1.136 brouard 9225: }
9226: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 9227: *nberr = *nberr + 1;
1.218 brouard 9228: if(firstone == 0){
9229: firstone=1;
1.260 brouard 9230: 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 9231: }
1.262 brouard 9232: 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 9233: s[m][i]=-1; /* Droping the death status */
1.136 brouard 9234: }
9235: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 9236: (*nberr)++;
1.259 brouard 9237: 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 9238: 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 9239: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 9240: }
9241: }
9242: }
9243:
9244: for (i=1; i<=imx; i++) {
9245: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
9246: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 9247: 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 9248: if (s[m][i] >= nlstate+1) {
1.169 brouard 9249: if(agedc[i]>0){
9250: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 9251: agev[m][i]=agedc[i];
1.214 brouard 9252: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 9253: }else {
1.136 brouard 9254: if ((int)andc[i]!=9999){
9255: nbwarn++;
9256: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
9257: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
9258: agev[m][i]=-1;
9259: }
9260: }
1.169 brouard 9261: } /* agedc > 0 */
1.214 brouard 9262: } /* end if */
1.136 brouard 9263: else if(s[m][i] !=9){ /* Standard case, age in fractional
9264: years but with the precision of a month */
9265: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
9266: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
9267: agev[m][i]=1;
9268: else if(agev[m][i] < *agemin){
9269: *agemin=agev[m][i];
9270: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
9271: }
9272: else if(agev[m][i] >*agemax){
9273: *agemax=agev[m][i];
1.156 brouard 9274: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 9275: }
9276: /*agev[m][i]=anint[m][i]-annais[i];*/
9277: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 9278: } /* en if 9*/
1.136 brouard 9279: else { /* =9 */
1.214 brouard 9280: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 9281: agev[m][i]=1;
9282: s[m][i]=-1;
9283: }
9284: }
1.214 brouard 9285: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 9286: agev[m][i]=1;
1.214 brouard 9287: else{
9288: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
9289: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
9290: agev[m][i]=0;
9291: }
9292: } /* End for lastpass */
9293: }
1.136 brouard 9294:
9295: for (i=1; i<=imx; i++) {
9296: for(m=firstpass; (m<=lastpass); m++){
9297: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 9298: (*nberr)++;
1.136 brouard 9299: 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);
9300: 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);
9301: return 1;
9302: }
9303: }
9304: }
9305:
9306: /*for (i=1; i<=imx; i++){
9307: for (m=firstpass; (m<lastpass); m++){
9308: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
9309: }
9310:
9311: }*/
9312:
9313:
1.139 brouard 9314: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
9315: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 9316:
9317: return (0);
1.164 brouard 9318: /* endread:*/
1.136 brouard 9319: printf("Exiting calandcheckages: ");
9320: return (1);
9321: }
9322:
1.172 brouard 9323: #if defined(_MSC_VER)
9324: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
9325: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
9326: //#include "stdafx.h"
9327: //#include <stdio.h>
9328: //#include <tchar.h>
9329: //#include <windows.h>
9330: //#include <iostream>
9331: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
9332:
9333: LPFN_ISWOW64PROCESS fnIsWow64Process;
9334:
9335: BOOL IsWow64()
9336: {
9337: BOOL bIsWow64 = FALSE;
9338:
9339: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
9340: // (HANDLE, PBOOL);
9341:
9342: //LPFN_ISWOW64PROCESS fnIsWow64Process;
9343:
9344: HMODULE module = GetModuleHandle(_T("kernel32"));
9345: const char funcName[] = "IsWow64Process";
9346: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
9347: GetProcAddress(module, funcName);
9348:
9349: if (NULL != fnIsWow64Process)
9350: {
9351: if (!fnIsWow64Process(GetCurrentProcess(),
9352: &bIsWow64))
9353: //throw std::exception("Unknown error");
9354: printf("Unknown error\n");
9355: }
9356: return bIsWow64 != FALSE;
9357: }
9358: #endif
1.177 brouard 9359:
1.191 brouard 9360: void syscompilerinfo(int logged)
1.167 brouard 9361: {
9362: /* #include "syscompilerinfo.h"*/
1.185 brouard 9363: /* command line Intel compiler 32bit windows, XP compatible:*/
9364: /* /GS /W3 /Gy
9365: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
9366: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
9367: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 9368: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
9369: */
9370: /* 64 bits */
1.185 brouard 9371: /*
9372: /GS /W3 /Gy
9373: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
9374: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
9375: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
9376: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
9377: /* Optimization are useless and O3 is slower than O2 */
9378: /*
9379: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
9380: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
9381: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
9382: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
9383: */
1.186 brouard 9384: /* Link is */ /* /OUT:"visual studio
1.185 brouard 9385: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
9386: /PDB:"visual studio
9387: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
9388: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
9389: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
9390: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
9391: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
9392: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
9393: uiAccess='false'"
9394: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
9395: /NOLOGO /TLBID:1
9396: */
1.177 brouard 9397: #if defined __INTEL_COMPILER
1.178 brouard 9398: #if defined(__GNUC__)
9399: struct utsname sysInfo; /* For Intel on Linux and OS/X */
9400: #endif
1.177 brouard 9401: #elif defined(__GNUC__)
1.179 brouard 9402: #ifndef __APPLE__
1.174 brouard 9403: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 9404: #endif
1.177 brouard 9405: struct utsname sysInfo;
1.178 brouard 9406: int cross = CROSS;
9407: if (cross){
9408: printf("Cross-");
1.191 brouard 9409: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 9410: }
1.174 brouard 9411: #endif
9412:
1.171 brouard 9413: #include <stdint.h>
1.178 brouard 9414:
1.191 brouard 9415: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 9416: #if defined(__clang__)
1.191 brouard 9417: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 9418: #endif
9419: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 9420: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 9421: #endif
9422: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 9423: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 9424: #endif
9425: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 9426: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 9427: #endif
9428: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 9429: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 9430: #endif
9431: #if defined(_MSC_VER)
1.191 brouard 9432: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 9433: #endif
9434: #if defined(__PGI)
1.191 brouard 9435: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 9436: #endif
9437: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 9438: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 9439: #endif
1.191 brouard 9440: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 9441:
1.167 brouard 9442: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
9443: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
9444: // Windows (x64 and x86)
1.191 brouard 9445: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 9446: #elif __unix__ // all unices, not all compilers
9447: // Unix
1.191 brouard 9448: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 9449: #elif __linux__
9450: // linux
1.191 brouard 9451: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 9452: #elif __APPLE__
1.174 brouard 9453: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 9454: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 9455: #endif
9456:
9457: /* __MINGW32__ */
9458: /* __CYGWIN__ */
9459: /* __MINGW64__ */
9460: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
9461: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
9462: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
9463: /* _WIN64 // Defined for applications for Win64. */
9464: /* _M_X64 // Defined for compilations that target x64 processors. */
9465: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 9466:
1.167 brouard 9467: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 9468: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 9469: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 9470: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 9471: #else
1.191 brouard 9472: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 9473: #endif
9474:
1.169 brouard 9475: #if defined(__GNUC__)
9476: # if defined(__GNUC_PATCHLEVEL__)
9477: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
9478: + __GNUC_MINOR__ * 100 \
9479: + __GNUC_PATCHLEVEL__)
9480: # else
9481: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
9482: + __GNUC_MINOR__ * 100)
9483: # endif
1.174 brouard 9484: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 9485: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 9486:
9487: if (uname(&sysInfo) != -1) {
9488: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 9489: 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 9490: }
9491: else
9492: perror("uname() error");
1.179 brouard 9493: //#ifndef __INTEL_COMPILER
9494: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 9495: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 9496: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 9497: #endif
1.169 brouard 9498: #endif
1.172 brouard 9499:
9500: // void main()
9501: // {
1.169 brouard 9502: #if defined(_MSC_VER)
1.174 brouard 9503: if (IsWow64()){
1.191 brouard 9504: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
9505: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 9506: }
9507: else{
1.191 brouard 9508: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
9509: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 9510: }
1.172 brouard 9511: // printf("\nPress Enter to continue...");
9512: // getchar();
9513: // }
9514:
1.169 brouard 9515: #endif
9516:
1.167 brouard 9517:
1.219 brouard 9518: }
1.136 brouard 9519:
1.219 brouard 9520: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.180 brouard 9521: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.235 brouard 9522: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 9523: /* double ftolpl = 1.e-10; */
1.180 brouard 9524: double age, agebase, agelim;
1.203 brouard 9525: double tot;
1.180 brouard 9526:
1.202 brouard 9527: strcpy(filerespl,"PL_");
9528: strcat(filerespl,fileresu);
9529: if((ficrespl=fopen(filerespl,"w"))==NULL) {
9530: printf("Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
9531: fprintf(ficlog,"Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
9532: }
1.227 brouard 9533: printf("\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
9534: fprintf(ficlog,"\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 9535: pstamp(ficrespl);
1.203 brouard 9536: fprintf(ficrespl,"# Period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 9537: fprintf(ficrespl,"#Age ");
9538: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
9539: fprintf(ficrespl,"\n");
1.180 brouard 9540:
1.219 brouard 9541: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 9542:
1.219 brouard 9543: agebase=ageminpar;
9544: agelim=agemaxpar;
1.180 brouard 9545:
1.227 brouard 9546: /* i1=pow(2,ncoveff); */
1.234 brouard 9547: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 9548: if (cptcovn < 1){i1=1;}
1.180 brouard 9549:
1.238 brouard 9550: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
9551: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 9552: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 9553: continue;
1.235 brouard 9554:
1.238 brouard 9555: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
9556: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
9557: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
9558: /* k=k+1; */
9559: /* to clean */
9560: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
9561: fprintf(ficrespl,"#******");
9562: printf("#******");
9563: fprintf(ficlog,"#******");
9564: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
9565: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
9566: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9567: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9568: }
9569: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
9570: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9571: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9572: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9573: }
9574: fprintf(ficrespl,"******\n");
9575: printf("******\n");
9576: fprintf(ficlog,"******\n");
9577: if(invalidvarcomb[k]){
9578: printf("\nCombination (%d) ignored because no case \n",k);
9579: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
9580: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
9581: continue;
9582: }
1.219 brouard 9583:
1.238 brouard 9584: fprintf(ficrespl,"#Age ");
9585: for(j=1;j<=cptcoveff;j++) {
9586: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9587: }
9588: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
9589: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 9590:
1.238 brouard 9591: for (age=agebase; age<=agelim; age++){
9592: /* for (age=agebase; age<=agebase; age++){ */
9593: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
9594: fprintf(ficrespl,"%.0f ",age );
9595: for(j=1;j<=cptcoveff;j++)
9596: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9597: tot=0.;
9598: for(i=1; i<=nlstate;i++){
9599: tot += prlim[i][i];
9600: fprintf(ficrespl," %.5f", prlim[i][i]);
9601: }
9602: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
9603: } /* Age */
9604: /* was end of cptcod */
9605: } /* cptcov */
9606: } /* nres */
1.219 brouard 9607: return 0;
1.180 brouard 9608: }
9609:
1.218 brouard 9610: 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){
9611: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
9612:
9613: /* Computes the back prevalence limit for any combination of covariate values
9614: * at any age between ageminpar and agemaxpar
9615: */
1.235 brouard 9616: int i, j, k, i1, nres=0 ;
1.217 brouard 9617: /* double ftolpl = 1.e-10; */
9618: double age, agebase, agelim;
9619: double tot;
1.218 brouard 9620: /* double ***mobaverage; */
9621: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 9622:
9623: strcpy(fileresplb,"PLB_");
9624: strcat(fileresplb,fileresu);
9625: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
9626: printf("Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
9627: fprintf(ficlog,"Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
9628: }
9629: printf("Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
9630: fprintf(ficlog,"Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
9631: pstamp(ficresplb);
9632: fprintf(ficresplb,"# Period (stable) back prevalence. Precision given by ftolpl=%g \n", ftolpl);
9633: fprintf(ficresplb,"#Age ");
9634: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
9635: fprintf(ficresplb,"\n");
9636:
1.218 brouard 9637:
9638: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
9639:
9640: agebase=ageminpar;
9641: agelim=agemaxpar;
9642:
9643:
1.227 brouard 9644: i1=pow(2,cptcoveff);
1.218 brouard 9645: if (cptcovn < 1){i1=1;}
1.227 brouard 9646:
1.238 brouard 9647: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9648: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 9649: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 9650: continue;
9651: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
9652: fprintf(ficresplb,"#******");
9653: printf("#******");
9654: fprintf(ficlog,"#******");
9655: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
9656: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9657: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9658: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9659: }
9660: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
9661: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9662: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9663: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9664: }
9665: fprintf(ficresplb,"******\n");
9666: printf("******\n");
9667: fprintf(ficlog,"******\n");
9668: if(invalidvarcomb[k]){
9669: printf("\nCombination (%d) ignored because no cases \n",k);
9670: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
9671: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
9672: continue;
9673: }
1.218 brouard 9674:
1.238 brouard 9675: fprintf(ficresplb,"#Age ");
9676: for(j=1;j<=cptcoveff;j++) {
9677: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9678: }
9679: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
9680: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 9681:
9682:
1.238 brouard 9683: for (age=agebase; age<=agelim; age++){
9684: /* for (age=agebase; age<=agebase; age++){ */
9685: if(mobilavproj > 0){
9686: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
9687: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 9688: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 9689: }else if (mobilavproj == 0){
9690: 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);
9691: 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);
9692: exit(1);
9693: }else{
9694: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 9695: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.238 brouard 9696: }
9697: fprintf(ficresplb,"%.0f ",age );
9698: for(j=1;j<=cptcoveff;j++)
9699: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9700: tot=0.;
9701: for(i=1; i<=nlstate;i++){
9702: tot += bprlim[i][i];
9703: fprintf(ficresplb," %.5f", bprlim[i][i]);
9704: }
9705: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
9706: } /* Age */
9707: /* was end of cptcod */
1.255 brouard 9708: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 9709: } /* end of any combination */
9710: } /* end of nres */
1.218 brouard 9711: /* hBijx(p, bage, fage); */
9712: /* fclose(ficrespijb); */
9713:
9714: return 0;
1.217 brouard 9715: }
1.218 brouard 9716:
1.180 brouard 9717: int hPijx(double *p, int bage, int fage){
9718: /*------------- h Pij x at various ages ------------*/
9719:
9720: int stepsize;
9721: int agelim;
9722: int hstepm;
9723: int nhstepm;
1.235 brouard 9724: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 9725:
9726: double agedeb;
9727: double ***p3mat;
9728:
1.201 brouard 9729: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 9730: if((ficrespij=fopen(filerespij,"w"))==NULL) {
9731: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
9732: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
9733: }
9734: printf("Computing pij: result on file '%s' \n", filerespij);
9735: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
9736:
9737: stepsize=(int) (stepm+YEARM-1)/YEARM;
9738: /*if (stepm<=24) stepsize=2;*/
9739:
9740: agelim=AGESUP;
9741: hstepm=stepsize*YEARM; /* Every year of age */
9742: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 9743:
1.180 brouard 9744: /* hstepm=1; aff par mois*/
9745: pstamp(ficrespij);
9746: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 9747: i1= pow(2,cptcoveff);
1.218 brouard 9748: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
9749: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
9750: /* k=k+1; */
1.235 brouard 9751: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9752: for(k=1; k<=i1;k++){
1.253 brouard 9753: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 9754: continue;
1.183 brouard 9755: fprintf(ficrespij,"\n#****** ");
1.227 brouard 9756: for(j=1;j<=cptcoveff;j++)
1.198 brouard 9757: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 9758: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
9759: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9760: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9761: }
1.183 brouard 9762: fprintf(ficrespij,"******\n");
9763:
9764: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
9765: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
9766: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
9767:
9768: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 9769:
1.183 brouard 9770: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9771: oldm=oldms;savm=savms;
1.235 brouard 9772: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 9773: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
9774: for(i=1; i<=nlstate;i++)
9775: for(j=1; j<=nlstate+ndeath;j++)
9776: fprintf(ficrespij," %1d-%1d",i,j);
9777: fprintf(ficrespij,"\n");
9778: for (h=0; h<=nhstepm; h++){
9779: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
9780: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 9781: for(i=1; i<=nlstate;i++)
9782: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 9783: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 9784: fprintf(ficrespij,"\n");
9785: }
1.183 brouard 9786: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9787: fprintf(ficrespij,"\n");
9788: }
1.180 brouard 9789: /*}*/
9790: }
1.218 brouard 9791: return 0;
1.180 brouard 9792: }
1.218 brouard 9793:
9794: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 9795: /*------------- h Bij x at various ages ------------*/
9796:
9797: int stepsize;
1.218 brouard 9798: /* int agelim; */
9799: int ageminl;
1.217 brouard 9800: int hstepm;
9801: int nhstepm;
1.238 brouard 9802: int h, i, i1, j, k, nres;
1.218 brouard 9803:
1.217 brouard 9804: double agedeb;
9805: double ***p3mat;
1.218 brouard 9806:
9807: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
9808: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
9809: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
9810: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
9811: }
9812: printf("Computing pij back: result on file '%s' \n", filerespijb);
9813: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
9814:
9815: stepsize=(int) (stepm+YEARM-1)/YEARM;
9816: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 9817:
1.218 brouard 9818: /* agelim=AGESUP; */
9819: ageminl=30;
9820: hstepm=stepsize*YEARM; /* Every year of age */
9821: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
9822:
9823: /* hstepm=1; aff par mois*/
9824: pstamp(ficrespijb);
1.255 brouard 9825: 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 9826: i1= pow(2,cptcoveff);
1.218 brouard 9827: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
9828: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
9829: /* k=k+1; */
1.238 brouard 9830: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9831: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 9832: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 9833: continue;
9834: fprintf(ficrespijb,"\n#****** ");
9835: for(j=1;j<=cptcoveff;j++)
9836: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9837: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
9838: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9839: }
9840: fprintf(ficrespijb,"******\n");
1.264 ! brouard 9841: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 9842: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
9843: continue;
9844: }
9845:
9846: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
9847: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
9848: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
9849: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
9850: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
9851:
9852: /* nhstepm=nhstepm*YEARM; aff par mois*/
9853:
9854: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9855: /* oldm=oldms;savm=savms; */
9856: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
9857: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k);
9858: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 9859: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 9860: for(i=1; i<=nlstate;i++)
9861: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 9862: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 9863: fprintf(ficrespijb,"\n");
1.238 brouard 9864: for (h=0; h<=nhstepm; h++){
9865: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
9866: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
9867: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
9868: for(i=1; i<=nlstate;i++)
9869: for(j=1; j<=nlstate+ndeath;j++)
9870: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
9871: fprintf(ficrespijb,"\n");
9872: }
9873: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9874: fprintf(ficrespijb,"\n");
9875: } /* end age deb */
9876: } /* end combination */
9877: } /* end nres */
1.218 brouard 9878: return 0;
9879: } /* hBijx */
1.217 brouard 9880:
1.180 brouard 9881:
1.136 brouard 9882: /***********************************************/
9883: /**************** Main Program *****************/
9884: /***********************************************/
9885:
9886: int main(int argc, char *argv[])
9887: {
9888: #ifdef GSL
9889: const gsl_multimin_fminimizer_type *T;
9890: size_t iteri = 0, it;
9891: int rval = GSL_CONTINUE;
9892: int status = GSL_SUCCESS;
9893: double ssval;
9894: #endif
9895: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.164 brouard 9896: int i,j, k, n=MAXN,iter=0,m,size=100, cptcod;
1.209 brouard 9897: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 9898: int jj, ll, li, lj, lk;
1.136 brouard 9899: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 9900: int num_filled;
1.136 brouard 9901: int itimes;
9902: int NDIM=2;
9903: int vpopbased=0;
1.235 brouard 9904: int nres=0;
1.258 brouard 9905: int endishere=0;
1.136 brouard 9906:
1.164 brouard 9907: char ca[32], cb[32];
1.136 brouard 9908: /* FILE *fichtm; *//* Html File */
9909: /* FILE *ficgp;*/ /*Gnuplot File */
9910: struct stat info;
1.191 brouard 9911: double agedeb=0.;
1.194 brouard 9912:
9913: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 9914: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 9915:
1.165 brouard 9916: double fret;
1.191 brouard 9917: double dum=0.; /* Dummy variable */
1.136 brouard 9918: double ***p3mat;
1.218 brouard 9919: /* double ***mobaverage; */
1.164 brouard 9920:
9921: char line[MAXLINE];
1.197 brouard 9922: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
9923:
1.234 brouard 9924: char modeltemp[MAXLINE];
1.230 brouard 9925: char resultline[MAXLINE];
9926:
1.136 brouard 9927: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 9928: char *tok, *val; /* pathtot */
1.136 brouard 9929: int firstobs=1, lastobs=10;
1.195 brouard 9930: int c, h , cpt, c2;
1.191 brouard 9931: int jl=0;
9932: int i1, j1, jk, stepsize=0;
1.194 brouard 9933: int count=0;
9934:
1.164 brouard 9935: int *tab;
1.136 brouard 9936: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.217 brouard 9937: int backcast=0;
1.136 brouard 9938: int mobilav=0,popforecast=0;
1.191 brouard 9939: int hstepm=0, nhstepm=0;
1.136 brouard 9940: int agemortsup;
9941: float sumlpop=0.;
9942: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
9943: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
9944:
1.191 brouard 9945: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 9946: double ftolpl=FTOL;
9947: double **prlim;
1.217 brouard 9948: double **bprlim;
1.136 brouard 9949: double ***param; /* Matrix of parameters */
1.251 brouard 9950: double ***paramstart; /* Matrix of starting parameter values */
9951: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 9952: double **matcov; /* Matrix of covariance */
1.203 brouard 9953: double **hess; /* Hessian matrix */
1.136 brouard 9954: double ***delti3; /* Scale */
9955: double *delti; /* Scale */
9956: double ***eij, ***vareij;
9957: double **varpl; /* Variances of prevalence limits by age */
9958: double *epj, vepp;
1.164 brouard 9959:
1.136 brouard 9960: double dateprev1, dateprev2,jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000;
1.217 brouard 9961: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000;
9962:
1.136 brouard 9963: double **ximort;
1.145 brouard 9964: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 9965: int *dcwave;
9966:
1.164 brouard 9967: char z[1]="c";
1.136 brouard 9968:
9969: /*char *strt;*/
9970: char strtend[80];
1.126 brouard 9971:
1.164 brouard 9972:
1.126 brouard 9973: /* setlocale (LC_ALL, ""); */
9974: /* bindtextdomain (PACKAGE, LOCALEDIR); */
9975: /* textdomain (PACKAGE); */
9976: /* setlocale (LC_CTYPE, ""); */
9977: /* setlocale (LC_MESSAGES, ""); */
9978:
9979: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 9980: rstart_time = time(NULL);
9981: /* (void) gettimeofday(&start_time,&tzp);*/
9982: start_time = *localtime(&rstart_time);
1.126 brouard 9983: curr_time=start_time;
1.157 brouard 9984: /*tml = *localtime(&start_time.tm_sec);*/
9985: /* strcpy(strstart,asctime(&tml)); */
9986: strcpy(strstart,asctime(&start_time));
1.126 brouard 9987:
9988: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 9989: /* tp.tm_sec = tp.tm_sec +86400; */
9990: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 9991: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
9992: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
9993: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 9994: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 9995: /* strt=asctime(&tmg); */
9996: /* printf("Time(after) =%s",strstart); */
9997: /* (void) time (&time_value);
9998: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
9999: * tm = *localtime(&time_value);
10000: * strstart=asctime(&tm);
10001: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
10002: */
10003:
10004: nberr=0; /* Number of errors and warnings */
10005: nbwarn=0;
1.184 brouard 10006: #ifdef WIN32
10007: _getcwd(pathcd, size);
10008: #else
1.126 brouard 10009: getcwd(pathcd, size);
1.184 brouard 10010: #endif
1.191 brouard 10011: syscompilerinfo(0);
1.196 brouard 10012: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 10013: if(argc <=1){
10014: printf("\nEnter the parameter file name: ");
1.205 brouard 10015: if(!fgets(pathr,FILENAMELENGTH,stdin)){
10016: printf("ERROR Empty parameter file name\n");
10017: goto end;
10018: }
1.126 brouard 10019: i=strlen(pathr);
10020: if(pathr[i-1]=='\n')
10021: pathr[i-1]='\0';
1.156 brouard 10022: i=strlen(pathr);
1.205 brouard 10023: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 10024: pathr[i-1]='\0';
1.205 brouard 10025: }
10026: i=strlen(pathr);
10027: if( i==0 ){
10028: printf("ERROR Empty parameter file name\n");
10029: goto end;
10030: }
10031: for (tok = pathr; tok != NULL; ){
1.126 brouard 10032: printf("Pathr |%s|\n",pathr);
10033: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
10034: printf("val= |%s| pathr=%s\n",val,pathr);
10035: strcpy (pathtot, val);
10036: if(pathr[0] == '\0') break; /* Dirty */
10037: }
10038: }
10039: else{
10040: strcpy(pathtot,argv[1]);
10041: }
10042: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
10043: /*cygwin_split_path(pathtot,path,optionfile);
10044: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
10045: /* cutv(path,optionfile,pathtot,'\\');*/
10046:
10047: /* Split argv[0], imach program to get pathimach */
10048: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
10049: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10050: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10051: /* strcpy(pathimach,argv[0]); */
10052: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
10053: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
10054: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 10055: #ifdef WIN32
10056: _chdir(path); /* Can be a relative path */
10057: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
10058: #else
1.126 brouard 10059: chdir(path); /* Can be a relative path */
1.184 brouard 10060: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
10061: #endif
10062: printf("Current directory %s!\n",pathcd);
1.126 brouard 10063: strcpy(command,"mkdir ");
10064: strcat(command,optionfilefiname);
10065: if((outcmd=system(command)) != 0){
1.169 brouard 10066: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 10067: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
10068: /* fclose(ficlog); */
10069: /* exit(1); */
10070: }
10071: /* if((imk=mkdir(optionfilefiname))<0){ */
10072: /* perror("mkdir"); */
10073: /* } */
10074:
10075: /*-------- arguments in the command line --------*/
10076:
1.186 brouard 10077: /* Main Log file */
1.126 brouard 10078: strcat(filelog, optionfilefiname);
10079: strcat(filelog,".log"); /* */
10080: if((ficlog=fopen(filelog,"w"))==NULL) {
10081: printf("Problem with logfile %s\n",filelog);
10082: goto end;
10083: }
10084: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 10085: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 10086: fprintf(ficlog,"\nEnter the parameter file name: \n");
10087: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
10088: path=%s \n\
10089: optionfile=%s\n\
10090: optionfilext=%s\n\
1.156 brouard 10091: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 10092:
1.197 brouard 10093: syscompilerinfo(1);
1.167 brouard 10094:
1.126 brouard 10095: printf("Local time (at start):%s",strstart);
10096: fprintf(ficlog,"Local time (at start): %s",strstart);
10097: fflush(ficlog);
10098: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 10099: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 10100:
10101: /* */
10102: strcpy(fileres,"r");
10103: strcat(fileres, optionfilefiname);
1.201 brouard 10104: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 10105: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 10106: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 10107:
1.186 brouard 10108: /* Main ---------arguments file --------*/
1.126 brouard 10109:
10110: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 10111: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
10112: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 10113: fflush(ficlog);
1.149 brouard 10114: /* goto end; */
10115: exit(70);
1.126 brouard 10116: }
10117:
10118:
10119:
10120: strcpy(filereso,"o");
1.201 brouard 10121: strcat(filereso,fileresu);
1.126 brouard 10122: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
10123: printf("Problem with Output resultfile: %s\n", filereso);
10124: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
10125: fflush(ficlog);
10126: goto end;
10127: }
10128:
10129: /* Reads comments: lines beginning with '#' */
10130: numlinepar=0;
1.197 brouard 10131:
10132: /* First parameter line */
10133: while(fgets(line, MAXLINE, ficpar)) {
10134: /* If line starts with a # it is a comment */
10135: if (line[0] == '#') {
10136: numlinepar++;
10137: fputs(line,stdout);
10138: fputs(line,ficparo);
10139: fputs(line,ficlog);
10140: continue;
10141: }else
10142: break;
10143: }
10144: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
10145: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
10146: if (num_filled != 5) {
10147: printf("Should be 5 parameters\n");
10148: }
1.126 brouard 10149: numlinepar++;
1.197 brouard 10150: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
10151: }
10152: /* Second parameter line */
10153: while(fgets(line, MAXLINE, ficpar)) {
10154: /* If line starts with a # it is a comment */
10155: if (line[0] == '#') {
10156: numlinepar++;
10157: fputs(line,stdout);
10158: fputs(line,ficparo);
10159: fputs(line,ficlog);
10160: continue;
10161: }else
10162: break;
10163: }
1.223 brouard 10164: 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", \
10165: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
10166: if (num_filled != 11) {
10167: 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 10168: printf("but line=%s\n",line);
1.197 brouard 10169: }
1.223 brouard 10170: 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);
1.126 brouard 10171: }
1.203 brouard 10172: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 10173: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 10174: /* Third parameter line */
10175: while(fgets(line, MAXLINE, ficpar)) {
10176: /* If line starts with a # it is a comment */
10177: if (line[0] == '#') {
10178: numlinepar++;
10179: fputs(line,stdout);
10180: fputs(line,ficparo);
10181: fputs(line,ficlog);
10182: continue;
10183: }else
10184: break;
10185: }
1.201 brouard 10186: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.263 brouard 10187: if (num_filled == 0){
10188: printf("ERROR %d: Model should be at minimum 'model=1+age.' WITHOUT space:'%s'\n",num_filled, line);
10189: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age.' WITHOUT space:'%s'\n",num_filled, line);
10190: model[0]='\0';
10191: goto end;
10192: } else if (num_filled != 1){
1.197 brouard 10193: printf("ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line);
10194: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line);
10195: model[0]='\0';
10196: goto end;
10197: }
10198: else{
10199: if (model[0]=='+'){
10200: for(i=1; i<=strlen(model);i++)
10201: modeltemp[i-1]=model[i];
1.201 brouard 10202: strcpy(model,modeltemp);
1.197 brouard 10203: }
10204: }
1.199 brouard 10205: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 10206: printf("model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 10207: }
10208: /* 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); */
10209: /* numlinepar=numlinepar+3; /\* In general *\/ */
10210: /* 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); */
1.223 brouard 10211: 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);
10212: 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 10213: fflush(ficlog);
1.190 brouard 10214: /* if(model[0]=='#'|| model[0]== '\0'){ */
10215: if(model[0]=='#'){
1.187 brouard 10216: printf("Error in 'model' line: model should start with 'model=1+age+' and end with '.' \n \
10217: 'model=1+age+.' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age.' or \n \
10218: 'model=1+age+V1+V2.' or 'model=1+age+V1+V2+V1*V2.' etc. \n"); \
10219: if(mle != -1){
10220: printf("Fix the model line and run imach with mle=-1 to get a correct template of the parameter file.\n");
10221: exit(1);
10222: }
10223: }
1.126 brouard 10224: while((c=getc(ficpar))=='#' && c!= EOF){
10225: ungetc(c,ficpar);
10226: fgets(line, MAXLINE, ficpar);
10227: numlinepar++;
1.195 brouard 10228: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
10229: z[0]=line[1];
10230: }
10231: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 10232: fputs(line, stdout);
10233: //puts(line);
1.126 brouard 10234: fputs(line,ficparo);
10235: fputs(line,ficlog);
10236: }
10237: ungetc(c,ficpar);
10238:
10239:
1.145 brouard 10240: covar=matrix(0,NCOVMAX,1,n); /**< used in readdata */
1.225 brouard 10241: coqvar=matrix(1,nqv,1,n); /**< Fixed quantitative covariate */
1.233 brouard 10242: cotvar=ma3x(1,maxwav,1,ntv+nqtv,1,n); /**< Time varying covariate (dummy and quantitative)*/
1.225 brouard 10243: cotqvar=ma3x(1,maxwav,1,nqtv,1,n); /**< Time varying quantitative covariate */
1.136 brouard 10244: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
10245: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
10246: v1+v2*age+v2*v3 makes cptcovn = 3
10247: */
10248: if (strlen(model)>1)
1.187 brouard 10249: 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 10250: else
1.187 brouard 10251: ncovmodel=2; /* Constant and age */
1.133 brouard 10252: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
10253: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 10254: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
10255: 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);
10256: 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);
10257: fflush(stdout);
10258: fclose (ficlog);
10259: goto end;
10260: }
1.126 brouard 10261: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
10262: delti=delti3[1][1];
10263: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
10264: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 10265: /* We could also provide initial parameters values giving by simple logistic regression
10266: * only one way, that is without matrix product. We will have nlstate maximizations */
10267: /* for(i=1;i<nlstate;i++){ */
10268: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
10269: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
10270: /* } */
1.126 brouard 10271: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 10272: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
10273: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 10274: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
10275: fclose (ficparo);
10276: fclose (ficlog);
10277: goto end;
10278: exit(0);
1.220 brouard 10279: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 10280: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 10281: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
10282: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 10283: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
10284: matcov=matrix(1,npar,1,npar);
1.203 brouard 10285: hess=matrix(1,npar,1,npar);
1.220 brouard 10286: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 10287: /* Read guessed parameters */
1.126 brouard 10288: /* Reads comments: lines beginning with '#' */
10289: while((c=getc(ficpar))=='#' && c!= EOF){
10290: ungetc(c,ficpar);
10291: fgets(line, MAXLINE, ficpar);
10292: numlinepar++;
1.141 brouard 10293: fputs(line,stdout);
1.126 brouard 10294: fputs(line,ficparo);
10295: fputs(line,ficlog);
10296: }
10297: ungetc(c,ficpar);
10298:
10299: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 10300: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 10301: for(i=1; i <=nlstate; i++){
1.234 brouard 10302: j=0;
1.126 brouard 10303: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 10304: if(jj==i) continue;
10305: j++;
10306: fscanf(ficpar,"%1d%1d",&i1,&j1);
10307: if ((i1 != i) || (j1 != jj)){
10308: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 10309: It might be a problem of design; if ncovcol and the model are correct\n \
10310: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 10311: exit(1);
10312: }
10313: fprintf(ficparo,"%1d%1d",i1,j1);
10314: if(mle==1)
10315: printf("%1d%1d",i,jj);
10316: fprintf(ficlog,"%1d%1d",i,jj);
10317: for(k=1; k<=ncovmodel;k++){
10318: fscanf(ficpar," %lf",¶m[i][j][k]);
10319: if(mle==1){
10320: printf(" %lf",param[i][j][k]);
10321: fprintf(ficlog," %lf",param[i][j][k]);
10322: }
10323: else
10324: fprintf(ficlog," %lf",param[i][j][k]);
10325: fprintf(ficparo," %lf",param[i][j][k]);
10326: }
10327: fscanf(ficpar,"\n");
10328: numlinepar++;
10329: if(mle==1)
10330: printf("\n");
10331: fprintf(ficlog,"\n");
10332: fprintf(ficparo,"\n");
1.126 brouard 10333: }
10334: }
10335: fflush(ficlog);
1.234 brouard 10336:
1.251 brouard 10337: /* Reads parameters values */
1.126 brouard 10338: p=param[1][1];
1.251 brouard 10339: pstart=paramstart[1][1];
1.126 brouard 10340:
10341: /* Reads comments: lines beginning with '#' */
10342: while((c=getc(ficpar))=='#' && c!= EOF){
10343: ungetc(c,ficpar);
10344: fgets(line, MAXLINE, ficpar);
10345: numlinepar++;
1.141 brouard 10346: fputs(line,stdout);
1.126 brouard 10347: fputs(line,ficparo);
10348: fputs(line,ficlog);
10349: }
10350: ungetc(c,ficpar);
10351:
10352: for(i=1; i <=nlstate; i++){
10353: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 10354: fscanf(ficpar,"%1d%1d",&i1,&j1);
10355: if ( (i1-i) * (j1-j) != 0){
10356: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
10357: exit(1);
10358: }
10359: printf("%1d%1d",i,j);
10360: fprintf(ficparo,"%1d%1d",i1,j1);
10361: fprintf(ficlog,"%1d%1d",i1,j1);
10362: for(k=1; k<=ncovmodel;k++){
10363: fscanf(ficpar,"%le",&delti3[i][j][k]);
10364: printf(" %le",delti3[i][j][k]);
10365: fprintf(ficparo," %le",delti3[i][j][k]);
10366: fprintf(ficlog," %le",delti3[i][j][k]);
10367: }
10368: fscanf(ficpar,"\n");
10369: numlinepar++;
10370: printf("\n");
10371: fprintf(ficparo,"\n");
10372: fprintf(ficlog,"\n");
1.126 brouard 10373: }
10374: }
10375: fflush(ficlog);
1.234 brouard 10376:
1.145 brouard 10377: /* Reads covariance matrix */
1.126 brouard 10378: delti=delti3[1][1];
1.220 brouard 10379:
10380:
1.126 brouard 10381: /* 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 10382:
1.126 brouard 10383: /* Reads comments: lines beginning with '#' */
10384: while((c=getc(ficpar))=='#' && c!= EOF){
10385: ungetc(c,ficpar);
10386: fgets(line, MAXLINE, ficpar);
10387: numlinepar++;
1.141 brouard 10388: fputs(line,stdout);
1.126 brouard 10389: fputs(line,ficparo);
10390: fputs(line,ficlog);
10391: }
10392: ungetc(c,ficpar);
1.220 brouard 10393:
1.126 brouard 10394: matcov=matrix(1,npar,1,npar);
1.203 brouard 10395: hess=matrix(1,npar,1,npar);
1.131 brouard 10396: for(i=1; i <=npar; i++)
10397: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 10398:
1.194 brouard 10399: /* Scans npar lines */
1.126 brouard 10400: for(i=1; i <=npar; i++){
1.226 brouard 10401: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 10402: if(count != 3){
1.226 brouard 10403: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 10404: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
10405: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 10406: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 10407: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
10408: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 10409: exit(1);
1.220 brouard 10410: }else{
1.226 brouard 10411: if(mle==1)
10412: printf("%1d%1d%d",i1,j1,jk);
10413: }
10414: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
10415: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 10416: for(j=1; j <=i; j++){
1.226 brouard 10417: fscanf(ficpar," %le",&matcov[i][j]);
10418: if(mle==1){
10419: printf(" %.5le",matcov[i][j]);
10420: }
10421: fprintf(ficlog," %.5le",matcov[i][j]);
10422: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 10423: }
10424: fscanf(ficpar,"\n");
10425: numlinepar++;
10426: if(mle==1)
1.220 brouard 10427: printf("\n");
1.126 brouard 10428: fprintf(ficlog,"\n");
10429: fprintf(ficparo,"\n");
10430: }
1.194 brouard 10431: /* End of read covariance matrix npar lines */
1.126 brouard 10432: for(i=1; i <=npar; i++)
10433: for(j=i+1;j<=npar;j++)
1.226 brouard 10434: matcov[i][j]=matcov[j][i];
1.126 brouard 10435:
10436: if(mle==1)
10437: printf("\n");
10438: fprintf(ficlog,"\n");
10439:
10440: fflush(ficlog);
10441:
10442: /*-------- Rewriting parameter file ----------*/
10443: strcpy(rfileres,"r"); /* "Rparameterfile */
10444: strcat(rfileres,optionfilefiname); /* Parameter file first name*/
10445: strcat(rfileres,"."); /* */
10446: strcat(rfileres,optionfilext); /* Other files have txt extension */
10447: if((ficres =fopen(rfileres,"w"))==NULL) {
1.201 brouard 10448: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
10449: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
1.126 brouard 10450: }
10451: fprintf(ficres,"#%s\n",version);
10452: } /* End of mle != -3 */
1.218 brouard 10453:
1.186 brouard 10454: /* Main data
10455: */
1.126 brouard 10456: n= lastobs;
10457: num=lvector(1,n);
10458: moisnais=vector(1,n);
10459: annais=vector(1,n);
10460: moisdc=vector(1,n);
10461: andc=vector(1,n);
1.220 brouard 10462: weight=vector(1,n);
1.126 brouard 10463: agedc=vector(1,n);
10464: cod=ivector(1,n);
1.220 brouard 10465: for(i=1;i<=n;i++){
1.234 brouard 10466: num[i]=0;
10467: moisnais[i]=0;
10468: annais[i]=0;
10469: moisdc[i]=0;
10470: andc[i]=0;
10471: agedc[i]=0;
10472: cod[i]=0;
10473: weight[i]=1.0; /* Equal weights, 1 by default */
10474: }
1.126 brouard 10475: mint=matrix(1,maxwav,1,n);
10476: anint=matrix(1,maxwav,1,n);
1.131 brouard 10477: s=imatrix(1,maxwav+1,1,n); /* s[i][j] health state for wave i and individual j */
1.126 brouard 10478: tab=ivector(1,NCOVMAX);
1.144 brouard 10479: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 10480: 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 10481:
1.136 brouard 10482: /* Reads data from file datafile */
10483: if (readdata(datafile, firstobs, lastobs, &imx)==1)
10484: goto end;
10485:
10486: /* Calculation of the number of parameters from char model */
1.234 brouard 10487: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 10488: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
10489: k=3 V4 Tvar[k=3]= 4 (from V4)
10490: k=2 V1 Tvar[k=2]= 1 (from V1)
10491: k=1 Tvar[1]=2 (from V2)
1.234 brouard 10492: */
10493:
10494: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
10495: TvarsDind=ivector(1,NCOVMAX); /* */
10496: TvarsD=ivector(1,NCOVMAX); /* */
10497: TvarsQind=ivector(1,NCOVMAX); /* */
10498: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 10499: TvarF=ivector(1,NCOVMAX); /* */
10500: TvarFind=ivector(1,NCOVMAX); /* */
10501: TvarV=ivector(1,NCOVMAX); /* */
10502: TvarVind=ivector(1,NCOVMAX); /* */
10503: TvarA=ivector(1,NCOVMAX); /* */
10504: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 10505: TvarFD=ivector(1,NCOVMAX); /* */
10506: TvarFDind=ivector(1,NCOVMAX); /* */
10507: TvarFQ=ivector(1,NCOVMAX); /* */
10508: TvarFQind=ivector(1,NCOVMAX); /* */
10509: TvarVD=ivector(1,NCOVMAX); /* */
10510: TvarVDind=ivector(1,NCOVMAX); /* */
10511: TvarVQ=ivector(1,NCOVMAX); /* */
10512: TvarVQind=ivector(1,NCOVMAX); /* */
10513:
1.230 brouard 10514: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 10515: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 10516: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
10517: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
10518: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 10519: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
10520: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
10521: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
10522: */
10523: /* For model-covariate k tells which data-covariate to use but
10524: because this model-covariate is a construction we invent a new column
10525: ncovcol + k1
10526: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
10527: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 10528: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
10529: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 10530: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
10531: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 10532: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 10533: */
1.145 brouard 10534: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
10535: 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 10536: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
10537: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 10538: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 10539: 4 covariates (3 plus signs)
10540: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
10541: */
1.230 brouard 10542: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 10543: * individual dummy, fixed or varying:
10544: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
10545: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 10546: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
10547: * V1 df, V2 qf, V3 & V4 dv, V5 qv
10548: * Tmodelind[1]@9={9,0,3,2,}*/
10549: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
10550: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 10551: * individual quantitative, fixed or varying:
10552: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
10553: * 3, 1, 0, 0, 0, 0, 0, 0},
10554: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 10555: /* Main decodemodel */
10556:
1.187 brouard 10557:
1.223 brouard 10558: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 10559: goto end;
10560:
1.137 brouard 10561: if((double)(lastobs-imx)/(double)imx > 1.10){
10562: nbwarn++;
10563: 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);
10564: 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);
10565: }
1.136 brouard 10566: /* if(mle==1){*/
1.137 brouard 10567: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
10568: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 10569: }
10570:
10571: /*-calculation of age at interview from date of interview and age at death -*/
10572: agev=matrix(1,maxwav,1,imx);
10573:
10574: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
10575: goto end;
10576:
1.126 brouard 10577:
1.136 brouard 10578: agegomp=(int)agemin;
10579: free_vector(moisnais,1,n);
10580: free_vector(annais,1,n);
1.126 brouard 10581: /* free_matrix(mint,1,maxwav,1,n);
10582: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 10583: /* free_vector(moisdc,1,n); */
10584: /* free_vector(andc,1,n); */
1.145 brouard 10585: /* */
10586:
1.126 brouard 10587: wav=ivector(1,imx);
1.214 brouard 10588: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
10589: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
10590: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
10591: 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.*/
10592: bh=imatrix(1,lastpass-firstpass+2,1,imx);
10593: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 10594:
10595: /* Concatenates waves */
1.214 brouard 10596: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
10597: Death is a valid wave (if date is known).
10598: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
10599: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
10600: and mw[mi+1][i]. dh depends on stepm.
10601: */
10602:
1.126 brouard 10603: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 10604: /* Concatenates waves */
1.145 brouard 10605:
1.215 brouard 10606: free_vector(moisdc,1,n);
10607: free_vector(andc,1,n);
10608:
1.126 brouard 10609: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
10610: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
10611: ncodemax[1]=1;
1.145 brouard 10612: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 10613: cptcoveff=0;
1.220 brouard 10614: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
10615: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 10616: }
10617:
10618: ncovcombmax=pow(2,cptcoveff);
10619: invalidvarcomb=ivector(1, ncovcombmax);
10620: for(i=1;i<ncovcombmax;i++)
10621: invalidvarcomb[i]=0;
10622:
1.211 brouard 10623: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 10624: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 10625: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 10626:
1.200 brouard 10627: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 10628: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 10629: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 10630: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
10631: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
10632: * (currently 0 or 1) in the data.
10633: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
10634: * corresponding modality (h,j).
10635: */
10636:
1.145 brouard 10637: h=0;
10638: /*if (cptcovn > 0) */
1.126 brouard 10639: m=pow(2,cptcoveff);
10640:
1.144 brouard 10641: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 10642: * For k=4 covariates, h goes from 1 to m=2**k
10643: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
10644: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 10645: * h\k 1 2 3 4
1.143 brouard 10646: *______________________________
10647: * 1 i=1 1 i=1 1 i=1 1 i=1 1
10648: * 2 2 1 1 1
10649: * 3 i=2 1 2 1 1
10650: * 4 2 2 1 1
10651: * 5 i=3 1 i=2 1 2 1
10652: * 6 2 1 2 1
10653: * 7 i=4 1 2 2 1
10654: * 8 2 2 2 1
1.197 brouard 10655: * 9 i=5 1 i=3 1 i=2 1 2
10656: * 10 2 1 1 2
10657: * 11 i=6 1 2 1 2
10658: * 12 2 2 1 2
10659: * 13 i=7 1 i=4 1 2 2
10660: * 14 2 1 2 2
10661: * 15 i=8 1 2 2 2
10662: * 16 2 2 2 2
1.143 brouard 10663: */
1.212 brouard 10664: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 10665: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
10666: * and the value of each covariate?
10667: * V1=1, V2=1, V3=2, V4=1 ?
10668: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
10669: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
10670: * In order to get the real value in the data, we use nbcode
10671: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
10672: * We are keeping this crazy system in order to be able (in the future?)
10673: * to have more than 2 values (0 or 1) for a covariate.
10674: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
10675: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
10676: * bbbbbbbb
10677: * 76543210
10678: * h-1 00000101 (6-1=5)
1.219 brouard 10679: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 10680: * &
10681: * 1 00000001 (1)
1.219 brouard 10682: * 00000000 = 1 & ((h-1) >> (k-1))
10683: * +1= 00000001 =1
1.211 brouard 10684: *
10685: * h=14, k=3 => h'=h-1=13, k'=k-1=2
10686: * h' 1101 =2^3+2^2+0x2^1+2^0
10687: * >>k' 11
10688: * & 00000001
10689: * = 00000001
10690: * +1 = 00000010=2 = codtabm(14,3)
10691: * Reverse h=6 and m=16?
10692: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
10693: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
10694: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
10695: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
10696: * V3=decodtabm(14,3,2**4)=2
10697: * h'=13 1101 =2^3+2^2+0x2^1+2^0
10698: *(h-1) >> (j-1) 0011 =13 >> 2
10699: * &1 000000001
10700: * = 000000001
10701: * +1= 000000010 =2
10702: * 2211
10703: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
10704: * V3=2
1.220 brouard 10705: * codtabm and decodtabm are identical
1.211 brouard 10706: */
10707:
1.145 brouard 10708:
10709: free_ivector(Ndum,-1,NCOVMAX);
10710:
10711:
1.126 brouard 10712:
1.186 brouard 10713: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 10714: strcpy(optionfilegnuplot,optionfilefiname);
10715: if(mle==-3)
1.201 brouard 10716: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 10717: strcat(optionfilegnuplot,".gp");
10718:
10719: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
10720: printf("Problem with file %s",optionfilegnuplot);
10721: }
10722: else{
1.204 brouard 10723: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 10724: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 10725: //fprintf(ficgp,"set missing 'NaNq'\n");
10726: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 10727: }
10728: /* fclose(ficgp);*/
1.186 brouard 10729:
10730:
10731: /* Initialisation of --------- index.htm --------*/
1.126 brouard 10732:
10733: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
10734: if(mle==-3)
1.201 brouard 10735: strcat(optionfilehtm,"-MORT_");
1.126 brouard 10736: strcat(optionfilehtm,".htm");
10737: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 10738: printf("Problem with %s \n",optionfilehtm);
10739: exit(0);
1.126 brouard 10740: }
10741:
10742: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
10743: strcat(optionfilehtmcov,"-cov.htm");
10744: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
10745: printf("Problem with %s \n",optionfilehtmcov), exit(0);
10746: }
10747: else{
10748: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
10749: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 10750: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 10751: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
10752: }
10753:
1.213 brouard 10754: 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 10755: <hr size=\"2\" color=\"#EC5E5E\"> \n\
10756: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 10757: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 10758: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 10759: \n\
10760: <hr size=\"2\" color=\"#EC5E5E\">\
10761: <ul><li><h4>Parameter files</h4>\n\
10762: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
10763: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
10764: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
10765: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
10766: - Date and time at start: %s</ul>\n",\
10767: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
10768: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
10769: fileres,fileres,\
10770: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
10771: fflush(fichtm);
10772:
10773: strcpy(pathr,path);
10774: strcat(pathr,optionfilefiname);
1.184 brouard 10775: #ifdef WIN32
10776: _chdir(optionfilefiname); /* Move to directory named optionfile */
10777: #else
1.126 brouard 10778: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 10779: #endif
10780:
1.126 brouard 10781:
1.220 brouard 10782: /* Calculates basic frequencies. Computes observed prevalence at single age
10783: and for any valid combination of covariates
1.126 brouard 10784: and prints on file fileres'p'. */
1.251 brouard 10785: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 10786: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 10787:
10788: fprintf(fichtm,"\n");
10789: fprintf(fichtm,"<br>Total number of observations=%d <br>\n\
10790: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
10791: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
10792: imx,agemin,agemax,jmin,jmax,jmean);
10793: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.220 brouard 10794: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
10795: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
10796: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
10797: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 10798:
1.126 brouard 10799: /* For Powell, parameters are in a vector p[] starting at p[1]
10800: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
10801: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
10802:
10803: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 10804: /* For mortality only */
1.126 brouard 10805: if (mle==-3){
1.136 brouard 10806: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 10807: for(i=1;i<=NDIM;i++)
10808: for(j=1;j<=NDIM;j++)
10809: ximort[i][j]=0.;
1.186 brouard 10810: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.126 brouard 10811: cens=ivector(1,n);
10812: ageexmed=vector(1,n);
10813: agecens=vector(1,n);
10814: dcwave=ivector(1,n);
1.223 brouard 10815:
1.126 brouard 10816: for (i=1; i<=imx; i++){
10817: dcwave[i]=-1;
10818: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 10819: if (s[m][i]>nlstate) {
10820: dcwave[i]=m;
10821: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
10822: break;
10823: }
1.126 brouard 10824: }
1.226 brouard 10825:
1.126 brouard 10826: for (i=1; i<=imx; i++) {
10827: if (wav[i]>0){
1.226 brouard 10828: ageexmed[i]=agev[mw[1][i]][i];
10829: j=wav[i];
10830: agecens[i]=1.;
10831:
10832: if (ageexmed[i]> 1 && wav[i] > 0){
10833: agecens[i]=agev[mw[j][i]][i];
10834: cens[i]= 1;
10835: }else if (ageexmed[i]< 1)
10836: cens[i]= -1;
10837: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
10838: cens[i]=0 ;
1.126 brouard 10839: }
10840: else cens[i]=-1;
10841: }
10842:
10843: for (i=1;i<=NDIM;i++) {
10844: for (j=1;j<=NDIM;j++)
1.226 brouard 10845: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 10846: }
10847:
1.145 brouard 10848: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 10849: /*printf("%lf %lf", p[1], p[2]);*/
10850:
10851:
1.136 brouard 10852: #ifdef GSL
10853: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 10854: #else
1.126 brouard 10855: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 10856: #endif
1.201 brouard 10857: strcpy(filerespow,"POW-MORT_");
10858: strcat(filerespow,fileresu);
1.126 brouard 10859: if((ficrespow=fopen(filerespow,"w"))==NULL) {
10860: printf("Problem with resultfile: %s\n", filerespow);
10861: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
10862: }
1.136 brouard 10863: #ifdef GSL
10864: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 10865: #else
1.126 brouard 10866: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 10867: #endif
1.126 brouard 10868: /* for (i=1;i<=nlstate;i++)
10869: for(j=1;j<=nlstate+ndeath;j++)
10870: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
10871: */
10872: fprintf(ficrespow,"\n");
1.136 brouard 10873: #ifdef GSL
10874: /* gsl starts here */
10875: T = gsl_multimin_fminimizer_nmsimplex;
10876: gsl_multimin_fminimizer *sfm = NULL;
10877: gsl_vector *ss, *x;
10878: gsl_multimin_function minex_func;
10879:
10880: /* Initial vertex size vector */
10881: ss = gsl_vector_alloc (NDIM);
10882:
10883: if (ss == NULL){
10884: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
10885: }
10886: /* Set all step sizes to 1 */
10887: gsl_vector_set_all (ss, 0.001);
10888:
10889: /* Starting point */
1.126 brouard 10890:
1.136 brouard 10891: x = gsl_vector_alloc (NDIM);
10892:
10893: if (x == NULL){
10894: gsl_vector_free(ss);
10895: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
10896: }
10897:
10898: /* Initialize method and iterate */
10899: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 10900: /* gsl_vector_set(x, 0, 0.0268); */
10901: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 10902: gsl_vector_set(x, 0, p[1]);
10903: gsl_vector_set(x, 1, p[2]);
10904:
10905: minex_func.f = &gompertz_f;
10906: minex_func.n = NDIM;
10907: minex_func.params = (void *)&p; /* ??? */
10908:
10909: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
10910: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
10911:
10912: printf("Iterations beginning .....\n\n");
10913: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
10914:
10915: iteri=0;
10916: while (rval == GSL_CONTINUE){
10917: iteri++;
10918: status = gsl_multimin_fminimizer_iterate(sfm);
10919:
10920: if (status) printf("error: %s\n", gsl_strerror (status));
10921: fflush(0);
10922:
10923: if (status)
10924: break;
10925:
10926: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
10927: ssval = gsl_multimin_fminimizer_size (sfm);
10928:
10929: if (rval == GSL_SUCCESS)
10930: printf ("converged to a local maximum at\n");
10931:
10932: printf("%5d ", iteri);
10933: for (it = 0; it < NDIM; it++){
10934: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
10935: }
10936: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
10937: }
10938:
10939: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
10940:
10941: gsl_vector_free(x); /* initial values */
10942: gsl_vector_free(ss); /* inital step size */
10943: for (it=0; it<NDIM; it++){
10944: p[it+1]=gsl_vector_get(sfm->x,it);
10945: fprintf(ficrespow," %.12lf", p[it]);
10946: }
10947: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
10948: #endif
10949: #ifdef POWELL
10950: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
10951: #endif
1.126 brouard 10952: fclose(ficrespow);
10953:
1.203 brouard 10954: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 10955:
10956: for(i=1; i <=NDIM; i++)
10957: for(j=i+1;j<=NDIM;j++)
1.220 brouard 10958: matcov[i][j]=matcov[j][i];
1.126 brouard 10959:
10960: printf("\nCovariance matrix\n ");
1.203 brouard 10961: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 10962: for(i=1; i <=NDIM; i++) {
10963: for(j=1;j<=NDIM;j++){
1.220 brouard 10964: printf("%f ",matcov[i][j]);
10965: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 10966: }
1.203 brouard 10967: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 10968: }
10969:
10970: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 10971: for (i=1;i<=NDIM;i++) {
1.126 brouard 10972: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 10973: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
10974: }
1.126 brouard 10975: lsurv=vector(1,AGESUP);
10976: lpop=vector(1,AGESUP);
10977: tpop=vector(1,AGESUP);
10978: lsurv[agegomp]=100000;
10979:
10980: for (k=agegomp;k<=AGESUP;k++) {
10981: agemortsup=k;
10982: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
10983: }
10984:
10985: for (k=agegomp;k<agemortsup;k++)
10986: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
10987:
10988: for (k=agegomp;k<agemortsup;k++){
10989: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
10990: sumlpop=sumlpop+lpop[k];
10991: }
10992:
10993: tpop[agegomp]=sumlpop;
10994: for (k=agegomp;k<(agemortsup-3);k++){
10995: /* tpop[k+1]=2;*/
10996: tpop[k+1]=tpop[k]-lpop[k];
10997: }
10998:
10999:
11000: printf("\nAge lx qx dx Lx Tx e(x)\n");
11001: for (k=agegomp;k<(agemortsup-2);k++)
11002: 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]);
11003:
11004:
11005: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 11006: ageminpar=50;
11007: agemaxpar=100;
1.194 brouard 11008: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
11009: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11010: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11011: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
11012: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11013: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11014: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 11015: }else{
11016: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
11017: 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 11018: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 11019: }
1.201 brouard 11020: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 11021: stepm, weightopt,\
11022: model,imx,p,matcov,agemortsup);
11023:
11024: free_vector(lsurv,1,AGESUP);
11025: free_vector(lpop,1,AGESUP);
11026: free_vector(tpop,1,AGESUP);
1.220 brouard 11027: free_matrix(ximort,1,NDIM,1,NDIM);
1.136 brouard 11028: free_ivector(cens,1,n);
11029: free_vector(agecens,1,n);
11030: free_ivector(dcwave,1,n);
1.220 brouard 11031: #ifdef GSL
1.136 brouard 11032: #endif
1.186 brouard 11033: } /* Endof if mle==-3 mortality only */
1.205 brouard 11034: /* Standard */
11035: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
11036: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11037: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 11038: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 11039: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11040: for (k=1; k<=npar;k++)
11041: printf(" %d %8.5f",k,p[k]);
11042: printf("\n");
1.205 brouard 11043: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
11044: /* mlikeli uses func not funcone */
1.247 brouard 11045: /* for(i=1;i<nlstate;i++){ */
11046: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11047: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11048: /* } */
1.205 brouard 11049: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
11050: }
11051: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
11052: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11053: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
11054: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11055: }
11056: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 11057: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11058: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11059: for (k=1; k<=npar;k++)
11060: printf(" %d %8.5f",k,p[k]);
11061: printf("\n");
11062:
11063: /*--------- results files --------------*/
1.224 brouard 11064: 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 11065:
11066:
11067: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11068: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11069: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11070: for(i=1,jk=1; i <=nlstate; i++){
11071: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 11072: if (k != i) {
11073: printf("%d%d ",i,k);
11074: fprintf(ficlog,"%d%d ",i,k);
11075: fprintf(ficres,"%1d%1d ",i,k);
11076: for(j=1; j <=ncovmodel; j++){
11077: printf("%12.7f ",p[jk]);
11078: fprintf(ficlog,"%12.7f ",p[jk]);
11079: fprintf(ficres,"%12.7f ",p[jk]);
11080: jk++;
11081: }
11082: printf("\n");
11083: fprintf(ficlog,"\n");
11084: fprintf(ficres,"\n");
11085: }
1.126 brouard 11086: }
11087: }
1.203 brouard 11088: if(mle != 0){
11089: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 11090: ftolhess=ftol; /* Usually correct */
1.203 brouard 11091: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
11092: 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");
11093: 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");
11094: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 11095: for(k=1; k <=(nlstate+ndeath); k++){
11096: if (k != i) {
11097: printf("%d%d ",i,k);
11098: fprintf(ficlog,"%d%d ",i,k);
11099: for(j=1; j <=ncovmodel; j++){
11100: 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]));
11101: 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]));
11102: jk++;
11103: }
11104: printf("\n");
11105: fprintf(ficlog,"\n");
11106: }
11107: }
1.193 brouard 11108: }
1.203 brouard 11109: } /* end of hesscov and Wald tests */
1.225 brouard 11110:
1.203 brouard 11111: /* */
1.126 brouard 11112: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
11113: printf("# Scales (for hessian or gradient estimation)\n");
11114: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
11115: for(i=1,jk=1; i <=nlstate; i++){
11116: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 11117: if (j!=i) {
11118: fprintf(ficres,"%1d%1d",i,j);
11119: printf("%1d%1d",i,j);
11120: fprintf(ficlog,"%1d%1d",i,j);
11121: for(k=1; k<=ncovmodel;k++){
11122: printf(" %.5e",delti[jk]);
11123: fprintf(ficlog," %.5e",delti[jk]);
11124: fprintf(ficres," %.5e",delti[jk]);
11125: jk++;
11126: }
11127: printf("\n");
11128: fprintf(ficlog,"\n");
11129: fprintf(ficres,"\n");
11130: }
1.126 brouard 11131: }
11132: }
11133:
11134: 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 11135: if(mle >= 1) /* To big for the screen */
1.126 brouard 11136: 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");
11137: 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");
11138: /* # 121 Var(a12)\n\ */
11139: /* # 122 Cov(b12,a12) Var(b12)\n\ */
11140: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
11141: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
11142: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
11143: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
11144: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
11145: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
11146:
11147:
11148: /* Just to have a covariance matrix which will be more understandable
11149: even is we still don't want to manage dictionary of variables
11150: */
11151: for(itimes=1;itimes<=2;itimes++){
11152: jj=0;
11153: for(i=1; i <=nlstate; i++){
1.225 brouard 11154: for(j=1; j <=nlstate+ndeath; j++){
11155: if(j==i) continue;
11156: for(k=1; k<=ncovmodel;k++){
11157: jj++;
11158: ca[0]= k+'a'-1;ca[1]='\0';
11159: if(itimes==1){
11160: if(mle>=1)
11161: printf("#%1d%1d%d",i,j,k);
11162: fprintf(ficlog,"#%1d%1d%d",i,j,k);
11163: fprintf(ficres,"#%1d%1d%d",i,j,k);
11164: }else{
11165: if(mle>=1)
11166: printf("%1d%1d%d",i,j,k);
11167: fprintf(ficlog,"%1d%1d%d",i,j,k);
11168: fprintf(ficres,"%1d%1d%d",i,j,k);
11169: }
11170: ll=0;
11171: for(li=1;li <=nlstate; li++){
11172: for(lj=1;lj <=nlstate+ndeath; lj++){
11173: if(lj==li) continue;
11174: for(lk=1;lk<=ncovmodel;lk++){
11175: ll++;
11176: if(ll<=jj){
11177: cb[0]= lk +'a'-1;cb[1]='\0';
11178: if(ll<jj){
11179: if(itimes==1){
11180: if(mle>=1)
11181: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11182: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11183: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11184: }else{
11185: if(mle>=1)
11186: printf(" %.5e",matcov[jj][ll]);
11187: fprintf(ficlog," %.5e",matcov[jj][ll]);
11188: fprintf(ficres," %.5e",matcov[jj][ll]);
11189: }
11190: }else{
11191: if(itimes==1){
11192: if(mle>=1)
11193: printf(" Var(%s%1d%1d)",ca,i,j);
11194: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
11195: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
11196: }else{
11197: if(mle>=1)
11198: printf(" %.7e",matcov[jj][ll]);
11199: fprintf(ficlog," %.7e",matcov[jj][ll]);
11200: fprintf(ficres," %.7e",matcov[jj][ll]);
11201: }
11202: }
11203: }
11204: } /* end lk */
11205: } /* end lj */
11206: } /* end li */
11207: if(mle>=1)
11208: printf("\n");
11209: fprintf(ficlog,"\n");
11210: fprintf(ficres,"\n");
11211: numlinepar++;
11212: } /* end k*/
11213: } /*end j */
1.126 brouard 11214: } /* end i */
11215: } /* end itimes */
11216:
11217: fflush(ficlog);
11218: fflush(ficres);
1.225 brouard 11219: while(fgets(line, MAXLINE, ficpar)) {
11220: /* If line starts with a # it is a comment */
11221: if (line[0] == '#') {
11222: numlinepar++;
11223: fputs(line,stdout);
11224: fputs(line,ficparo);
11225: fputs(line,ficlog);
11226: continue;
11227: }else
11228: break;
11229: }
11230:
1.209 brouard 11231: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
11232: /* ungetc(c,ficpar); */
11233: /* fgets(line, MAXLINE, ficpar); */
11234: /* fputs(line,stdout); */
11235: /* fputs(line,ficparo); */
11236: /* } */
11237: /* ungetc(c,ficpar); */
1.126 brouard 11238:
11239: estepm=0;
1.209 brouard 11240: 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 11241:
11242: if (num_filled != 6) {
11243: 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);
11244: 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);
11245: goto end;
11246: }
11247: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
11248: }
11249: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
11250: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
11251:
1.209 brouard 11252: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 11253: if (estepm==0 || estepm < stepm) estepm=stepm;
11254: if (fage <= 2) {
11255: bage = ageminpar;
11256: fage = agemaxpar;
11257: }
11258:
11259: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 11260: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
11261: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 11262:
1.186 brouard 11263: /* Other stuffs, more or less useful */
1.254 brouard 11264: while(fgets(line, MAXLINE, ficpar)) {
11265: /* If line starts with a # it is a comment */
11266: if (line[0] == '#') {
11267: numlinepar++;
11268: fputs(line,stdout);
11269: fputs(line,ficparo);
11270: fputs(line,ficlog);
11271: continue;
11272: }else
11273: break;
11274: }
11275:
11276: 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){
11277:
11278: if (num_filled != 7) {
11279: 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);
11280: 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);
11281: goto end;
11282: }
11283: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
11284: 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);
11285: 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);
11286: 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 11287: }
1.254 brouard 11288:
11289: while(fgets(line, MAXLINE, ficpar)) {
11290: /* If line starts with a # it is a comment */
11291: if (line[0] == '#') {
11292: numlinepar++;
11293: fputs(line,stdout);
11294: fputs(line,ficparo);
11295: fputs(line,ficlog);
11296: continue;
11297: }else
11298: break;
1.126 brouard 11299: }
11300:
11301:
11302: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
11303: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
11304:
1.254 brouard 11305: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
11306: if (num_filled != 1) {
11307: 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);
11308: 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);
11309: goto end;
11310: }
11311: printf("pop_based=%d\n",popbased);
11312: fprintf(ficlog,"pop_based=%d\n",popbased);
11313: fprintf(ficparo,"pop_based=%d\n",popbased);
11314: fprintf(ficres,"pop_based=%d\n",popbased);
11315: }
11316:
1.258 brouard 11317: /* Results */
11318: nresult=0;
11319: do{
11320: if(!fgets(line, MAXLINE, ficpar)){
11321: endishere=1;
11322: parameterline=14;
11323: }else if (line[0] == '#') {
11324: /* If line starts with a # it is a comment */
1.254 brouard 11325: numlinepar++;
11326: fputs(line,stdout);
11327: fputs(line,ficparo);
11328: fputs(line,ficlog);
11329: continue;
1.258 brouard 11330: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
11331: parameterline=11;
11332: else if(sscanf(line,"backcast=%[^\n]\n",modeltemp))
11333: parameterline=12;
11334: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
11335: parameterline=13;
11336: else{
11337: parameterline=14;
1.254 brouard 11338: }
1.258 brouard 11339: switch (parameterline){
11340: case 11:
11341: 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){
11342: if (num_filled != 8) {
11343: 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);
11344: 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);
11345: goto end;
11346: }
11347: 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);
11348: 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);
11349: 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);
11350: 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);
11351: /* day and month of proj2 are not used but only year anproj2.*/
11352: }
1.254 brouard 11353: break;
1.258 brouard 11354: case 12:
11355: /*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);*/
11356: 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){
11357: if (num_filled != 8) {
1.262 brouard 11358: 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);
11359: 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 11360: goto end;
11361: }
11362: 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);
11363: 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);
11364: 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);
11365: 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);
11366: /* day and month of proj2 are not used but only year anproj2.*/
11367: }
1.230 brouard 11368: break;
1.258 brouard 11369: case 13:
11370: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
11371: if (num_filled == 0){
11372: resultline[0]='\0';
11373: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
11374: 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);
11375: break;
11376: } else if (num_filled != 1){
11377: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
11378: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
11379: }
11380: nresult++; /* Sum of resultlines */
11381: printf("Result %d: result=%s\n",nresult, resultline);
11382: if(nresult > MAXRESULTLINES){
11383: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
11384: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
11385: goto end;
11386: }
11387: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
11388: fprintf(ficparo,"result: %s\n",resultline);
11389: fprintf(ficres,"result: %s\n",resultline);
11390: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 11391: break;
1.258 brouard 11392: case 14:
1.259 brouard 11393: if(ncovmodel >2 && nresult==0 ){
11394: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 11395: goto end;
11396: }
1.259 brouard 11397: break;
1.258 brouard 11398: default:
11399: nresult=1;
11400: decoderesult(".",nresult ); /* No covariate */
11401: }
11402: } /* End switch parameterline */
11403: }while(endishere==0); /* End do */
1.126 brouard 11404:
1.230 brouard 11405: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 11406: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 11407:
11408: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 11409: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 11410: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 11411: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11412: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 11413: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 11414: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11415: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 11416: }else{
1.218 brouard 11417: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p);
1.220 brouard 11418: }
11419: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.258 brouard 11420: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,backcast, estepm, \
1.225 brouard 11421: jprev1,mprev1,anprev1,dateprev1,jprev2,mprev2,anprev2,dateprev2);
1.220 brouard 11422:
1.225 brouard 11423: /*------------ free_vector -------------*/
11424: /* chdir(path); */
1.220 brouard 11425:
1.215 brouard 11426: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
11427: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
11428: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
11429: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.126 brouard 11430: free_lvector(num,1,n);
11431: free_vector(agedc,1,n);
11432: /*free_matrix(covar,0,NCOVMAX,1,n);*/
11433: /*free_matrix(covar,1,NCOVMAX,1,n);*/
11434: fclose(ficparo);
11435: fclose(ficres);
1.220 brouard 11436:
11437:
1.186 brouard 11438: /* Other results (useful)*/
1.220 brouard 11439:
11440:
1.126 brouard 11441: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 11442: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
11443: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 11444: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 11445: fclose(ficrespl);
11446:
11447: /*------------- h Pij x at various ages ------------*/
1.180 brouard 11448: /*#include "hpijx.h"*/
11449: hPijx(p, bage, fage);
1.145 brouard 11450: fclose(ficrespij);
1.227 brouard 11451:
1.220 brouard 11452: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 11453: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 11454: k=1;
1.126 brouard 11455: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 11456:
1.219 brouard 11457: /* Prevalence for each covariates in probs[age][status][cov] */
1.218 brouard 11458: probs= ma3x(1,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.126 brouard 11459: for(i=1;i<=AGESUP;i++)
1.219 brouard 11460: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 11461: for(k=1;k<=ncovcombmax;k++)
11462: probs[i][j][k]=0.;
1.219 brouard 11463: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
11464: if (mobilav!=0 ||mobilavproj !=0 ) {
11465: mobaverages= ma3x(1, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.227 brouard 11466: for(i=1;i<=AGESUP;i++)
11467: for(j=1;j<=nlstate;j++)
11468: for(k=1;k<=ncovcombmax;k++)
11469: mobaverages[i][j][k]=0.;
1.219 brouard 11470: mobaverage=mobaverages;
11471: if (mobilav!=0) {
1.235 brouard 11472: printf("Movingaveraging observed prevalence\n");
1.258 brouard 11473: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 11474: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
11475: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
11476: printf(" Error in movingaverage mobilav=%d\n",mobilav);
11477: }
1.219 brouard 11478: }
11479: /* /\* Prevalence for each covariates in probs[age][status][cov] *\/ */
11480: /* prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
11481: else if (mobilavproj !=0) {
1.235 brouard 11482: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 11483: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 11484: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
11485: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
11486: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
11487: }
1.219 brouard 11488: }
11489: }/* end if moving average */
1.227 brouard 11490:
1.126 brouard 11491: /*---------- Forecasting ------------------*/
11492: /*if((stepm == 1) && (strcmp(model,".")==0)){*/
11493: if(prevfcast==1){
11494: /* if(stepm ==1){*/
1.225 brouard 11495: prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
1.126 brouard 11496: }
1.217 brouard 11497: if(backcast==1){
1.219 brouard 11498: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
11499: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
11500: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
11501:
11502: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
11503:
11504: bprlim=matrix(1,nlstate,1,nlstate);
11505: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
11506: fclose(ficresplb);
11507:
1.222 brouard 11508: hBijx(p, bage, fage, mobaverage);
11509: fclose(ficrespijb);
1.219 brouard 11510: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
11511:
11512: /* prevbackforecast(fileresu, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, mobilavproj,
1.225 brouard 11513: bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
1.219 brouard 11514: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
11515: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
11516: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
11517: }
1.217 brouard 11518:
1.186 brouard 11519:
11520: /* ------ Other prevalence ratios------------ */
1.126 brouard 11521:
1.215 brouard 11522: free_ivector(wav,1,imx);
11523: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
11524: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
11525: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 11526:
11527:
1.127 brouard 11528: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 11529:
1.201 brouard 11530: strcpy(filerese,"E_");
11531: strcat(filerese,fileresu);
1.126 brouard 11532: if((ficreseij=fopen(filerese,"w"))==NULL) {
11533: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
11534: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
11535: }
1.208 brouard 11536: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
11537: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 11538:
11539: pstamp(ficreseij);
1.219 brouard 11540:
1.235 brouard 11541: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
11542: if (cptcovn < 1){i1=1;}
11543:
11544: for(nres=1; nres <= nresult; nres++) /* For each resultline */
11545: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 11546: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 11547: continue;
1.219 brouard 11548: fprintf(ficreseij,"\n#****** ");
1.235 brouard 11549: printf("\n#****** ");
1.225 brouard 11550: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 11551: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 11552: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11553: }
11554: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11555: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11556: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 11557: }
11558: fprintf(ficreseij,"******\n");
1.235 brouard 11559: printf("******\n");
1.219 brouard 11560:
11561: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
11562: oldm=oldms;savm=savms;
1.235 brouard 11563: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 11564:
1.219 brouard 11565: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 11566: }
11567: fclose(ficreseij);
1.208 brouard 11568: printf("done evsij\n");fflush(stdout);
11569: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.218 brouard 11570:
1.227 brouard 11571: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 11572:
11573:
1.201 brouard 11574: strcpy(filerest,"T_");
11575: strcat(filerest,fileresu);
1.127 brouard 11576: if((ficrest=fopen(filerest,"w"))==NULL) {
11577: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
11578: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
11579: }
1.208 brouard 11580: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
11581: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.218 brouard 11582:
1.126 brouard 11583:
1.201 brouard 11584: strcpy(fileresstde,"STDE_");
11585: strcat(fileresstde,fileresu);
1.126 brouard 11586: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 11587: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
11588: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 11589: }
1.227 brouard 11590: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
11591: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 11592:
1.201 brouard 11593: strcpy(filerescve,"CVE_");
11594: strcat(filerescve,fileresu);
1.126 brouard 11595: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 11596: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
11597: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 11598: }
1.227 brouard 11599: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
11600: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 11601:
1.201 brouard 11602: strcpy(fileresv,"V_");
11603: strcat(fileresv,fileresu);
1.126 brouard 11604: if((ficresvij=fopen(fileresv,"w"))==NULL) {
11605: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
11606: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
11607: }
1.227 brouard 11608: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
11609: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 11610:
1.145 brouard 11611: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
11612: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
11613:
1.235 brouard 11614: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
11615: if (cptcovn < 1){i1=1;}
11616:
11617: for(nres=1; nres <= nresult; nres++) /* For each resultline */
11618: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 11619: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 11620: continue;
1.242 brouard 11621: printf("\n#****** Result for:");
11622: fprintf(ficrest,"\n#****** Result for:");
11623: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 11624: for(j=1;j<=cptcoveff;j++){
11625: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11626: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11627: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11628: }
1.235 brouard 11629: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11630: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11631: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11632: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11633: }
1.208 brouard 11634: fprintf(ficrest,"******\n");
1.227 brouard 11635: fprintf(ficlog,"******\n");
11636: printf("******\n");
1.208 brouard 11637:
11638: fprintf(ficresstdeij,"\n#****** ");
11639: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 11640: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 11641: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11642: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 11643: }
1.235 brouard 11644: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11645: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11646: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11647: }
1.208 brouard 11648: fprintf(ficresstdeij,"******\n");
11649: fprintf(ficrescveij,"******\n");
11650:
11651: fprintf(ficresvij,"\n#****** ");
1.238 brouard 11652: /* pstamp(ficresvij); */
1.225 brouard 11653: for(j=1;j<=cptcoveff;j++)
1.227 brouard 11654: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 11655: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11656: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11657: }
1.208 brouard 11658: fprintf(ficresvij,"******\n");
11659:
11660: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
11661: oldm=oldms;savm=savms;
1.235 brouard 11662: printf(" cvevsij ");
11663: fprintf(ficlog, " cvevsij ");
11664: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 11665: printf(" end cvevsij \n ");
11666: fprintf(ficlog, " end cvevsij \n ");
11667:
11668: /*
11669: */
11670: /* goto endfree; */
11671:
11672: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
11673: pstamp(ficrest);
11674:
11675:
11676: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 11677: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
11678: cptcod= 0; /* To be deleted */
11679: printf("varevsij vpopbased=%d \n",vpopbased);
11680: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 11681: 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 11682: 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 ");
11683: if(vpopbased==1)
11684: 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);
11685: else
11686: fprintf(ficrest,"the age specific period (stable) prevalences in each health state \n");
11687: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
11688: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
11689: fprintf(ficrest,"\n");
11690: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
11691: epj=vector(1,nlstate+1);
11692: printf("Computing age specific period (stable) prevalences in each health state \n");
11693: fprintf(ficlog,"Computing age specific period (stable) prevalences in each health state \n");
11694: for(age=bage; age <=fage ;age++){
1.235 brouard 11695: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 11696: if (vpopbased==1) {
11697: if(mobilav ==0){
11698: for(i=1; i<=nlstate;i++)
11699: prlim[i][i]=probs[(int)age][i][k];
11700: }else{ /* mobilav */
11701: for(i=1; i<=nlstate;i++)
11702: prlim[i][i]=mobaverage[(int)age][i][k];
11703: }
11704: }
1.219 brouard 11705:
1.227 brouard 11706: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
11707: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
11708: /* printf(" age %4.0f ",age); */
11709: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
11710: for(i=1, epj[j]=0.;i <=nlstate;i++) {
11711: epj[j] += prlim[i][i]*eij[i][j][(int)age];
11712: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
11713: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
11714: }
11715: epj[nlstate+1] +=epj[j];
11716: }
11717: /* printf(" age %4.0f \n",age); */
1.219 brouard 11718:
1.227 brouard 11719: for(i=1, vepp=0.;i <=nlstate;i++)
11720: for(j=1;j <=nlstate;j++)
11721: vepp += vareij[i][j][(int)age];
11722: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
11723: for(j=1;j <=nlstate;j++){
11724: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
11725: }
11726: fprintf(ficrest,"\n");
11727: }
1.208 brouard 11728: } /* End vpopbased */
11729: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
11730: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
11731: free_vector(epj,1,nlstate+1);
1.235 brouard 11732: printf("done selection\n");fflush(stdout);
11733: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 11734:
1.145 brouard 11735: /*}*/
1.235 brouard 11736: } /* End k selection */
1.227 brouard 11737:
11738: printf("done State-specific expectancies\n");fflush(stdout);
11739: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
11740:
1.126 brouard 11741: /*------- Variance of period (stable) prevalence------*/
1.227 brouard 11742:
1.201 brouard 11743: strcpy(fileresvpl,"VPL_");
11744: strcat(fileresvpl,fileresu);
1.126 brouard 11745: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
11746: printf("Problem with variance of period (stable) prevalence resultfile: %s\n", fileresvpl);
11747: exit(0);
11748: }
1.208 brouard 11749: printf("Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
11750: fprintf(ficlog, "Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.227 brouard 11751:
1.145 brouard 11752: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
11753: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
1.227 brouard 11754:
1.235 brouard 11755: i1=pow(2,cptcoveff);
11756: if (cptcovn < 1){i1=1;}
11757:
11758: for(nres=1; nres <= nresult; nres++) /* For each resultline */
11759: for(k=1; k<=i1;k++){
1.253 brouard 11760: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 11761: continue;
1.227 brouard 11762: fprintf(ficresvpl,"\n#****** ");
11763: printf("\n#****** ");
11764: fprintf(ficlog,"\n#****** ");
11765: for(j=1;j<=cptcoveff;j++) {
11766: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11767: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11768: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11769: }
1.235 brouard 11770: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11771: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11772: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11773: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11774: }
1.227 brouard 11775: fprintf(ficresvpl,"******\n");
11776: printf("******\n");
11777: fprintf(ficlog,"******\n");
11778:
11779: varpl=matrix(1,nlstate,(int) bage, (int) fage);
11780: oldm=oldms;savm=savms;
1.235 brouard 11781: varprevlim(fileres, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, &ncvyear, k, strstart, nres);
1.227 brouard 11782: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
1.145 brouard 11783: /*}*/
1.126 brouard 11784: }
1.227 brouard 11785:
1.126 brouard 11786: fclose(ficresvpl);
1.208 brouard 11787: printf("done variance-covariance of period prevalence\n");fflush(stdout);
11788: fprintf(ficlog,"done variance-covariance of period prevalence\n");fflush(ficlog);
1.227 brouard 11789:
11790: free_vector(weight,1,n);
11791: free_imatrix(Tvard,1,NCOVMAX,1,2);
11792: free_imatrix(s,1,maxwav+1,1,n);
11793: free_matrix(anint,1,maxwav,1,n);
11794: free_matrix(mint,1,maxwav,1,n);
11795: free_ivector(cod,1,n);
11796: free_ivector(tab,1,NCOVMAX);
11797: fclose(ficresstdeij);
11798: fclose(ficrescveij);
11799: fclose(ficresvij);
11800: fclose(ficrest);
11801: fclose(ficpar);
11802:
11803:
1.126 brouard 11804: /*---------- End : free ----------------*/
1.219 brouard 11805: if (mobilav!=0 ||mobilavproj !=0)
11806: free_ma3x(mobaverages,1, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
1.218 brouard 11807: free_ma3x(probs,1,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 11808: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
11809: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 11810: } /* mle==-3 arrives here for freeing */
1.227 brouard 11811: /* endfree:*/
11812: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
11813: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
11814: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
11815: free_ma3x(cotqvar,1,maxwav,1,nqtv,1,n);
1.233 brouard 11816: free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,1,n);
1.227 brouard 11817: free_matrix(coqvar,1,maxwav,1,n);
11818: free_matrix(covar,0,NCOVMAX,1,n);
11819: free_matrix(matcov,1,npar,1,npar);
11820: free_matrix(hess,1,npar,1,npar);
11821: /*free_vector(delti,1,npar);*/
11822: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11823: free_matrix(agev,1,maxwav,1,imx);
11824: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11825:
11826: free_ivector(ncodemax,1,NCOVMAX);
11827: free_ivector(ncodemaxwundef,1,NCOVMAX);
11828: free_ivector(Dummy,-1,NCOVMAX);
11829: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 11830: free_ivector(DummyV,1,NCOVMAX);
11831: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 11832: free_ivector(Typevar,-1,NCOVMAX);
11833: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 11834: free_ivector(TvarsQ,1,NCOVMAX);
11835: free_ivector(TvarsQind,1,NCOVMAX);
11836: free_ivector(TvarsD,1,NCOVMAX);
11837: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 11838: free_ivector(TvarFD,1,NCOVMAX);
11839: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 11840: free_ivector(TvarF,1,NCOVMAX);
11841: free_ivector(TvarFind,1,NCOVMAX);
11842: free_ivector(TvarV,1,NCOVMAX);
11843: free_ivector(TvarVind,1,NCOVMAX);
11844: free_ivector(TvarA,1,NCOVMAX);
11845: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 11846: free_ivector(TvarFQ,1,NCOVMAX);
11847: free_ivector(TvarFQind,1,NCOVMAX);
11848: free_ivector(TvarVD,1,NCOVMAX);
11849: free_ivector(TvarVDind,1,NCOVMAX);
11850: free_ivector(TvarVQ,1,NCOVMAX);
11851: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 11852: free_ivector(Tvarsel,1,NCOVMAX);
11853: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 11854: free_ivector(Tposprod,1,NCOVMAX);
11855: free_ivector(Tprod,1,NCOVMAX);
11856: free_ivector(Tvaraff,1,NCOVMAX);
11857: free_ivector(invalidvarcomb,1,ncovcombmax);
11858: free_ivector(Tage,1,NCOVMAX);
11859: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 11860: free_ivector(TmodelInvind,1,NCOVMAX);
11861: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 11862:
11863: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
11864: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 11865: fflush(fichtm);
11866: fflush(ficgp);
11867:
1.227 brouard 11868:
1.126 brouard 11869: if((nberr >0) || (nbwarn>0)){
1.216 brouard 11870: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
11871: 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 11872: }else{
11873: printf("End of Imach\n");
11874: fprintf(ficlog,"End of Imach\n");
11875: }
11876: printf("See log file on %s\n",filelog);
11877: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 11878: /*(void) gettimeofday(&end_time,&tzp);*/
11879: rend_time = time(NULL);
11880: end_time = *localtime(&rend_time);
11881: /* tml = *localtime(&end_time.tm_sec); */
11882: strcpy(strtend,asctime(&end_time));
1.126 brouard 11883: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
11884: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 11885: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 11886:
1.157 brouard 11887: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
11888: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
11889: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 11890: /* printf("Total time was %d uSec.\n", total_usecs);*/
11891: /* if(fileappend(fichtm,optionfilehtm)){ */
11892: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
11893: fclose(fichtm);
11894: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
11895: fclose(fichtmcov);
11896: fclose(ficgp);
11897: fclose(ficlog);
11898: /*------ End -----------*/
1.227 brouard 11899:
11900:
11901: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 11902: #ifdef WIN32
1.227 brouard 11903: if (_chdir(pathcd) != 0)
11904: printf("Can't move to directory %s!\n",path);
11905: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 11906: #else
1.227 brouard 11907: if(chdir(pathcd) != 0)
11908: printf("Can't move to directory %s!\n", path);
11909: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 11910: #endif
1.126 brouard 11911: printf("Current directory %s!\n",pathcd);
11912: /*strcat(plotcmd,CHARSEPARATOR);*/
11913: sprintf(plotcmd,"gnuplot");
1.157 brouard 11914: #ifdef _WIN32
1.126 brouard 11915: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
11916: #endif
11917: if(!stat(plotcmd,&info)){
1.158 brouard 11918: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 11919: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 11920: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 11921: }else
11922: strcpy(pplotcmd,plotcmd);
1.157 brouard 11923: #ifdef __unix
1.126 brouard 11924: strcpy(plotcmd,GNUPLOTPROGRAM);
11925: if(!stat(plotcmd,&info)){
1.158 brouard 11926: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 11927: }else
11928: strcpy(pplotcmd,plotcmd);
11929: #endif
11930: }else
11931: strcpy(pplotcmd,plotcmd);
11932:
11933: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 11934: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.227 brouard 11935:
1.126 brouard 11936: if((outcmd=system(plotcmd)) != 0){
1.158 brouard 11937: printf("gnuplot command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 11938: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 11939: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.150 brouard 11940: if((outcmd=system(plotcmd)) != 0)
1.153 brouard 11941: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.126 brouard 11942: }
1.158 brouard 11943: printf(" Successful, please wait...");
1.126 brouard 11944: while (z[0] != 'q') {
11945: /* chdir(path); */
1.154 brouard 11946: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 11947: scanf("%s",z);
11948: /* if (z[0] == 'c') system("./imach"); */
11949: if (z[0] == 'e') {
1.158 brouard 11950: #ifdef __APPLE__
1.152 brouard 11951: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 11952: #elif __linux
11953: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 11954: #else
1.152 brouard 11955: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 11956: #endif
11957: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
11958: system(pplotcmd);
1.126 brouard 11959: }
11960: else if (z[0] == 'g') system(plotcmd);
11961: else if (z[0] == 'q') exit(0);
11962: }
1.227 brouard 11963: end:
1.126 brouard 11964: while (z[0] != 'q') {
1.195 brouard 11965: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 11966: scanf("%s",z);
11967: }
11968: }
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